Does somatosensory function relate to bimanual function in children with unilateral cerebral palsy?

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Lize Kleeren, Lisa Mailleux, Anja Van Campenhout, Olivier Lambercy, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9201856/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Goal-directed bimanual movements rely on the integration of somatosensory information to plan and adjust motor actions. In children with unilateral cerebral palsy (uCP), previous studies have primarily relied on clinical assessments of bimanual function and proprioception, whereas robotic and instrumented assessments may provide more precise and objective measures to further outline this relationship. Objectives To investigate the association between tactile registration, tactile perception, proprioception and bimanual function in children with uCP, using both clinical and instrumented assessments. Methods In this cross-sectional study, sixty-one children with uCP (mean age 11y11mo (SD 3y0mo); 35 males) completed assessments of tactile registration, tactile perception and proprioception. Bimanual function was evaluated through functional hand use (Assisting Hand Assessment; Children’s Hand-Use Experience Questionnaire), bimanual dexterity (Tyneside pegboard Test) and bimanual coordination (Ball-on-Bar task on the Kinarm robot; Box opening task). Associations were investigated using correlations (r/r s ) and multiple linear regressions (R²). Results Worse tactile registration was weakly associated with reduced functional hand use (rₛ=-0.320-(-0.408), p ≤ 0.032). Worse tactile perception showed low to moderate associations with reduced functional hand use ( r ₛ=-0.348-(-0.626), p ≤ 0.023), slower bimanual dexterity ( r ₛ=-0.478-(-0.574), p < 0.001) and poorer coordination (| r ₛ|=0.357–0.501, p < 0.022). Proprioceptive impairments were generally lowly to moderately related to functional hand use ( r ₛ=-0.236-(-0.493), p < 0.113) and bimanual dexterity ( r ₛ=0.279–0.509, p < 0.095). Regression analyses indicated that two-point discrimination, distal position sense and proximal position sense explained respectively 33–40% and 58% of the variance in functional hand use ( p < 0.050) and of bimanual dexterity ( p < 0.050). Variability in bimanual coordination was only minimally explained by proprioceptive measures (R²=4%-9%, p = 0.024–0.081). Conclusions Higher-order tactile perception and proprioception are particularly relevant for functional hand use and bimanual dexterity in children with uCP, whereas associations with bimanual coordination are more task- and parameter dependent. The results emphasize the importance of integrating somatosensory assessments into the follow-up of children with uCP to further understand bimanual impairments. Developmental Neuroscience Pediatrics Physical Medicine & Rehab Upper limb somatosensation proprioception bimanual function unilateral cerebral palsy children 1. INTRODUCTION Goal-directed movements depend on the accurate integration of somatosensory input, which provides the feedback necessary to plan, guide and adjust motor actions [ 1 , 2 ]. Integration of tactile and proprioceptive information relies on distributed neural networks [ 3 ]. Early brain lesions, such as those occurring in children with cerebral palsy (CP), can disrupt these networks, leading to somatosensory impairments and altered sensorimotor processing [ 4 – 6 ]. Unilateral cerebral palsy (uCP) is the most prevalent subtype, accounting for approximately 40% of the cases [ 7 ]. Although motor impairments are the most apparent symptom in children with uCP, somatosensory impairments are a well-established comorbidity [ 8 – 11 ]. Somatosensation refers to the ability to process and interpret bodily sensory information and encompasses tactile function and proprioception [ 12 ]. Tactile function further includes tactile registration, reflecting the initial awareness of a tactile stimulus and tactile perception, which additionally involves interpretation of the stimulus [ 13 ]. Proprioception, in turn, refers to the ability to accurately perceive limb positions and movements [ 14 ]. Previous studies have shown that somatosensory impairments across all modalities are common in children with uCP, with reported prevalence rates of up to 90% [ 8 – 11 ]. Somatosensory impairments may further compromise the execution of complex motor actions, particularly bimanual tasks requiring coordinated use of both hands. During the performance of bimanual activities, continuous integration of tactile and proprioceptive information is essential to synchronize the movements of both hands and ensure successful task performance [ 1 ]. For example, when opening a container, tactile feedback provides information about surface properties and lid position, needed to regulate grip forces and appropriately position the hands. Proprioceptive input from both hands additionally supports stabilization of the container as the other hand twists or pulls off the lid. Two recent systematic reviews indeed reported a moderate to high association between tactile perception and bimanual function in children with CP [ 15 , 16 ]. For tactile registration, however, evidence was limited with only five studies investigating this relation, of which three reported no to low associations [ 15 ]. Information regarding proprioception is also scarce, with only a few studies reporting conflicting associations ranging from no to moderate association [ 15 – 17 ]. As proprioceptive accuracy has shown to be site- and method-specific, variability in assessment approaches may partially explain these inconsistencies [ 18 ]. Moreover, quantifying proprioception remains challenging due to the limited precision of current clinical assessments [ 19 ]. Robot-assisted technological assessments may overcome these limitations and provide deeper insight into the relation between proprioception and bimanual function. Moreover, bimanual function is often evaluated using self-reported questionnaires or functional hand use measures, such as the Assisting Hand Assessment (AHA). While these tools are clinically relevant and widely used, they may not capture the precise temporal and spatial coordination between both hands [ 20 , 21 ]. In contrast, technological assessments can provide detailed insight into complex bimanual motor tasks, including bimanual dexterity or the ability to perform fast and accurate movements and bimanual coordination or the ability to synchronize the upper limbs for a common goal [ 22 – 24 ]. Innovative tools such as three-dimensional motion analysis and robotics have been proposed to assess these aspects [ 25 , 26 ]. Nevertheless, to the best of our knowledge, such fine-grained bimanual assessments have not yet been used to further delineate their potential relation with somatosensation in children with uCP. Therefore, the main aims of this study were to: (1) map the relation between tactile registration, tactile perception, proprioception and different aspects of bimanual function, using a comprehensive test-battery encompassing functional hand use, bimanual dexterity and bimanual coordination; and (2) explore the extent to which somatosensory function explains variability across these different aspects of bimanual function. We additionally examined the association between measures of functional hand use and instrumented measures of bimanual dexterity and bimanual coordination to provide insight into the relationship between the different aspects of bimanual function. We hypothesized to find low to moderate correlations between tactile perception and proprioception and bimanual function, with stronger correlations expected for functional hand use and bimanual dexterity. We further expected that tactile perception and distal position sense would account for part of the variability in functional hand use, bimanual dexterity and bimanual coordination as measured with the box opening task, while variability in bimanual coordination measured with the Kinarm exoskeleton would be more determined by proximal position sense. 2. MATERIAL AND METHODS 2.1. Participants Children with spastic uCP were recruited through the Cerebral Palsy Reference Center at the University Hospitals Leuven (Belgium). Eligible participants were between 7 and 15 years old, able to understand the assessment instructions and could actively grasp and hold an object with the more-impaired hand (House Functional Classification System ≥ 4) [ 27 ]. Children were excluded if they had received upper limb botulinum neurotoxin-A injection within the previous six months or had undergone upper limb surgery within the two previous years. Ethical approval was granted by the Ethics Committee Research UZ/KU Leuven (S62906 and S67467). Written informed consent was obtained from the parents before participation. Children aged 12 years or older provided additional assent to participate. 2.2. Assessments 2.2.1. Somatosensory function Somatosensory assessments were performed for the more-impaired upper limb only and comprised clinical measures of tactile registration and tactile perception as well as clinical and robotic measures of proprioception. Further details regarding the somatosensory assessments can be found elsewhere [ 11 ]. Tactile registration was assessed on the ventral surface of the index fingertip using the 20-item Semmes-Weinstein monofilaments (Jamar® Monofilaments, Bolingbrook, IL) [ 28 , 29 ]. The assessment began with the filament representing the upper boundary of intact tactile registration (0.07 grams). Next, the difficulty was adapted based on the participant’s response. The outcome corresponded to the thinnest filament that was correctly detected across three consecutive touches and was categorized as “intact” (0.008–0.07 grams), “impaired” (0.16–300 grams) and “absent” (if touches with the largest monofilament could not be perceived (> 300 grams)). Tactile perception comprised stereognosis and two-point discrimination [ 30 ]. During the assessment of stereognosis , participants were asked to identify six out of 12 familiar objects, including three paired objects of similar size and shape (i.e., pen/pencil, coin/button, paperclip/safety pin) and three distinct items (e.g., marble, spoon, comb, ball, clothespin, key). The total number of correctly identified objects was recorded and further classified as “intact” (6 objects identified), “impaired” (4–5 objects) or “absent” (≤ 3 objects). Two-point discrimination was assessed on the ventral side of the index fingertip using an aesthesiometer (Lafayette Instrument, IN). Testing began at four millimeters and was adjusted according to the child’s performance. The minimal distance recognized as two separate points across five consecutive trials was determined and classified as “intact” (2–4 mm), “impaired” (5–10 mm) or “absent” (> 10 mm). Proprioception was assessed clinically by testing movement sense of the index finger [ 30 ]. Participants were asked to indicate when they perceived small-amplitude movements; if these were not detected, larger movements were performed. Movement sense was classified as “intact” when three small-amplitude movements were correctly perceived, “impaired” when only larger movements were detected and “absent” when no movements were perceived. Next, previously validated robot-assisted assessments were used to further quantify proprioception. Participants performed a contralateral position matching task on the Kinarm exoskeleton robot (BKIN Technologies Ltd, Kingston, Canada) to evaluate position sense of the shoulder and elbow joints, which will be referred to as proximal position sense [ 11 , 31 ]. In this task, the robot passively moves the more-impaired limb to one of four targets positioned in a 12-cm square. The participant then actively mirror matches this position as precisely as possible with the less-impaired upper limb. Two parameters were calculated by the Kinarm software, namely the absolute error (i.e., mean of the absolute distance between the actual and matched position in the X and Y directions) and variability (i.e., root-sum-square of the standard deviations of the matched position in the X and Y directions). The ETH MIKE (Motor Impairment and Kinesthetic Evaluation) end-effector (Rehabilitation Engineering Laboratory, ETH Zurich, Zurich, Switzerland) measured position sense of the metacarpophalangeal joint or distal position sense [ 11 , 32 ]. During the passive position sense task, the index finger of the participant is moved passively from a 0°-flexion position to one of 11 predefined positions, spaced every 2° between 10° and 30° of metacarpophalangeal flexion. Participants then indicate the perceived finger position on a tablet positioned above their hand. This results again in two task parameters representing the absolute error (i.e., mean of the absolute difference between the actual and indicated position of the index finger) and variability (i.e., standard deviation of the absolute error across all trials). Further details regarding the robotic assessments can be found elsewhere [ 11 , 31 ]. 2.2.2. Bimanual function Different aspects of bimanual function were evaluated using both clinical measures of functional hand use and instrumented assessments of bimanual dexterity and coordination. Further details regarding the instrumented bimanual assessments can be found elsewhere [ 23 , 33 , 34 ]. Functional hand use was evaluated using the fifth version of the AHA and the Children’s Hand-Use Experience Questionnaire (CHEQ 2.0). The AHA measures bimanual performance, which is defined as the spontaneous use of the more-impaired hand during bimanual tasks. Participants played a semi-structured board game that was video recorded [ 35 ]. Afterwards, 20 items related to upper limb function were scored on a 4-point scale. The CHEQ captures the subjective experience of the child’s hand use during 27 bimanual daily life activities ( http://www.cheq.se ) [ 36 ]. The questionnaire was completed by the parents of the participants. It includes three subscales, that are all scored on a 4-point scale: (1) grasp effectiveness of the more-impaired hand (CHEQ-grip), (2) time required to complete the activity (CHEQ-time) and (3) the level of hindrance experienced by the more-impaired hand during task performance (CHEQ-feeling). For both assessments, raw scores are converted to a 0-100 logit-based scale, with higher scores indicating better performance. Bimanual dexterity was assessed using the Tyneside Pegboard Test (TPT; Newcastle University, Newcastle upon Tyne, UK) [ 23 , 24 ]. Participants were asked to transfer nine pegs as fast as possible from one board to an adjacent one, by passing it through an opening in a Perspex screen that was positioned between both boards. Completion times were recorded in two directions, namely from the more-impaired to the less-impaired hand (TPT MI−LI ) and from the less-impaired to the more-impaired hand (TPT LI−MI ). Bimanual coordination was measured using the box opening task , where participants opened a box with the less-impaired hand and pressed a button inside with the more-impaired hand at a self-selected pace [ 25 , 34 ]. Hand movements were recorded at a frequency of 120 Hz using three-dimensional electromagnetic motion sensors from Polhemus G4 (Polhemus, Colchester, Vermont, USA). Two bimanual parameters were calculated using MATLAB R2022a (The Mathworks Inc., Natick, MA, USA), namely the total movement time (i.e., average time needed to complete the task) and goal synchronization (i.e., the temporal coupling between the end of movement of both hands, normalized for total movement time). For both parameters, higher scores indicate poorer bimanual coordination. Bimanual coordination was additionally assessed using the second level of the Ball-on-Bar (BoB) task on the Kinarm exoskeleton robot [ 31 , 33 ]. Here, participants balanced a ball on a virtual bar, while reaching targets appearing on the screen. Three bimanual parameters, calculated by the Kinarm software, were selected based on the study of Decraene et al., namely bar tilt standard deviation (i.e., variability of the bar angle during the task), hand speed difference (i.e., difference between absolute hand speeds normalized by the mean hand speed) and hand path length bias (i.e., difference in hand path length between hands). These parameters have previously shown to be the most discriminative between children with uCP and typically developing children [ 33 ]. Lower scores on these parameters represent better bimanual coordination. 2.3. Statistical analysis SPSS Statistics version 30.0 (IBM, Armonk, New York, USA) was used for all statistical analyses. Descriptive statistics were used to summarize the demographic information and clinical characteristics of the participants. The number of participants classified as having “intact”, “impaired” or “absent” somatosensory function, based on the clinical assessments, was determined according to the cut-off values described above. For the robotic assessments, z-scores were computed to determine the number of participants with an impairment in proximal and/or distal position sense. Z-scores were calculated using the formula: Z=(x-x̄)/S, where x represents the individual score of the participant and x̄ and S are respectively the mean and standard deviation of a control group consisting of 58 typically developing children (mean age 11y9mo (SD 2y9mo); 28 males)). Proximal and distal position sense were then classified as “intact” when the Z-scores of both parameters (i.e., absolute error and variability) were lower than 1.96, “impaired” when the Z-score of one of the two parameters was higher than 1.96 and “absent” when both Z-scores were higher than 1.96. First, data normality was evaluated using Shapiro-Wilk tests. As the somatosensory data were not normally distributed, Spearman’s rank correlations (r s ) were performed to map the relation between tactile registration, tactile perception, proprioception and bimanual function. A false discovery rate (adjusted p-value ≤ 0.05) for multiple testing correction was applied [ 37 ]. Correlation coefficients were interpreted as no or negligible (< 0.30), low (0.30–0.49), moderate (0.50–0.69), high (0.70–0.89) or very high (≥ 0.90) [ 38 ]. Secondly, to explore the extent to which measures of somatosensory function explain variability across measures of bimanual function, we performed multiple regression models with backward elimination. Multiple regressions models were made for the AHA and the feeling subscale of the CHEQ. The latter was selected as the level of hindrance experienced during bimanual tasks was expected to be most clinically relevant to children with uCP. For bimanual dexterity and bimanual coordination, parameters were selected based on the results of the correlation analyses, excluding the parameters with no significant correlation (p > 0.05) with any of the somatosensory assessments. Furthermore, we selected the parameters that showed to be the most discriminative between typically developing children and children with uCP in previous research, resulting in the following selection: the less-impaired to the more-impaired hand condition for the TPT, goal synchronization for the box opening task and hand path length bias for the BoB task of the Kinarm exoskeleton [ 23 , 33 , 34 ]. For the independent variables, a selection was also made based on clinical reasoning, as approximately one independent variable should be included per 10 participants [ 39 ]. More specifically, we selected at least one measure of each somatosensory modality, with the least interference of motor impairments expected and mostly reflecting the magnitude of somatosensory deficits rather than the consistency in performance across repetitions. This resulted in the following selection: Semmes-Weinstein monofilaments, two-point discrimination, movement sense and the absolute error of distal and proximal position sense. Multicollinearity between the independent variables was investigated using the variance inflation factor, with a value above 10 indicating multicollinearity. Outlier detection was based on the scatterplots of the standardized residuals, with values of more than 3.3 or less than − 3.3 being considered as outliers [ 40 ]. In the regression models for the parameters of bimanual coordination, some outliers were identified. Therefore, analyses were repeated removing one extreme outlier for the goal synchronization of the box opening task model and two extreme outliers for hand path length bias of the Kinarm BoB task model. For all the multiple regression analyses, the variance inflation factor ranged from 1.00 to 2.16, indicating low multicollinearity between the independent variables. Lastly, to study the relation between measures of functional hand use and instrumented measures of bimanual dexterity and coordination, Pearson (r) or Spearman’s rank (r s ) correlations were performed, depending on the normality of the data. A false discovery rate (adjusted p-value ≤ 0.05) was again applied [ 37 ] and correlation coefficients were interpreted as no or negligible (< 0.30), low (0.30–0.49), moderate (0.50–0.69), high (0.70–0.89) or very high (≥ 0.90) [ 38 ]. 3. RESULTS 3.1 Participants A total of 61 children with uCP participated in this study. An overview of the demographic information and clinical characteristics is presented in Table 1. Technical issues with the robotic and instrumented assessments caused some missing data; distal and proximal position sense were missing in five participants, the TPT in 12 participants, the box opening task in 13 and the BoB task on the Kinarm exoskeleton in four participants. Table 1. Demographic information and clinical characteristics of the participants. uCP (N=61), N (%) Mean age (SD) 11y 11mo (3y 0mo) Sex Male 35 (57) Female 26 (43) Side of cerebral palsy Right-sided 32 (52) Left-sided 29 (48) MACS I 28 (46) II 24 (39) III 9 (15) Tactile registration Semmes-Weinstein monofilaments Intact (0.008-0.07 grams) 33 (54) Impaired (0.16-300 grams) 25 (41) Absent (>300 grams) 3 (5) Tactile perception Stereognosis Intact (6/6 objects identified) 18 (30) Impaired (4-5/6 objects identified) 28 (38) Absent (≤3/6 objects identified) 20 (32) Two-point discrimination Intact (2-4 millimeters) 34 (55) Impaired (5-10 millimeters) 18 (30) Absent (>10 millimeters) 9 (15) Proprioception Movement sense Intact (3/3 small movements detected) 45 (73) Impaired (1/3 larger movements detected) 12 (20) Absent (no movement detected) 4 (7) Distal position sense Intact (both Z-scores 1.96) 17 (30) Absent (both Z-scores >1.96) 18 (32) Proximal position sense Intact (both Z-scores 1.96) 7 (13) Absent (both Z-scores >1.96) 26 (46) MACS: Manual Ability Classification System; mo: months; SD: standard deviation; y: years. 3.2 Relation between somatosensory and bimanual function Table 2 shows the correlation coefficients between measures of tactile registration, tactile perception, proprioception and functional hand use, bimanual dexterity and bimanual coordination. Overall, several low to moderate correlations were found between somatosensory function and bimanual function, particularly for tactile perception and proprioception. Children with worse tactile registration needed more time and were more hindered by their more-impaired hand when performing bimanual daily live activities (rₛ=-0.320-(-0.408), p ≤0.032), but no significant relationship was found with bimanual dexterity or coordination. For tactile perception , worse stereognosis and two-point discrimination was lowly to moderately related to worse functional hand use ( r ₛ=-0.348-(-0.626), p ≤0.023), slower performance of dexterous movements ( r ₛ=-0.478-(-0.574), p <0.001) and worse bimanual coordination (| r ₛ|=0.357-0.501, p <0.022). Lastly, poorer proprioceptive accuracy was generally lowly related to reduced functional hand use ( r ₛ=-0.236-(-0.493), p <0.113), bimanual dexterity ( r ₛ=0.279-0.509, p <0.095) and with some parameters of bimanual coordination. Most notably, larger hand speed differences during the Kinarm BoB task related to worse movement sense ( r ₛ=-0.315, p =0.036), distal ( r ₛ=0.304-0.363, p <0.048) and proximal position sense ( r ₛ=0.359-0.454, p <0.022). Larger distal position sense errors were further related to reduced goal synchronization in the box opening task ( r ₛ=0.327, p =0.048), while worse proximal position sense related to larger bar tilt standard deviation and hand path length bias during the Kinarm BOB task ( r ₛ=0.305-0.395, p <0.042). Table 2. Spearman’s rank correlation coefficients between measures of tactile registration, tactile perception, proprioception and bimanual function Tactile registration Tactile perception Proprioception Semmes-Weinstein monofilaments Stereognosis Two-point discrimination Movement sense Distal position sense - absolute error Distal position sense - variability Proximal position sense - absolute error Proximal position sense - variability Functional hand use AHA -0.293 0.619 -0.626 0.335 -0.307 -0.320 -0.428 -0.493 CHEQ Grip -0.273 0.531 -0.459 0.290 -0.338 -0.266 -0.356 -0.302 Time -0.320 0.460 -0.348 0.309 -0.308 -0.311 -0.388 -0.350 Feeling -0.408 0.541 -0.442 0.342 -0.249 -0.236 -0.415 -0.355 Bimanual dexterity TPT MI to LI 0.229 -0.478 0.479 -0.343 0.279 0.335 0.351 0.509 LI to MI 0.231 -0.551 0.574 -0.356 0.328 0.345 0.364 0.472 Bimanual coordination Box opening task Total movement time 0.294 -0.254 0.129 -0.289 0.174 0.082 0.156 0.09 Goal synchronization 0.107 -0.217 0.182 -0.096 0.327 0.211 0.104 0.161 Kinarm BoB Bar tilt standard deviation 0.111 -0.357 0.256 -0.171 0.058 0.166 0.305 0.395 Hand speed difference 0.260 -0.501 0.499 -0.315 0.363 0.304 0.359 0.454 Hand path length bias 0.242 -0.199 0.114 -0.147 0.156 0.217 0.362 0.288 AHA: Assisting Hand Assessment; BoB: Ball-on-Bar task; CHEQ: Children's Hand-Use Experience Questionnaire; LI to MI: From the less-impaired to the more-impaired hand; MI to LI: From the more-impaired to the less-impaired hand; TPT: Tyneside Pegboard Test. Strength of correlation coefficients: light green = low, green = moderate, dark green = high. Significance: bold = significant correlation with adjusted FDR-p≤0.05, bold italic = significant correlation with FDR-adjusted p≤0.01. 3.3 Variability in bimanual function explained by somatosensory function Table 3 presents the results of the multiple regression analyses. Two-point discrimination emerged as the main determinant explaining a substantial proportion of variance in functional hand use and bimanual dexterity (R²=0.167-0.292 p <0.001). Proximal position sense additionally determined functional hand use, as assessed with the AHA and CHEQ-feeling (R²=0.050-0.113, p ≤0.046), while distal position sense further explained bimanual dexterity (TPT LI-MI , R²=0.084, p =0.006). Distal position sense was also the only significant predictor of goal synchronization of the box opening task (R²=0.115, p =0.006), while proximal position sense was identified for hand path length bias of the Kinarm BoB task, however, this model did not reach significance ( proximal position sense : R²=0.062, p =0.081). Table 3. Overview of the final models of the multiple regressions analysis on distinct components of bimanual function. Adjusted R² Retained predictors p -value Unique R² B (95% CI) β Functional hand use AHA 0.395 Two-point discrimination <0.001 0.292 -3.132 (-4.400; -1.864) -0.555 Proximal position sense - absolute error 0.046 0.050 -102.672 (-203.343; -2.001) -0.229 CHEQ-feeling 0.334 Two-point discrimination <0.001 0.167 -2.419 (-3.780; -1.058) -0.419 Proximal position sense - absolute error 0.005 0.113 -158.315 (-266.369; -50.262) -0.345 Bimanual dexterity TPT - LI to MI 0.576 Two-point discrimination <0.001 0.337 6.324 (4.140; 8.507) 0.614 Distal position sense - absolute error 0.006 0.084 1.078 (0.335; 1.822) 0.308 Bimanual coordination Box opening task - goal synchronization 0.094 Distal position sense - absolute error 0.024 0.115 0.004 (0.001; 0.007) 0.339 Kinarm BoB task - hand path length bias 0.043 Proximal position sense - absolute error 0.081 0.062 0.268 (-0.034; 0.571) 0.249 Adjusted R² = Degree of variance of the bimanual function assessment that is explained by the retained predictors; AHA: Assisting Hand Assessment; B: Unstandardized coefficient; β : Standardized coefficients; BoB: Ball-on-Bar task; CHEQ: Children's Hand-Use Experience Questionnaire; CI: Confidence interval; LI to MI: From the less-impaired to the more-impaired hand; TPT: Tyneside Pegboard Test; Unique R²: Degree of variance of the bimanual function assessment that is uniquely explained by one specific retained predictor. 3.4 Relation between functional hand use, bimanual dexterity and coordination Correlation coefficients between measures of functional hand use, bimanual dexterity and coordination can be found in Table 4. Firstly, the TPT correlated moderately to highly with both measures of functional hand use (AHA: r s =-0.682-(-0.757), p <0.001; CHEQ: r s =-0.577-(-0.707), p <0.001), showing that worse bimanual dexterity was related to worse functional hand use. Secondly, the box opening task showed that worse goal synchronization and longer movement time were lowly related to worse functional hand use (r s =-0.365-(-0.395), p ≤0.016). Lastly, for the BoB task of the Kinarm robot , higher bar tilt standard deviation and hand speed difference were associated with worse functional hand use (r/r s =-0.332-(-0.665), p ≤0.016), while hand path length bias did not show any significant correlation (r s =-0.161-(-0.263), p >0.061). Table 4. Pearson and spearman’s rank correlation coefficients between measures of functional hand use and measures of bimanual dexterity and coordination Functional hand use AHA CHEQ-grip CHEQ-time CHEQ-feeling Bimanual dexterity TPT MI to LI -0.682 -0.617 -0.577 -0.587 LI to MI -0.757 -0.707 -0.611 -0.647 Bimanual coordination Box opening task Total movement time -0.376 -0.276 -0.237 -0.208 Goal synchronization -0.365 -0.395 -0.372 -0.367 Kinarm BoB Bar tilt standard deviation -0.404 -0.332 -0.376 -0.344 Hand speed difference -0.665 -0.544 p -0.522 p -0.538 Hand path length bias -0.161 -0.221 -0.263 -0.211 AHA: Assisting Hand Assessment; BoB: Ball-on-Bar task; CHEQ: Children's Hand-Use Experience Questionnaire; LI to MI: From the less-impaired to the more-impaired hand; MI to LI: From the more-impaired to the less-impaired hand; p: Pearson correlation coefficient; TPT: Tyneside Pegboard Test. Strength of correlation coefficients: light green = low, green = moderate, dark green = high. Significance: bold = significant correlation with adjusted FDR-p≤0.05, bold italic = significant correlation with FDR-adjusted p≤0.01. 4. DISCUSSION In this study, we comprehensively evaluated somatosensory upper limb function and distinct components of bimanual function to obtain an improved understanding of their relation in children with uCP. We demonstrated low to moderate correlations, especially between tactile perception and proprioception with measures of functional hand use, bimanual dexterity and bimanual coordination. Regression analyses further indicated that two-point discrimination and robotic measurement of distal and proximal position sense explained part of the variability in bimanual function. Our findings underline the importance of comprehensive assessments of somatosensory function to further understand bimanual impairments. First, our findings regarding tactile function closely align with earlier work by Poitras et al. (2021), who demonstrated that reduced higher-order tactile perception, particularly stereognosis and two-point discrimination, is consistently related to poorer bimanual performance in activities of daily living in children with (unilateral) CP, whereas tactile registration showed a generally weaker relation [ 15 ]. Similarly, in the present study, tactile perception was related to all measures of functional hand use and bimanual dexterity, while tactile registration was only weakly associated with perceived time and hinder during daily activities and showed no relationship with bimanual dexterity and bimanual coordination. Interestingly, the regression analyses further emphasized the important role of tactile perception, with two-point discrimination emerging as the strongest factor explaining a substantial proportion of variance in functional hand use and bimanual dexterity. The importance of tactile perception might be explained by the notion that higher-order tactile perception is essential in identifying object’s characteristics, such as texture, shape and size, which is crucial to adjust grip strength and precise object manipulation [ 41 ]. In contrast, tactile registration reflects only the detection of a tactile stimulus and may be more easily compensated through visual feedback. Together, these findings add to the growing body of evidence that impairments in tactile perception, rather than tactile detection alone, limit the efficiency of bimanual actions even when overall task completion remains possible [ 15 , 16 ]. Second, by using fine-grained robotic assessments of both distal and proximal position sense, our results showed several significant associations with bimanual function. Furthermore, proprioception was retained as one of the most important predictors in the different multiple regression models, underscoring its unique importance for bimanual function. Although no statistical comparison was performed, the observed associations were generally weaker than those found for tactile perception and appeared to be more task-dependent, which aligns with earlier research [ 15 , 16 ]. More specifically, Poitras et al. (2021) suggested that robotics may improve the reliability of proprioceptive assessments, that often lack validity and protocol standardization in clinical practice, thereby enhancing insight into proprioceptive impairments and their impact on motor function [ 15 ]. Nevertheless, also using robotic proprioceptive assessments, the relation with bimanual function remains low [ 11 , 32 , 42 ]. As activities of daily living require movements of different upper limb joints simultaneously, methodological aspects of the current proprioceptive assessments might explain the weaker relationship found. Nevertheless, distal and proximal position sense contributed uniquely to several bimanual outcomes in the regression models. Distal position sense explained part of the variance in bimanual dexterity and goal synchronization during the box opening task, whereas proximal position sense explained additional variance in functional hand use. The TPT assessment and box opening task require fine motor function of the more-impaired hand to be able to place the peg accurately in the hole and specifically press a button inside the box [ 23 , 24 , 34 ]. Therefore, reduced distal position sense might cause stronger reliance on visual function, resulting in a longer task execution. While these bimanual assessments are performed relatively close to the body, assessments of functional hand use may additionally require reaching movements to handle objects positioned further away, potentially explaining the greater importance of proximal position sense. Taken together, these results suggest that proprioceptive impairments subtly constrain the precision and pace of bimanual function, being most related to tasks that demand continuous sensorimotor integration and movement corrections. Lastly, we investigated associations between distinct components of bimanual function, namely functional hand use, bimanual dexterity and bimanual coordination. Functional hand use showed moderate to strong correlations with bimanual dexterity, consistent with earlier literature [ 23 ]. These associations may be attributed to the fact that both functional hand use and bimanual dexterity assessments rely extensively on the grasping ability of the more-impaired hand [ 23 , 24 , 35 ]. In contrast, associations between functional hand use and bimanual coordination varied from negligible to moderate across parameters. This finding confirms that bimanual coordination is a multifaceted process that additionally reflects movement strategies and movement quality, components that are often not evaluated using clinical assessments of functional hand use [ 22 ]. Nevertheless, parameters reflecting temporal interlimb differences, such as hand speed difference, goal synchronization or bar tilt standard deviation, showed most association with functional hand use. This finding suggests that temporal coupling of both hands is particularly relevant for daily activities. In contrast, spatial alignment (hand path length bias) or overall task performance (total movement time) seem not to be related to functional hand use, possibly because these aspects can be more easily compensated for without substantially affecting task performance. Interestingly, this pattern may also explain why somatosensory function appears to be particularly relevant for tasks requiring rapid and spontaneous movements. In such tasks, reliance on compensatory mechanisms, using the less-impaired limb, visual function or cognition, is limited. Instead, more automated and unconscious sensorimotor processes predominate. As accurate integration of somatosensory input is necessary for fine-grained sensorimotor control, reduced somatosensory function can directly constrain the effectiveness and speed of hand use [ 1 , 2 ]. Nevertheless, some limitations of this study should be recognized. First, technical difficulties with the robotic and instrumented assessment resulted in some missing data and therefore, not all participants could be included in the analyses. However, as the pattern of missing data was random, the analyses remained unbiased [ 43 ]. Second, future studies with larger sample sizes could focus on combining several explanatory factors, such as cognition, attention, but also the presence of mirror movements and visual function, to further improve our clinical insight in the variability of bimanual function. It should also be recognized that bimanual function, unimanual motor capacity and somatosensory function likely interact in complex and reciprocal ways. Future longitudinal studies are warranted to better characterize these relationships and clarify their directionality. Lastly, we performed a comprehensive somatosensory test battery, including assessments of tactile registration, tactile perception and proprioception. Nevertheless, the selected tactile assessments did not evaluate the temporal and modality-specific dimensions of tactile perception and no somatosensory evaluation of the less impaired upper limb was included, although previous research indicated that somatosensory impairments can be present in both upper limbs [ 11 , 13 , 17 ]. Moreover, methodological differences in the proprioceptive assessments used, such as the plane of movement and number of joints simultaneously assessed, might impact the correlations found in this study. 5. CONCLUSIONS When performing bimanual tasks, somatosensory information is important to synchronize the movements of both hands and ensure successful task performance. Although tactile and proprioceptive impairments are common in children with uCP, the relation with distinct aspects of bimanual function has not fully been examined. This study demonstrated that higher-order tactile perception and robotic assessment of proprioception are related to bimanual function, with the strongest associations for functional hand use and bimanual dexterity. In contrast, relationships with bimanual coordination were more parameter-specific, potentially reflecting differences in task demands, compensatory strategies and the potential role of other factors such as cognition and visual function. Together, these findings highlight that distinct aspects of bimanual function rely on different sensorimotor processes and underscore the importance of comprehensively assessing tactile perception and proprioception in clinical practice. Further research should examine whether targeting somatosensory function may offer opportunities to optimize bimanual function, particularly for tasks requiring precise object manipulation and dexterous hand use. Abbreviations CP: Cerebral palsy uCP: Unilateral cerebral palsy AHA: Assisting Hand Assessment CHEQ: Children's Hand-Use Experience Questionnaire TPT: Tyneside Pegboard Test TPT MI-LI : Tyneside Pegboard Test from the more impaired to the less impaired hand TPT LI-MI : Tyneside Pegboard Test from the less impaired to the more impaired hand BoB: Ball-on-Bar Declarations ACKNOWLEDGEMENTS We would like to express our appreciation to all children and families for their participation in this study. We additionally thank Dr. Monica Crotti and Dr. Lisa Decraene for their efforts in the recruitment and assessment of participants. FUNDING This work was supported by the Flemish Research Foundation (FWO-Vlaanderen) under an FWO project (G0C4919N) and an FWO research fellowship to LK (11PP224N). DECLARATIONS OF INTEREST The authors report there are no competing interests to declare. DATA AVAILABILITY Detailed research data related to this manuscript are available upon reasonable request to the corresponding author. The data are not publicly available due to participant privacy restrictions. Declarations of interest: None References Machado S, Cunha M, Velasques B, Minc D, Teixeira S, Domingues CA et al (2010) Sensorimotor integration: Basic concepts, abnormalities related to movement disorders and sensorimotor training-induced cortical reorganization. Rev Neurol 51(7):427–436 Edwards LL, King EM, Buetefisch CM, Borich MR (2019) Putting the sensory into sensorimotor control: The role of sensorimotor integration in goal-directed hand movements after stroke. Front Integr Neurosci 13:16. https://doi.org/10.3389/fnint.2019.00016 Delhaye BP, Long KH, Bensmaia SJ (2018) Neural Basis of Touch and Proprioception in Primate Cortex. 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Cengage Learning EMEA, United Kingdom Saal HP, Birznieks I, Johansson RS (2025) Fingertip viscoelasticity enables human tactile neurons to encode loading history alongside current force. eLife 12:RP89616. https://doi.org/10.7554/elife.89616 Kuczynski AM, Dukelow SP, Semrau JA, Kirton A (2016) Robotic quantification of position sense in children with perinatal stroke. Neurorehabil Neural Repair 30(8):762–772. https://doi.org/10.1177/1545968315624781 Kang H (2013) The prevention and handling of the missing data. Kor J Anesthesiol 64:402–406. https://doi.org/10.4097/kjae.2013.64.5.402 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9201856","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":610781731,"identity":"fc5be557-8eca-497b-82ce-81fbafc2ecce","order_by":0,"name":"Lize Kleeren","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIie3QsWrDMBCA4QsCZzmq9YyK8woyhhBooK9iE7AXDx27JZ2yhM5+jL5BDQJ10QN4yNBg8CwolECXqkmHDpXTsYP+QSDExx0CCIX+YVfs62wX55tt4fr7ofWS6EzodJk0LeBlAj8Iwz+R6fTwCoYSLpTul0Yhpzrt72CfjCy2ktBRFj+WVVZ3CuOmzrIGhmyEaAJLxZPBuaitQtmVpUBQxcZLJtujI+tnw9/FwpHbrqw+HFn7CXM/0FEuESMBbjFJK80cyf2LRYxyQ2ljonm8MxWS6ZVAOaS+KZy/HKzVyxnfsYGO+ibh2+LhDe/3M9+UU7/sIEdBKBQKhS70CT0KTw1+tQvTAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4649-4662","institution":"KU Leuven, Hasselt University","correspondingAuthor":true,"prefix":"","firstName":"Lize","middleName":"","lastName":"Kleeren","suffix":""},{"id":610781732,"identity":"2a7be87c-98e6-483f-9b4f-4259e12c5ea2","order_by":1,"name":"Lisa Mailleux","email":"","orcid":"https://orcid.org/0000-0002-9955-098X","institution":"KU Leuven","correspondingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"","lastName":"Mailleux","suffix":""},{"id":610781733,"identity":"a8bdd9a9-b7fb-454e-b9e0-b908a6f73629","order_by":2,"name":"Anja Van Campenhout","email":"","orcid":"https://orcid.org/0000-0002-8158-5535","institution":"University Hospitals Leuven, KU Leuven","correspondingAuthor":false,"prefix":"","firstName":"Anja","middleName":"Van","lastName":"Campenhout","suffix":""},{"id":610781734,"identity":"014ba6e8-44bb-464e-8fd4-0a9120508d31","order_by":3,"name":"Olivier Lambercy","email":"","orcid":"https://orcid.org/0000-0002-0760-7054","institution":"ETH Zurich, Signapore-ETH Centre","correspondingAuthor":false,"prefix":"","firstName":"Olivier","middleName":"","lastName":"Lambercy","suffix":""},{"id":610781735,"identity":"898968d2-d658-4a5b-9a98-3e0c67a1d051","order_by":4,"name":"Katrijn Klingels","email":"","orcid":"https://orcid.org/0000-0001-5853-9680","institution":"Hasselt University, KU Leuven","correspondingAuthor":false,"prefix":"","firstName":"Katrijn","middleName":"","lastName":"Klingels","suffix":""},{"id":610781736,"identity":"65115264-a355-40a3-9685-18caae4bfa5e","order_by":5,"name":"Hilde Feys","email":"","orcid":"https://orcid.org/0009-0002-3858-3080","institution":"KU Leuven","correspondingAuthor":false,"prefix":"","firstName":"Hilde","middleName":"","lastName":"Feys","suffix":""}],"badges":[],"createdAt":"2026-03-23 14:35:15","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9201856/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9201856/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105564700,"identity":"726e2dfd-eb54-46d3-ae2a-d17961e21388","added_by":"auto","created_at":"2026-03-27 12:50:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1868664,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9201856/v1/b0072ab2-3c2e-45b0-a308-fbb82267c14d.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDoes somatosensory function relate to bimanual function in children with unilateral cerebral palsy?\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eGoal-directed movements depend on the accurate integration of somatosensory input, which provides the feedback necessary to plan, guide and adjust motor actions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Integration of tactile and proprioceptive information relies on distributed neural networks [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Early brain lesions, such as those occurring in children with cerebral palsy (CP), can disrupt these networks, leading to somatosensory impairments and altered sensorimotor processing [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Unilateral cerebral palsy (uCP) is the most prevalent subtype, accounting for approximately 40% of the cases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although motor impairments are the most apparent symptom in children with uCP, somatosensory impairments are a well-established comorbidity [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSomatosensation refers to the ability to process and interpret bodily sensory information and encompasses tactile function and proprioception [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Tactile function further includes tactile registration, reflecting the initial awareness of a tactile stimulus and tactile perception, which additionally involves interpretation of the stimulus [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Proprioception, in turn, refers to the ability to accurately perceive limb positions and movements [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous studies have shown that somatosensory impairments across all modalities are common in children with uCP, with reported prevalence rates of up to 90% [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSomatosensory impairments may further compromise the execution of complex motor actions, particularly bimanual tasks requiring coordinated use of both hands. During the performance of bimanual activities, continuous integration of tactile and proprioceptive information is essential to synchronize the movements of both hands and ensure successful task performance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For example, when opening a container, tactile feedback provides information about surface properties and lid position, needed to regulate grip forces and appropriately position the hands. Proprioceptive input from both hands additionally supports stabilization of the container as the other hand twists or pulls off the lid.\u003c/p\u003e \u003cp\u003eTwo recent systematic reviews indeed reported a moderate to high association between tactile perception and bimanual function in children with CP [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. For tactile registration, however, evidence was limited with only five studies investigating this relation, of which three reported no to low associations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Information regarding proprioception is also scarce, with only a few studies reporting conflicting associations ranging from no to moderate association [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. As proprioceptive accuracy has shown to be site- and method-specific, variability in assessment approaches may partially explain these inconsistencies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Moreover, quantifying proprioception remains challenging due to the limited precision of current clinical assessments [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Robot-assisted technological assessments may overcome these limitations and provide deeper insight into the relation between proprioception and bimanual function.\u003c/p\u003e \u003cp\u003eMoreover, bimanual function is often evaluated using self-reported questionnaires or functional hand use measures, such as the Assisting Hand Assessment (AHA). While these tools are clinically relevant and widely used, they may not capture the precise temporal and spatial coordination between both hands [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In contrast, technological assessments can provide detailed insight into complex bimanual motor tasks, including bimanual dexterity or the ability to perform fast and accurate movements and bimanual coordination or the ability to synchronize the upper limbs for a common goal [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Innovative tools such as three-dimensional motion analysis and robotics have been proposed to assess these aspects [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Nevertheless, to the best of our knowledge, such fine-grained bimanual assessments have not yet been used to further delineate their potential relation with somatosensation in children with uCP.\u003c/p\u003e \u003cp\u003eTherefore, the main aims of this study were to: (1) map the relation between tactile registration, tactile perception, proprioception and different aspects of bimanual function, using a comprehensive test-battery encompassing functional hand use, bimanual dexterity and bimanual coordination; and (2) explore the extent to which somatosensory function explains variability across these different aspects of bimanual function. We additionally examined the association between measures of functional hand use and instrumented measures of bimanual dexterity and bimanual coordination to provide insight into the relationship between the different aspects of bimanual function. We hypothesized to find low to moderate correlations between tactile perception and proprioception and bimanual function, with stronger correlations expected for functional hand use and bimanual dexterity. We further expected that tactile perception and distal position sense would account for part of the variability in functional hand use, bimanual dexterity and bimanual coordination as measured with the box opening task, while variability in bimanual coordination measured with the Kinarm exoskeleton would be more determined by proximal position sense.\u003c/p\u003e"},{"header":"2. MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Participants\u003c/h2\u003e\n \u003cp\u003eChildren with spastic uCP were recruited through the Cerebral Palsy Reference Center at the University Hospitals Leuven (Belgium). Eligible participants were between 7 and 15 years old, able to understand the assessment instructions and could actively grasp and hold an object with the more-impaired hand (House Functional Classification System\u0026thinsp;\u0026ge;\u0026thinsp;4) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Children were excluded if they had received upper limb botulinum neurotoxin-A injection within the previous six months or had undergone upper limb surgery within the two previous years.\u003c/p\u003e\n \u003cp\u003eEthical approval was granted by the Ethics Committee Research UZ/KU Leuven (S62906 and S67467). Written informed consent was obtained from the parents before participation. Children aged 12 years or older provided additional assent to participate.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Assessments\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1. Somatosensory function\u003c/h2\u003e\n \u003cp\u003eSomatosensory assessments were performed for the more-impaired upper limb only and comprised clinical measures of tactile registration and tactile perception as well as clinical and robotic measures of proprioception. Further details regarding the somatosensory assessments can be found elsewhere [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTactile registration\u003c/strong\u003e was assessed on the ventral surface of the index fingertip using the 20-item \u003cem\u003eSemmes-Weinstein monofilaments\u003c/em\u003e (Jamar\u0026reg; Monofilaments, Bolingbrook, IL) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The assessment began with the filament representing the upper boundary of intact tactile registration (0.07 grams). Next, the difficulty was adapted based on the participant\u0026rsquo;s response. The outcome corresponded to the thinnest filament that was correctly detected across three consecutive touches and was categorized as \u0026ldquo;intact\u0026rdquo; (0.008\u0026ndash;0.07 grams), \u0026ldquo;impaired\u0026rdquo; (0.16\u0026ndash;300 grams) and \u0026ldquo;absent\u0026rdquo; (if touches with the largest monofilament could not be perceived (\u0026gt;\u0026thinsp;300 grams)).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTactile perception\u003c/strong\u003e comprised stereognosis and two-point discrimination [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. During the assessment of \u003cem\u003estereognosis\u003c/em\u003e, participants were asked to identify six out of 12 familiar objects, including three paired objects of similar size and shape (i.e., pen/pencil, coin/button, paperclip/safety pin) and three distinct items (e.g., marble, spoon, comb, ball, clothespin, key). The total number of correctly identified objects was recorded and further classified as \u0026ldquo;intact\u0026rdquo; (6 objects identified), \u0026ldquo;impaired\u0026rdquo; (4\u0026ndash;5 objects) or \u0026ldquo;absent\u0026rdquo; (\u0026le;\u0026thinsp;3 objects). \u003cem\u003eTwo-point discrimination\u003c/em\u003e was assessed on the ventral side of the index fingertip using an aesthesiometer (Lafayette Instrument, IN). Testing began at four millimeters and was adjusted according to the child\u0026rsquo;s performance. The minimal distance recognized as two separate points across five consecutive trials was determined and classified as \u0026ldquo;intact\u0026rdquo; (2\u0026ndash;4 mm), \u0026ldquo;impaired\u0026rdquo; (5\u0026ndash;10 mm) or \u0026ldquo;absent\u0026rdquo; (\u0026gt;\u0026thinsp;10 mm).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProprioception\u003c/strong\u003e was assessed \u003cem\u003eclinically\u003c/em\u003e by testing \u003cem\u003emovement sense\u003c/em\u003e of the index finger [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Participants were asked to indicate when they perceived small-amplitude movements; if these were not detected, larger movements were performed. Movement sense was classified as \u0026ldquo;intact\u0026rdquo; when three small-amplitude movements were correctly perceived, \u0026ldquo;impaired\u0026rdquo; when only larger movements were detected and \u0026ldquo;absent\u0026rdquo; when no movements were perceived.\u003c/p\u003e\n \u003cp\u003eNext, previously validated robot-assisted assessments were used to further quantify proprioception. Participants performed a contralateral position matching task on the Kinarm exoskeleton robot (BKIN Technologies Ltd, Kingston, Canada) to evaluate position sense of the shoulder and elbow joints, which will be referred to as \u003cem\u003eproximal position sense\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this task, the robot passively moves the more-impaired limb to one of four targets positioned in a 12-cm square. The participant then actively mirror matches this position as precisely as possible with the less-impaired upper limb. Two parameters were calculated by the Kinarm software, namely the absolute error (i.e., mean of the absolute distance between the actual and matched position in the X and Y directions) and variability (i.e., root-sum-square of the standard deviations of the matched position in the X and Y directions). The ETH MIKE (Motor Impairment and Kinesthetic Evaluation) end-effector (Rehabilitation Engineering Laboratory, ETH Zurich, Zurich, Switzerland) measured position sense of the metacarpophalangeal joint or \u003cem\u003edistal position sense\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. During the passive position sense task, the index finger of the participant is moved passively from a 0\u0026deg;-flexion position to one of 11 predefined positions, spaced every 2\u0026deg; between 10\u0026deg; and 30\u0026deg; of metacarpophalangeal flexion. Participants then indicate the perceived finger position on a tablet positioned above their hand. This results again in two task parameters representing the absolute error (i.e., mean of the absolute difference between the actual and indicated position of the index finger) and variability (i.e., standard deviation of the absolute error across all trials). Further details regarding the robotic assessments can be found elsewhere [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2. Bimanual function\u003c/h2\u003e\n \u003cp\u003eDifferent aspects of bimanual function were evaluated using both clinical measures of functional hand use and instrumented assessments of bimanual dexterity and coordination. Further details regarding the instrumented bimanual assessments can be found elsewhere [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional hand use\u003c/strong\u003e was evaluated using the fifth version of the AHA and the Children\u0026rsquo;s Hand-Use Experience Questionnaire (CHEQ 2.0). The AHA measures bimanual performance, which is defined as the spontaneous use of the more-impaired hand during bimanual tasks. Participants played a semi-structured board game that was video recorded [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Afterwards, 20 items related to upper limb function were scored on a 4-point scale. The CHEQ captures the subjective experience of the child\u0026rsquo;s hand use during 27 bimanual daily life activities (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cheq.se\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The questionnaire was completed by the parents of the participants. It includes three subscales, that are all scored on a 4-point scale: (1) grasp effectiveness of the more-impaired hand (CHEQ-grip), (2) time required to complete the activity (CHEQ-time) and (3) the level of hindrance experienced by the more-impaired hand during task performance (CHEQ-feeling). For both assessments, raw scores are converted to a 0-100 logit-based scale, with higher scores indicating better performance.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual dexterity\u003c/strong\u003e was assessed using the Tyneside Pegboard Test (TPT; Newcastle University, Newcastle upon Tyne, UK) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Participants were asked to transfer nine pegs as fast as possible from one board to an adjacent one, by passing it through an opening in a Perspex screen that was positioned between both boards. Completion times were recorded in two directions, namely from the more-impaired to the less-impaired hand (TPT\u003csub\u003eMI\u0026minus;LI\u003c/sub\u003e) and from the less-impaired to the more-impaired hand (TPT\u003csub\u003eLI\u0026minus;MI\u003c/sub\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual coordination\u003c/strong\u003e was measured using the \u003cem\u003ebox opening task\u003c/em\u003e, where participants opened a box with the less-impaired hand and pressed a button inside with the more-impaired hand at a self-selected pace [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Hand movements were recorded at a frequency of 120 Hz using three-dimensional electromagnetic motion sensors from Polhemus G4 (Polhemus, Colchester, Vermont, USA). Two bimanual parameters were calculated using MATLAB R2022a (The Mathworks Inc., Natick, MA, USA), namely the total movement time (i.e., average time needed to complete the task) and goal synchronization (i.e., the temporal coupling between the end of movement of both hands, normalized for total movement time). For both parameters, higher scores indicate poorer bimanual coordination.\u003c/p\u003e\n \u003cp\u003eBimanual coordination was additionally assessed using the second level of the \u003cem\u003eBall-on-Bar (BoB) task\u003c/em\u003e on the Kinarm exoskeleton robot [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Here, participants balanced a ball on a virtual bar, while reaching targets appearing on the screen. Three bimanual parameters, calculated by the Kinarm software, were selected based on the study of Decraene et al., namely bar tilt standard deviation (i.e., variability of the bar angle during the task), hand speed difference (i.e., difference between absolute hand speeds normalized by the mean hand speed) and hand path length bias (i.e., difference in hand path length between hands). These parameters have previously shown to be the most discriminative between children with uCP and typically developing children [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Lower scores on these parameters represent better bimanual coordination.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. Statistical analysis\u003c/h2\u003e\n \u003cp\u003eSPSS Statistics version 30.0 (IBM, Armonk, New York, USA) was used for all statistical analyses. Descriptive statistics were used to summarize the demographic information and clinical characteristics of the participants. The number of participants classified as having \u0026ldquo;intact\u0026rdquo;, \u0026ldquo;impaired\u0026rdquo; or \u0026ldquo;absent\u0026rdquo; somatosensory function, based on the clinical assessments, was determined according to the cut-off values described above. For the robotic assessments, z-scores were computed to determine the number of participants with an impairment in proximal and/or distal position sense. Z-scores were calculated using the formula: Z=(x-x̄)/S, where x represents the individual score of the participant and x̄ and S are respectively the mean and standard deviation of a control group consisting of 58 typically developing children (mean age 11y9mo (SD 2y9mo); 28 males)). Proximal and distal position sense were then classified as \u0026ldquo;intact\u0026rdquo; when the Z-scores of both parameters (i.e., absolute error and variability) were lower than 1.96, \u0026ldquo;impaired\u0026rdquo; when the Z-score of one of the two parameters was higher than 1.96 and \u0026ldquo;absent\u0026rdquo; when both Z-scores were higher than 1.96.\u003c/p\u003e\n \u003cp\u003eFirst, data normality was evaluated using Shapiro-Wilk tests. As the somatosensory data were not normally distributed, Spearman\u0026rsquo;s rank correlations (r\u003csub\u003es\u003c/sub\u003e) were performed to map the relation between tactile registration, tactile perception, proprioception and bimanual function. A false discovery rate (adjusted p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05) for multiple testing correction was applied [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Correlation coefficients were interpreted as no or negligible (\u0026lt;\u0026thinsp;0.30), low (0.30\u0026ndash;0.49), moderate (0.50\u0026ndash;0.69), high (0.70\u0026ndash;0.89) or very high (\u0026ge;\u0026thinsp;0.90) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Secondly, to explore the extent to which measures of somatosensory function explain variability across measures of bimanual function, we performed multiple regression models with backward elimination. Multiple regressions models were made for the AHA and the feeling subscale of the CHEQ. The latter was selected as the level of hindrance experienced during bimanual tasks was expected to be most clinically relevant to children with uCP. For bimanual dexterity and bimanual coordination, parameters were selected based on the results of the correlation analyses, excluding the parameters with no significant correlation (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) with any of the somatosensory assessments. Furthermore, we selected the parameters that showed to be the most discriminative between typically developing children and children with uCP in previous research, resulting in the following selection: the less-impaired to the more-impaired hand condition for the TPT, goal synchronization for the box opening task and hand path length bias for the BoB task of the Kinarm exoskeleton [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. For the independent variables, a selection was also made based on clinical reasoning, as approximately one independent variable should be included per 10 participants [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. More specifically, we selected at least one measure of each somatosensory modality, with the least interference of motor impairments expected and mostly reflecting the magnitude of somatosensory deficits rather than the consistency in performance across repetitions. This resulted in the following selection: Semmes-Weinstein monofilaments, two-point discrimination, movement sense and the absolute error of distal and proximal position sense. Multicollinearity between the independent variables was investigated using the variance inflation factor, with a value above 10 indicating multicollinearity. Outlier detection was based on the scatterplots of the standardized residuals, with values of more than 3.3 or less than \u0026minus;\u0026thinsp;3.3 being considered as outliers [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In the regression models for the parameters of bimanual coordination, some outliers were identified. Therefore, analyses were repeated removing one extreme outlier for the goal synchronization of the box opening task model and two extreme outliers for hand path length bias of the Kinarm BoB task model. For all the multiple regression analyses, the variance inflation factor ranged from 1.00 to 2.16, indicating low multicollinearity between the independent variables. Lastly, to study the relation between measures of functional hand use and instrumented measures of bimanual dexterity and coordination, Pearson (r) or Spearman\u0026rsquo;s rank (r\u003csub\u003es\u003c/sub\u003e) correlations were performed, depending on the normality of the data. A false discovery rate (adjusted p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05) was again applied [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and correlation coefficients were interpreted as no or negligible (\u0026lt;\u0026thinsp;0.30), low (0.30\u0026ndash;0.49), moderate (0.50\u0026ndash;0.69), high (0.70\u0026ndash;0.89) or very high (\u0026ge;\u0026thinsp;0.90) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1 Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 61 children with uCP participated in this study. An overview of the demographic information and clinical characteristics is presented in Table 1. Technical issues with the robotic and instrumented assessments caused some missing data; distal and proximal position sense were missing in five participants, the TPT in 12 participants, the box opening task in 13 and the BoB task on the Kinarm exoskeleton in four participants.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"641\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 641px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Demographic information and clinical characteristics of the participants.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003euCP (N=61), N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean age (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e11y 11mo (3y 0mo)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e35 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e26 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSide of cerebral palsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eRight-sided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e32 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eLeft-sided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e29 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMACS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e28 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e24 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e9 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTactile registration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSemmes-Weinstein monofilaments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIntact \u003cem\u003e(0.008-0.07 grams)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e33 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eImpaired \u003cem\u003e(0.16-300 grams)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e25 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eAbsent \u003cem\u003e(\u0026gt;300 grams)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e3 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTactile perception\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eStereognosis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIntact \u003cem\u003e(6/6 objects identified)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e18 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eImpaired \u003cem\u003e(4-5/6 objects identified)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e28 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eAbsent \u003cem\u003e(\u0026le;3/6 objects identified)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e20 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTwo-point discrimination\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIntact \u003cem\u003e(2-4 millimeters)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e34 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eImpaired \u003cem\u003e(5-10 millimeters)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e18 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eAbsent \u003cem\u003e(\u0026gt;10 millimeters)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e9 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProprioception\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMovement sense\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIntact \u003cem\u003e(3/3 small movements detected)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e45 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eImpaired \u003cem\u003e(1/3 larger movements detected)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e12 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eAbsent \u003cem\u003e(no movement detected)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e4 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDistal position sense\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIntact \u003cem\u003e(both Z-scores \u0026lt;1.96)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e21 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eImpaired \u003cem\u003e(only one Z-score \u0026gt;1.96)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e17 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eAbsent \u003cem\u003e(both Z-scores \u0026gt;1.96)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e18 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eProximal position sense\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eIntact \u003cem\u003e(both Z-scores \u0026lt;1.96)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e23 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eImpaired \u003cem\u003e(only one Z-score \u0026gt;1.96)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e7 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eAbsent \u003cem\u003e(both Z-scores \u0026gt;1.96)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e26 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 641px;\"\u003e\n \u003cp\u003eMACS: Manual Ability Classification System; mo: months; SD: standard deviation; y: years.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Relation between somatosensory and bimanual function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 shows the correlation coefficients between measures of tactile registration, tactile perception, proprioception and functional hand use, bimanual dexterity and bimanual coordination. Overall, several low to moderate correlations were found between somatosensory function and bimanual function, particularly for tactile perception and proprioception.\u003c/p\u003e\n\u003cp\u003eChildren with worse \u003cstrong\u003etactile registration\u003c/strong\u003e needed more time and were more hindered by their more-impaired hand when performing bimanual daily live activities (rₛ=-0.320-(-0.408), \u003cem\u003ep\u003c/em\u003e\u0026le;0.032), but no significant relationship was found with bimanual dexterity or coordination. For \u003cstrong\u003etactile perception\u003c/strong\u003e, worse stereognosis and two-point discrimination was lowly to moderately related to worse functional hand use (\u003cem\u003er\u003c/em\u003eₛ=-0.348-(-0.626), \u003cem\u003ep\u003c/em\u003e\u0026le;0.023), slower performance of dexterous movements\u0026nbsp;(\u003cem\u003er\u003c/em\u003eₛ=-0.478-(-0.574), \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001)\u0026nbsp;and worse bimanual coordination\u0026nbsp;(|\u003cem\u003er\u003c/em\u003eₛ|=0.357-0.501, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.022). Lastly, poorer \u003cstrong\u003eproprioceptive\u003c/strong\u003e accuracy was generally lowly related to reduced functional hand use (\u003cem\u003er\u003c/em\u003eₛ=-0.236-(-0.493), \u003cem\u003ep\u003c/em\u003e\u0026lt;0.113), bimanual dexterity (\u003cem\u003er\u003c/em\u003eₛ=0.279-0.509, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.095) and\u0026nbsp;with some parameters of bimanual coordination. Most notably, larger hand speed differences during the Kinarm BoB task related to worse movement sense (\u003cem\u003er\u003c/em\u003eₛ=-0.315, \u003cem\u003ep\u003c/em\u003e=0.036), distal (\u003cem\u003er\u003c/em\u003eₛ=0.304-0.363, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.048)\u0026nbsp;and proximal position sense (\u003cem\u003er\u003c/em\u003eₛ=0.359-0.454, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.022). Larger distal position sense errors were further related to reduced goal synchronization in the box opening task (\u003cem\u003er\u003c/em\u003eₛ=0.327, \u003cem\u003ep\u003c/em\u003e=0.048), while worse proximal position sense related to larger bar tilt standard deviation and hand path length bias during the Kinarm BOB task (\u003cem\u003er\u003c/em\u003eₛ=0.305-0.395, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.042).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"723\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 723px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2. Spearman\u0026rsquo;s rank correlation coefficients between measures of tactile registration, tactile perception, proprioception and bimanual function\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTactile registration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 152px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTactile perception\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" style=\"width: 283px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProprioception\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSemmes-Weinstein monofilaments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStereognosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTwo-point discrimination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMovement sense\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistal position sense - absolute error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistal position sense - variability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProximal position sense - absolute error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProximal position sense - variability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional hand use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAHA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.293\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.619\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.626\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.335\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.307\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.320\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.428\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.493\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHEQ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGrip\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e-0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.531\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.459\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.290\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.338\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.356\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.302\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTime\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.320\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.460\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.348\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.309\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.308\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.311\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.388\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.350\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFeeling\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.408\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.541\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.442\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.342\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e-0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.415\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.355\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual dexterity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMI to LI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.478\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.479\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.343\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.335\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.351\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.509\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLI to MI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.551\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.574\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.356\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.328\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.345\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.364\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.472\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual coordination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBox opening task\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTotal movement time\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e-0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGoal synchronization\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e-0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.327\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKinarm BoB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBar tilt standard deviation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.357\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.305\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.395\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHand speed difference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.501\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.499\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.315\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.363\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.304\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.359\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.454\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eHand path length bias\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e-0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e-0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.362\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 723px;\"\u003e\n \u003cp\u003e\u003cem\u003eAHA: Assisting Hand Assessment; BoB: Ball-on-Bar task; CHEQ: Children\u0026apos;s Hand-Use Experience Questionnaire; LI to MI: From the less-impaired to the more-impaired hand; MI to LI: From the more-impaired to the less-impaired hand; TPT: Tyneside Pegboard Test.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eStrength of correlation coefficients: light green = low, green = moderate, dark green = high.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSignificance: bold = significant correlation with adjusted FDR-p\u0026le;0.05, bold italic = significant correlation with FDR-adjusted p\u0026le;0.01.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Variability in bimanual function explained by somatosensory function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 presents the results of the multiple regression analyses.\u003cstrong\u003e\u0026nbsp;Two-point discrimination\u003c/strong\u003e emerged as the main determinant explaining a substantial proportion of variance in functional hand use and bimanual dexterity (R\u0026sup2;=0.167-0.292 \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). \u003cstrong\u003eProximal position sense\u003c/strong\u003e additionally determined functional hand use, as assessed with the AHA and CHEQ-feeling (R\u0026sup2;=0.050-0.113, \u003cem\u003ep\u003c/em\u003e\u0026le;0.046), while \u003cstrong\u003edistal position sense\u003c/strong\u003e further explained bimanual dexterity (TPT\u003csub\u003eLI-MI\u003c/sub\u003e,\u003csub\u003e\u0026nbsp;\u003c/sub\u003eR\u0026sup2;=0.084, \u003cem\u003ep\u003c/em\u003e=0.006). \u003cstrong\u003eDistal position sense\u0026nbsp;\u003c/strong\u003ewas also the only\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003esignificant predictor of goal synchronization of the box opening task (R\u0026sup2;=0.115, \u003cem\u003ep\u003c/em\u003e=0.006), while \u003cstrong\u003eproximal position sense\u003c/strong\u003e was identified for hand path length bias of the Kinarm BoB task, however, this model did not reach significance (\u003cstrong\u003eproximal position sense\u003c/strong\u003e: R\u0026sup2;=0.062, \u003cem\u003ep\u003c/em\u003e=0.081).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"721\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 721px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. Overview of the final models of the multiple regressions analysis on distinct components of bimanual function.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted R\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRetained predictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnique R\u0026sup2;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 721px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional hand use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eAHA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eTwo-point discrimination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.292\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cem\u003e-3.132 (-4.400; -1.864)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e-0.555\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eProximal position sense - absolute error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.050\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cem\u003e-102.672 (-203.343; -2.001)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e-0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eCHEQ-feeling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eTwo-point discrimination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.167\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-2.419 (-3.780; -1.058)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e-0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eProximal position sense - absolute error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.113\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e-158.315 (-266.369; -50.262)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e-0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 721px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual dexterity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003eTPT - LI to MI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eTwo-point discrimination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.337\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cem\u003e6.324 (4.140; 8.507)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eDistal position sense - absolute error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.084\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cem\u003e1.078 (0.335; 1.822)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 721px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual coordination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eBox opening task - goal synchronization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eDistal position sense - absolute error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.115\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.004 (0.001; 0.007)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eKinarm BoB task - hand path length bias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eProximal position sense - absolute error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.062\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cem\u003e0.268 (-0.034; 0.571)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 721px;\"\u003e\n \u003cp\u003e\u003cem\u003eAdjusted R\u0026sup2; = Degree of variance of the bimanual function assessment that is explained by the retained predictors; AHA: Assisting Hand Assessment; B: Unstandardized coefficient;\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003cem\u003e: Standardized coefficients; BoB: Ball-on-Bar task; CHEQ: Children\u0026apos;s Hand-Use Experience Questionnaire; CI: Confidence interval; LI to MI: From the less-impaired to the more-impaired hand; TPT: Tyneside Pegboard Test; Unique R\u0026sup2;: Degree of variance of the bimanual function assessment that is uniquely explained by one specific retained predictor.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Relation between functional hand use, bimanual dexterity and coordination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation coefficients between measures of functional hand use, bimanual dexterity and coordination can be found in Table 4. Firstly, the \u003cstrong\u003eTPT\u003c/strong\u003e correlated moderately to highly with both measures of functional hand use (AHA: r\u003csub\u003es\u003c/sub\u003e=-0.682-(-0.757),\u003cem\u003e\u0026nbsp;p\u003c/em\u003e\u0026lt;0.001; CHEQ: r\u003csub\u003es\u003c/sub\u003e=-0.577-(-0.707), \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), showing that worse bimanual dexterity was related to worse functional hand use. Secondly, the \u003cstrong\u003ebox opening task\u003c/strong\u003e showed that worse goal synchronization and longer movement time were lowly related to worse functional hand use (r\u003csub\u003es\u003c/sub\u003e=-0.365-(-0.395), \u003cem\u003ep\u003c/em\u003e\u0026le;0.016). Lastly, for the \u003cstrong\u003eBoB task of the Kinarm robot\u003c/strong\u003e, higher bar tilt standard deviation and hand speed difference were associated with worse functional hand use (r/r\u003csub\u003es\u003c/sub\u003e=-0.332-(-0.665), \u003cem\u003ep\u003c/em\u003e\u0026le;0.016), while hand path length bias did not show any significant correlation (r\u003csub\u003es\u003c/sub\u003e=-0.161-(-0.263), \u003cem\u003ep\u003c/em\u003e\u0026gt;0.061).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4. Pearson and spearman\u0026rsquo;s rank correlation coefficients between measures of functional hand use and measures of bimanual dexterity and coordination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 275px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional hand use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAHA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHEQ-grip\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHEQ-time\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHEQ-feeling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual dexterity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMI to LI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.682\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.617\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.577\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.587\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLI to MI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.757\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.707\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.611\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.647\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBimanual coordination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBox opening task\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal movement time\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.376\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGoal synchronization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.365\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.395\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.372\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.367\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKinarm BoB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBar tilt standard deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.404\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.332\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.376\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.344\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHand speed difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.665\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.544\u003csup\u003e\u0026nbsp;p\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.522\u003csup\u003ep\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e-0.538\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHand path length bias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e-0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cem\u003eAHA: Assisting Hand Assessment; BoB: Ball-on-Bar task; CHEQ: Children\u0026apos;s Hand-Use Experience Questionnaire; LI to MI: From the less-impaired to the more-impaired hand; MI to LI: From the more-impaired to the less-impaired hand; p: Pearson correlation coefficient; TPT: Tyneside Pegboard Test.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eStrength of correlation coefficients: light green = low, green = moderate, dark green = high.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSignificance: bold = significant correlation with adjusted FDR-p\u0026le;0.05, bold italic = significant correlation with FDR-adjusted p\u0026le;0.01.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eIn this study, we comprehensively evaluated somatosensory upper limb function and distinct components of bimanual function to obtain an improved understanding of their relation in children with uCP. We demonstrated low to moderate correlations, especially between tactile perception and proprioception with measures of functional hand use, bimanual dexterity and bimanual coordination. Regression analyses further indicated that two-point discrimination and robotic measurement of distal and proximal position sense explained part of the variability in bimanual function. Our findings underline the importance of comprehensive assessments of somatosensory function to further understand bimanual impairments.\u003c/p\u003e \u003cp\u003eFirst, our findings regarding tactile function closely align with earlier work by Poitras et al. (2021), who demonstrated that reduced higher-order tactile perception, particularly stereognosis and two-point discrimination, is consistently related to poorer bimanual performance in activities of daily living in children with (unilateral) CP, whereas tactile registration showed a generally weaker relation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Similarly, in the present study, tactile perception was related to all measures of functional hand use and bimanual dexterity, while tactile registration was only weakly associated with perceived time and hinder during daily activities and showed no relationship with bimanual dexterity and bimanual coordination. Interestingly, the regression analyses further emphasized the important role of tactile perception, with two-point discrimination emerging as the strongest factor explaining a substantial proportion of variance in functional hand use and bimanual dexterity. The importance of tactile perception might be explained by the notion that higher-order tactile perception is essential in identifying object\u0026rsquo;s characteristics, such as texture, shape and size, which is crucial to adjust grip strength and precise object manipulation [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In contrast, tactile registration reflects only the detection of a tactile stimulus and may be more easily compensated through visual feedback. Together, these findings add to the growing body of evidence that impairments in tactile perception, rather than tactile detection alone, limit the efficiency of bimanual actions even when overall task completion remains possible [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSecond, by using fine-grained robotic assessments of both distal and proximal position sense, our results showed several significant associations with bimanual function. Furthermore, proprioception was retained as one of the most important predictors in the different multiple regression models, underscoring its unique importance for bimanual function. Although no statistical comparison was performed, the observed associations were generally weaker than those found for tactile perception and appeared to be more task-dependent, which aligns with earlier research [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. More specifically, Poitras et al. (2021) suggested that robotics may improve the reliability of proprioceptive assessments, that often lack validity and protocol standardization in clinical practice, thereby enhancing insight into proprioceptive impairments and their impact on motor function [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Nevertheless, also using robotic proprioceptive assessments, the relation with bimanual function remains low [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. As activities of daily living require movements of different upper limb joints simultaneously, methodological aspects of the current proprioceptive assessments might explain the weaker relationship found. Nevertheless, distal and proximal position sense contributed uniquely to several bimanual outcomes in the regression models. Distal position sense explained part of the variance in bimanual dexterity and goal synchronization during the box opening task, whereas proximal position sense explained additional variance in functional hand use. The TPT assessment and box opening task require fine motor function of the more-impaired hand to be able to place the peg accurately in the hole and specifically press a button inside the box [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, reduced distal position sense might cause stronger reliance on visual function, resulting in a longer task execution. While these bimanual assessments are performed relatively close to the body, assessments of functional hand use may additionally require reaching movements to handle objects positioned further away, potentially explaining the greater importance of proximal position sense. Taken together, these results suggest that proprioceptive impairments subtly constrain the precision and pace of bimanual function, being most related to tasks that demand continuous sensorimotor integration and movement corrections.\u003c/p\u003e \u003cp\u003eLastly, we investigated associations between distinct components of bimanual function, namely functional hand use, bimanual dexterity and bimanual coordination. Functional hand use showed moderate to strong correlations with bimanual dexterity, consistent with earlier literature [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These associations may be attributed to the fact that both functional hand use and bimanual dexterity assessments rely extensively on the grasping ability of the more-impaired hand [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In contrast, associations between functional hand use and bimanual coordination varied from negligible to moderate across parameters. This finding confirms that bimanual coordination is a multifaceted process that additionally reflects movement strategies and movement quality, components that are often not evaluated using clinical assessments of functional hand use [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Nevertheless, parameters reflecting temporal interlimb differences, such as hand speed difference, goal synchronization or bar tilt standard deviation, showed most association with functional hand use. This finding suggests that temporal coupling of both hands is particularly relevant for daily activities. In contrast, spatial alignment (hand path length bias) or overall task performance (total movement time) seem not to be related to functional hand use, possibly because these aspects can be more easily compensated for without substantially affecting task performance. Interestingly, this pattern may also explain why somatosensory function appears to be particularly relevant for tasks requiring rapid and spontaneous movements. In such tasks, reliance on compensatory mechanisms, using the less-impaired limb, visual function or cognition, is limited. Instead, more automated and unconscious sensorimotor processes predominate. As accurate integration of somatosensory input is necessary for fine-grained sensorimotor control, reduced somatosensory function can directly constrain the effectiveness and speed of hand use [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNevertheless, some limitations of this study should be recognized. First, technical difficulties with the robotic and instrumented assessment resulted in some missing data and therefore, not all participants could be included in the analyses. However, as the pattern of missing data was random, the analyses remained unbiased [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Second, future studies with larger sample sizes could focus on combining several explanatory factors, such as cognition, attention, but also the presence of mirror movements and visual function, to further improve our clinical insight in the variability of bimanual function. It should also be recognized that bimanual function, unimanual motor capacity and somatosensory function likely interact in complex and reciprocal ways. Future longitudinal studies are warranted to better characterize these relationships and clarify their directionality. Lastly, we performed a comprehensive somatosensory test battery, including assessments of tactile registration, tactile perception and proprioception. Nevertheless, the selected tactile assessments did not evaluate the temporal and modality-specific dimensions of tactile perception and no somatosensory evaluation of the less impaired upper limb was included, although previous research indicated that somatosensory impairments can be present in both upper limbs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Moreover, methodological differences in the proprioceptive assessments used, such as the plane of movement and number of joints simultaneously assessed, might impact the correlations found in this study.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eWhen performing bimanual tasks, somatosensory information is important to synchronize the movements of both hands and ensure successful task performance. Although tactile and proprioceptive impairments are common in children with uCP, the relation with distinct aspects of bimanual function has not fully been examined. This study demonstrated that higher-order tactile perception and robotic assessment of proprioception are related to bimanual function, with the strongest associations for functional hand use and bimanual dexterity. In contrast, relationships with bimanual coordination were more parameter-specific, potentially reflecting differences in task demands, compensatory strategies and the potential role of other factors such as cognition and visual function. Together, these findings highlight that distinct aspects of bimanual function rely on different sensorimotor processes and underscore the importance of comprehensively assessing tactile perception and proprioception in clinical practice. Further research should examine whether targeting somatosensory function may offer opportunities to optimize bimanual function, particularly for tasks requiring precise object manipulation and dexterous hand use.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCP: Cerebral palsy\u003c/p\u003e\n\u003cp\u003euCP: Unilateral cerebral palsy\u003c/p\u003e\n\u003cp\u003eAHA: Assisting Hand Assessment\u003c/p\u003e\n\u003cp\u003eCHEQ: Children\u0026apos;s Hand-Use Experience Questionnaire\u003c/p\u003e\n\u003cp\u003eTPT: Tyneside Pegboard Test\u003c/p\u003e\n\u003cp\u003eTPT\u003csub\u003eMI-LI\u003c/sub\u003e: Tyneside Pegboard Test from the more impaired to the less impaired hand\u003c/p\u003e\n\u003cp\u003eTPT\u003csub\u003eLI-MI\u003c/sub\u003e: Tyneside Pegboard Test from the less impaired to the more impaired hand\u003c/p\u003e\n\u003cp\u003eBoB: Ball-on-Bar\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our appreciation to all children and families for their participation in this study. We additionally thank Dr. Monica Crotti and Dr. Lisa Decraene for their efforts in the recruitment and assessment of participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Flemish Research Foundation (FWO-Vlaanderen) under an FWO project (G0C4919N) and an FWO research fellowship to LK (11PP224N).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDECLARATIONS OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report there are no competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDetailed research data related to this manuscript are available upon reasonable request to the corresponding author. The data are not publicly available due to participant privacy restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations of interest:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMachado S, Cunha M, Velasques B, Minc D, Teixeira S, Domingues CA et al (2010) Sensorimotor integration: Basic concepts, abnormalities related to movement disorders and sensorimotor training-induced cortical reorganization. Rev Neurol 51(7):427\u0026ndash;436\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdwards LL, King EM, Buetefisch CM, Borich MR (2019) Putting the sensory into sensorimotor control: The role of sensorimotor integration in goal-directed hand movements after stroke. 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Kor J Anesthesiol 64:402\u0026ndash;406. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4097/kjae.2013.64.5.402\u003c/span\u003e\u003cspan address=\"10.4097/kjae.2013.64.5.402\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"de929abc-1476-4a7d-b379-e72f9e469462","identifier":"10.13039/501100003130","name":"Fonds Wetenschappelijk Onderzoek","awardNumber":"G0C4919N","order_by":0},{"identity":"bf403e62-7f35-46ac-be5a-f71aeab595f1","identifier":"10.13039/501100003130","name":"Fonds Wetenschappelijk Onderzoek","awardNumber":"11PP224N","order_by":1}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"KU Leuven","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Upper limb, somatosensation, proprioception, bimanual function, unilateral cerebral palsy, children","lastPublishedDoi":"10.21203/rs.3.rs-9201856/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9201856/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGoal-directed bimanual movements rely on the integration of somatosensory information to plan and adjust motor actions. In children with unilateral cerebral palsy (uCP), previous studies have primarily relied on clinical assessments of bimanual function and proprioception, whereas robotic and instrumented assessments may provide more precise and objective measures to further outline this relationship.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo investigate the association between tactile registration, tactile perception, proprioception and bimanual function in children with uCP, using both clinical and instrumented assessments.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this cross-sectional study, sixty-one children with uCP (mean age 11y11mo (SD 3y0mo); 35 males) completed assessments of tactile registration, tactile perception and proprioception. Bimanual function was evaluated through functional hand use (Assisting Hand Assessment; Children\u0026rsquo;s Hand-Use Experience Questionnaire), bimanual dexterity (Tyneside pegboard Test) and bimanual coordination (Ball-on-Bar task on the Kinarm robot; Box opening task). Associations were investigated using correlations (r/r\u003csub\u003es\u003c/sub\u003e) and multiple linear regressions (R\u0026sup2;).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWorse tactile registration was weakly associated with reduced functional hand use (rₛ=-0.320-(-0.408), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.032). Worse tactile perception showed low to moderate associations with reduced functional hand use (\u003cem\u003er\u003c/em\u003eₛ=-0.348-(-0.626), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.023), slower bimanual dexterity (\u003cem\u003er\u003c/em\u003eₛ=-0.478-(-0.574), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and poorer coordination (|\u003cem\u003er\u003c/em\u003eₛ|=0.357\u0026ndash;0.501, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.022). Proprioceptive impairments were generally lowly to moderately related to functional hand use (\u003cem\u003er\u003c/em\u003eₛ=-0.236-(-0.493), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.113) and bimanual dexterity (\u003cem\u003er\u003c/em\u003eₛ=0.279\u0026ndash;0.509, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.095). Regression analyses indicated that two-point discrimination, distal position sense and proximal position sense explained respectively 33\u0026ndash;40% and 58% of the variance in functional hand use (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.050) and of bimanual dexterity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.050). Variability in bimanual coordination was only minimally explained by proprioceptive measures (R\u0026sup2;=4%-9%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024\u0026ndash;0.081).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHigher-order tactile perception and proprioception are particularly relevant for functional hand use and bimanual dexterity in children with uCP, whereas associations with bimanual coordination are more task- and parameter dependent. The results emphasize the importance of integrating somatosensory assessments into the follow-up of children with uCP to further understand bimanual impairments.\u003c/p\u003e","manuscriptTitle":"Does somatosensory function relate to bimanual function in children with unilateral cerebral palsy?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-25 09:02:29","doi":"10.21203/rs.3.rs-9201856/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e87db4d3-64af-4a46-9564-a487ab362c07","owner":[],"postedDate":"March 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":64985960,"name":"Developmental Neuroscience"},{"id":64985961,"name":"Pediatrics"},{"id":64985962,"name":"Physical Medicine \u0026 Rehab"}],"tags":[],"updatedAt":"2026-03-25T09:02:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-25 09:02:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9201856","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9201856","identity":"rs-9201856","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}