Beyond En-Bloc Turning: Head-Pelvis Coordination Variability in 360° turns in people with Parkinson’s

Beyond En-Bloc Turning: Head-Pelvis Coordination Variability in 360° turns in people with Parkinson’s | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Beyond En-Bloc Turning: Head-Pelvis Coordination Variability in 360° turns in people with Parkinson’s Phaedra Leveridge, Yuri Russo, Genevieve Williams, Jiaxi Ye, Zijing Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6456602/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 People with Parkinson’s Disease (PD) and Freezing of Gait (FOG) reportedly turn using an ‘en-bloc’ strategy, where the head and pelvis rotate together, unlike the head-leading movement seen in healthy adults. However, previous research relies on discrete maximum separation angles in 180° walking turns, despite recommendations to use 360° on-the-spot turns to better induce FOG. Current reports in people with Parkinson’s also fail to capture the time-varying coordination of body segments as the turn unfolds. Our study aimed to investigate head-pelvis coordination across strides during 360° on-the-spot turns in people with PD and FOG (PD + FOG), PD without FOG (PD-FOG), and healthy controls (HC). Twelve PD + FOG, 14 PD-FOG (tested ON medication), and 17 HC completed the turns during which head and pelvis angles in the transverse plane were calculated across strides in the first, middle and final sections of the turn. Head-pelvis angular difference did not differ between groups. However, PD + FOG showed increased coordination variability compared to HC (4.93°, p = 0.005) and PD-FOG (3.47°, p = 0.047); an observation that was no longer apparent after adjusting for MDS-UPDRS motor scores (p = 0.249) and MiniBEST (p = 0.051). PD + FOG also took more steps than PD-FOG (3.94, p = 0.008) and HC (6.47, p < 0.001), even after adjusting for covariates (MDS-UPDRS: p = 0.037; MiniBEST: p = 0.003). These findings suggest that people with PD do not necessarily exhibit more en-bloc turning compared to healthy controls. While head-pelvis coordination variability is higher in people with PD + FOG, this does not seem to be linked to FOG pathology per se , but rather balance deficits associated with disease severity. Increased step count seems to be related to FOG, which could be interpreted as a factors that might provoke FOG, but also serve as a compensatory strategy to promote postural stability. Health sciences/Signs and symptoms Health sciences/Diseases/Neurological disorders turning Parkinson’s disease freezing of gait segmental coordination vector coding Figures Figure 1 Figure 2 Figure 3 Introduction Turning, while standing or walking, is an essential component of human locomotion. Approximately one third of steps during daily living incorporate turns 1 . Typically, healthy adults first rotate their head in the direction of the turn, followed by their shoulders and pelvis 2 , 3 . Head-pelvis coordination in turning appears to be altered in people with PD, with a more ‘en-bloc’ (in-line) strategy. Initiation of head rotation is postponed, resulting in a more closely coupled start of head and pelvis rotation in comparison with the top-down coordination in healthy controls 4 . Furthermore, maximum head-pelvis separation appears to be lower in people with PD compared to healthy older adults during 180° walking turns 5 , 6 . Freezing of gait (FOG) is experienced by over 50% of people who have PD 7 . FOG is defined as a “brief, episodic absence, or marked reduction of forward progression of the feet despite the intention to walk” 8 and is often experienced during turning 9 . People with PD and FOG take longer and more steps to turn than those without, with the difference between groups increasing with turning angle 10 . Spildooren and co-workers 5 found that head-pelvis angular difference in the first 65° of a 180° turn was lower in people with FOG compared to people with PD without FOG. Reduced separation between head-pelvis motion is significant because it may reflect a reduced ability to coordinate segmental reorientation during turning. Identifying the most meaningful aspects of head-pelvis coordination to quantify can be challenging. Previous studies have used rotation onset times 6 , 11 – 15 , maximum head-pelvis angular difference 5 , 6 , and angular velocity 16 , 17 . Since the demands on head-pelvis coordination change throughout a turn, different sections may pose unique motor control challenges. Spildooren and co-workers 5 captured angular difference at every 5° of pelvis rotation, providing a view of head-pelvis separation throughout the turn. However, focusing on angular differences limits understanding of how the head and the pelvis move together. For example, it is possible to have a large angular difference yet experience rigid en-bloc motion (i.e. after the initial decoupling the relationship among the body segments does not change). Vector coding is used to quantify relative movement and coupling between segments, describing the relative predominance of motion in one segment or another 18 – 21 . Vector coding could therefore provide an informative measure representing the dynamic relationship between the head and pelvis across the turn. Coordinated movement requires the complex organisation of multiple degrees of freedom to perform actions 22 . Therefore, variability in joint coordination is typically seen in healthy individuals, allowing motor patterns to be stable and repeatable, yet giving flexibility to adapt to task constraints 23 , 24 . In straight-line walking, head-pelvis coordination variability in the transverse plane is lower in people with PD than in healthy controls 25 . Similarly, people with PD have reduced gait adaptability (ability to adjust gait to target/obstacles) 26 , and increased axial rigidity 27 which may hinder an ability to adapt to the dynamic requirements of turning. However, head-pelvis coordination variability has not yet been investigated during turning in PD. The so-called ‘Ziegler protocol’ 28 , and paradigms using 360° standing turns, are increasingly used to elicit FOG in clinical and research settings 29 , 30 . Previous research investigating head-pelvis coordination in people with FOG has focused on walking turns of 180° 5 , 31 . While 360° turning has been shown to provoke FOG, understanding coordination patterns during successful turns helps to contextualise findings. Investigating head-pelvis coordination in 360° turns may provide a clearer understanding of how segmental coupling is impacted in people with PD and FOG, as well as insight into the role of head-pelvis coordination in FOG. Disease severity has been linked with turning behaviour in PD. Specifically, turning step count, velocity and turn duration are associated with disease severity 32 , 33 . It remains unclear whether head-pelvis coordination is related to disease severity. FOG more frequently presents in people with moderate to severe PD, affecting more than 60% of those with a disease duration over 10 years 34 . Previous reports 35 have highlighted that disease severity should be statistically controlled for to isolate the contributions of FOG to behaviour. By controlling for disease severity, we can determine whether observed deficits are inherent to FOG as a symptom or reflect broader motor impairments associated with advanced PD. Using approaches novel to the context of turning in PD (vector coding and continuous analysis), we quantified head-pelvis coupling and coordination variability during 360° turning to explore whether segmental control during turning is a characteristic of people with PD and FOG or associated with disease severity or balance. This study compared head-pelvis coordination in 360° on-the-spot turns in people with PD and FOG (PD + FOG), PD without FOG (PD-FOG), and healthy controls (HC). It was hypothesised that: (i) head-pelvis angular difference would be lower, and the percentage of the stride in-phase would be higher in PD + FOG than HC and PD-FOG; (ii) head-pelvis coordination variability would be lower in PD + FOG than PD-FOG and HC (iii) increased disease severity would exacerbate differences between PD + FOG and PD-FOG. Methods Study Design This study followed an observational cross-sectional design. All participants with PD were tested ON medication – (approximately 60 minutes after their last dose) of dopaminergic medication. The study was approved by the local institutional review board of the University of Exeter (21-12-08-B-02, Department of Public Health & Sport Sciences). Participants Forty-five people with PD were recruited through local Parkinson’s UK branches. Twenty-three self-reported frequently experiencing FOG (PD + FOG), and twenty-two did not experience FOG (PD-FOG). Participants in each group required a diagnosis of idiopathic PD using the UK Brain Bank Criteria 36 . Participants were included in the PD + FOG group if they self-reported FOG according to the first item of the New Freezing of Gait Questionnaire (NFOG-Q) 37 . Twenty-seven older adults (aged 55 years+) were recruited as controls (HC). Participants were required to be able to walk unsupported (> 1 minute), have no cognitive impairment (Montreal Cognitive Assessment (MOCA) Score > 20), have no comorbidities that would affect balance or walking, and be aged 55 + years old. All participants provided written informed consent prior to participating in the study. Procedure After providing informed consent, participants with PD were rated by a trained examiner on the Motor Section (III) of the Movement Disorder Society-Unified PD Rating Scale (MDS-UPDRS) 38 . Mini Balance Evaluation Systems Test (MiniBEST) 39 and the MOCA 40 were administered to all participants. All participants were asked to complete a walking task (shown in Fig. 1) in a clockwise direction, followed by an anti-clockwise direction. They were asked to walk through cones to a yellow and black striped circular target in the capture area. Then, they were instructed to stop on the target and complete a modified Ziegler protocol 28 - where a 360˚ turn was performed in one direction, then a second 360˚ turn was performed in the opposite direction. Participants were asked to stop before and after each turn. Once the turning task had been completed, the participant continued through the cones to the next target and repeated the task. Participants were instructed when to change from travelling in the clockwise direction to anticlockwise, completing around 4–5 targets in each direction. Kinematic data were recorded during the task using a 19-camera motion capture system (Prime 13, Optitrack, USA) with a sampling rate of 100 Hz. Thirty-nine retroreflective markers were placed on each participant’s skin and clothing according to the full-body Plug-in Gait model. If clothing was not skin-tight, or if preferred, participants wore an Optitrack Motion Capture Suit where markers were attached using Velcro. Data Analysis Data were processed in Visual3D (C-Motion, Inc., Germantown, MD, USA), and further processed in MATLAB (Version R2024a, MathWorks Inc., USA). Data were filtered using a low pass 4th order Butterworth filter with a cut-off frequency of 6Hz 41 . The head and pelvis were defined as rigid bodies, and transverse plane head and pelvis angle in relation to the global coordinate system was extracted, where a pelvis angle of 0° corresponded to the position at the start of the turn. The start of each turn was defined as when participants stopped in quiet stance on the target prior to each 360° turn, or the point where the head reached 5° rotation (whichever point was earlier). Turns were excluded from analysis if there was no clear stop before, after, or in between turns. Video recordings were used to identify turns to be excluded from analysis due to the presence of FOG events, assessed through the annotation of video recordings by a panel of trained researchers. Participants were excluded from the analysis if they were unable to complete any 360° turns without FOG, and if they had any turning problems unrelated to PD. Maximum head-pelvis angular difference was the maximum difference across the whole turn, and average angular difference was the average difference across the whole turn. Head-pelvis angular difference and coupling angle were calculated across the stride from heel strike to heel strike of the foot contralateral to the direction of turn (as described in the supplementary materials). Strides were categorised into three sections of the turn—start, middle, and end—based on the pelvis rotation angle (0–120°, 120–240°, and 240–360°, respectively) during 60% of the stride. Data preceding the first full stride and following the last full stride were excluded from analysis. Vector coding coupling angle was calculated across each stride based on head (H) and pelvis (P) rotation angle according to the following Eq. (1): $$\:{\theta\:}_{i}={\text{tan}}^{-1}(\frac{{P}_{(i+1)}-{P}_{\left(i\right)}}{{H}_{(i+1)}-{H}_{\left(i\right)}})$$ where 0° ≤ θ ≤ 360° and i represents consecutive data points 19 , 20 . The percentage of each stride in the in-phase coordination bin (22.5–67.5° and 202.5-247.5°) was calculated 18 . Coordination variability was calculated as circular standard deviation of coupling angle for the start, middle, and end of the turn for each participant 42 . A discrete measure of coordination variability was defined as the mean of the circular standard deviation across the stride. Statistical Analysis Discrete statistical analysis was performed in SPSS (Version 28, IBM, Chicago, IL). A two-way mixed model ANOVA (3x3) was used to examine differences between groups (PD + FOG, PD-FOG and HC) and part of the turn (start, middle, and end) in the percentage of the stride inphase, and coordination variability. A one-way ANOVA was used to investigate differences between groups in maximum/average angular difference, turn duration, and number of steps. A mixed-model ANCOVA, and one-way ANCOVA was performed using MDS-UPDRS (FOG item removed (3.11)) as covariate to account for differing disease severity between PD + FOG and PD-FOG groups. MiniBEST score was also included as a covariate to determine the contribution of balance ability to turning behaviour. Data were tested for sphericity using Mauchly’s test, and Greenhouse-Geisser corrections were applied if violated. Bonferroni corrections were applied to post-hoc comparisons to investigate significant main effects. Data presented as mean ± standard deviation (SD), and standard error (SEM) where values have been adjusted for covariate. SEM has been presented to reflect precision of the adjusted estimates and facilitates between-group comparisons by showing uncertainty in the mean rather than individual variability. Pearson’s correlations were carried out between coordination variability, turn duration, and MDS-UPDRS/MiniBEST scores. Using the SPM1D package (v.0.4.2) 43 , 44 , statistical parametric mapping (SPM) two-way ANOVA with repeated-measures on one factor was used to compare angular difference and coordination variability across the stride between groups and part of the turn. To account for MDS-UPDRS and MiniBEST scores, an SPM ANCOVA was used. Since the SPM1D package does not directly implement ANCOVA’s, an SPM regression was run and a two-way ANOVA with repeated-measures on one factor used to compare residuals between groups and part of the turn. Bonferroni corrections were applied to post-hoc comparisons. For all tests, the level of significance was set at p = 0.05. Results Participant Demographics Thirteen PD + FOG, twelve PD-FOG and seventeen HC were included in these analyses (see supplementary materials for further details). Participants in each group were well matched in demographic characteristics, and MOCA scores (Table 1 ). Balance abilities (MiniBEST) were better in HC, than PD + FOG, and balance was worse in PD + FOG. Disease severity was worse in the PD + FOG group than PD-FOG (both Hoehn and Yahr (H&Y) stage, and MDS-UPDRS score). Temporal Turning Characteristics The total number of steps per turn was significantly higher in PD + FOG than PD-FOG and HC. These differences remained when including MDS-UPDRS score and MiniBEST score as a covariate. PD + FOG took longer to turn than HC. However, when including MDS-UPDRS as a covariate, while a main effect of group remained, there was no longer a difference between PD + FOG and HC when Bonferroni corrections were applied (p = 0.061). En-bloc Turning - Angular Difference There were no significant differences between groups in maximum or average angular difference (as shown in Table 2 ). Based on SPM analysis of head-pelvis angular difference across the stride in each third of the turn, there was no significant interaction effect or main effect of group (as shown in Fig. 2 ). Angular difference was significantly lower from 54–100% of the stride in the end part of the turn compared to the start part of the turn. Angular difference was lower from 42–100% of the stride in strides at the end of the turn compared to strides in the middle of the turn. En-Bloc Turning – Percentage of the Stride Inphase There was a significant interaction between group and part of the turn in percentage of the stride in the in-phase coordination bin (p = 0.022, shown in Table 3 ). In the start of the turn, there was significantly less of the stride in the in-phase bin in the PD + FOG group (92.28 ± 4.14%) compared to the PD-FOG group (95.14 ± 2.24%; p = 0.019). In the middle of the turn there was less of the stride in the in-phase bin in the PD + FOG group (93.4 ± 3.64%) compared to the HC group (96.48 ± 0.436%; p = 0.002). In the HC group, start (94.26 ± 0.34%), middle, and end (83.55 ± 2.47%) were significantly different (p < 0.001 across all). In PD + FOG and PD-FOG groups, the start and middle (PD-FOG: 95.42 ± 2.02%) were different to the end of the turn (PD + FOG: 83.87 ± 4.66%; PD-FOG: 86.79 ± 5.62%; p < 0.001 for all comparisons). When including MiniBEST score and MDS-UPDRS score as a covariate, there was no longer an interaction effect, nor was there a main group effect. When accounting for MDS-UPDRS score, the end of the turn (85.31 ± 0.97%) had a significantly lower percentage in-phase than the start (93.72 ± 0.64%, p < 0.001) and middle of the turn (94.43 ± 0.56%, p < 0.001). When accounting for MiniBEST score, the end of the turn (84.93 ± 0.70%) had a lower percentage of the stride in-phase compared to the start (93.91 ± 0.44%, p < 0.001) and middle (95.13 ± 0.70%, p < 0.001). Here, the start of the turn had less of the stride in-phase compared to the middle of the turn (p < 0.001). Coordination Variability There was no interaction effect between group and turn section in discrete coordination variability (Table 3 ). PD + FOG (12.42 ± 0.95°) had higher coordination variability than PD-FOG (8.94 ± 0.99°, p = 0.047) and HC (7.48 ± 1.07°, p = 0.005). Coordination variability was higher at the end of the turn than at the start (p < 0.001) and middle (p < 0.001). When including MDS-UPDRS and MiniBEST score as a covariate, there was no longer a main effect of group. The main effect of part of turn remained when accounting for MiniBEST score (p = 0.002), but not MDS-UPDRS (p = 0.340). Coordination variability was associated with the turn duration and balance ability, but not disease severity. There was a moderate positive correlation between turn duration and coordination variability at the start (r = 0.393, p = 0.015) and end of the turn (r = 0.387, p = 0.008), and a strong positive correlation in the middle (r = 0.693, p < 0.001). MDS-UPDRS scores showed no significant correlation with coordination variability. MiniBEST scores had a moderate negative correlation with coordination variability in the middle (r=-0.341, p = 0.027) and end of the turn (r=-0.406, p = 0.008). MDS-UPDRS scores showed a moderate positive correlation with turn duration (r = 0.390, p = 0.036), while MiniBEST scores had a moderate negative correlation (r=-0.445, p = 0.003). In SPM analysis of coordination variability across the stride in each third of the turn, there was no significant interaction effect between group and part of turn. The PD + FOG group had significantly higher coordination variability than the PD-FOG group between 37–41% and 53–59% of the stride. The PD + FOG group had higher coordination variability at 30%, 36–38%, 40–41%, 43–55% of the stride. There were no significant differences in coordination variability between PD-FOG and HC groups. However, in the SPM analysis of the residuals from the regression between MDS-UPDRS/MiniBEST, and coordination variability, no group differences were observed (as shown in Fig. 3 ). There was no significant difference between strides in the start and middle of the turn. Strides at the end of the turn had higher coordination variability from 56–100% of the stride than at the start of the turn. Strides in the middle of the turn had lower head-pelvis coordination variability from 47–48%, 52–54% and 56–100% of the stride. Discussion This study aimed to investigate head-pelvis coordination in 360° on-the-spot turns in people with PD and FOG, PD without FOG, and healthy controls. Contrary to our hypothesis, results showed no differences between PD + FOG, PD-FOG and HC groups in angular difference across the stride, or in maximum angular difference during the turn. There were also no differences between PD + FOG, PD-FOG and HC groups in the percentage of the stride in which the head and pelvis were in-phase. Contrary to our second hypothesis, coordination variability was higher in PD + FOG than PD-FOG and HC, but this effect was no longer significant after accounting for disease severity and balance ability. PD + FOG took more steps to complete the turn than both PD-FOG and HC, even when controlling for these covariates. To quantify head-pelvis coordination during turning, we applied both previously used definitions of head-pelvis coordination (angular difference across the stride and maximum angular difference) as well as vector coding techniques that overcome limitations of focusing on maximum difference. Despite applying both methods, we found no evidence of more en-bloc turning in PD + FOG, or PD-FOG compared to HC. Spildooren and colleagues 5 found similar maximum head-pelvis angular differences in 180° walking turns in people with PD (without FOG = 27.3°; with FOG = 25.7°) to the present study (PD-FOG = 23.44 ± 14.56°; PD + FOG = 29.42 ± 14.21°). However, their control group showed greater maximum head-pelvis differences (35.4°) than our HC group (22.76 ± 8.94°). The typical head-first strategy deployed by healthy older adults is disrupted when turning on-the-spot towards predictable targets 45 , 16 , 46 , 47 . A smaller angular difference may reflect prioritisation of stability over visual input, as the target and movement path are known. Thus, the lower maximum angular difference in our HC group (compared to previous work 5 ) may be due to the reduced requirement for a head-first strategy when turning on-the-spot to pre-determined targets, unlike in the 180° walking turn paradigm. En-bloc turning in people with PD and older adults seems to be task-dependent, but it is unclear to what extent the nature of the task affords the need to gather information (through visual input). To understand the most influential aspect of the task, coordination should be compared across standing and walking turns at different angles. We found evidence of reduced in-phase coordination between the head and the pelvis in the strides at the end of the turn across all groups. Furthermore, SPM analysis revealed that angular difference was lower at the end of strides in the last part of the turn compared to the start and middle. This suggests that there is reorientation of the head and pelvis towards the end of the 360° turn. If the turn were completed in an en-bloc manner, head-pelvis angular difference and in-phase coordination would remain consistent throughout. We therefore found no evidence of en-bloc turning in any group. In previous literature, en-bloc turning is typically defined based on group-to-group comparisons of angular difference. For example, Yang et al. 6 found that, in 180° walking turns, the maximum head-pelvis angle was 18.41 ± 6.06° in people with PD, which was significantly lower than 22.77 ± 1.62° in a healthy control group; while significance was reached, interpretation of a more en-bloc strategy is ambiguous. Future work on en-bloc turning should analyse movement patterns throughout the turn to determine the presence of an en-bloc strategy, rather than relying on group comparisons. We found higher head-pelvis coordination variability in PD + FOG compared to PD-FOG and HC, with significant correlations between coordination variability and turn duration (start: r = 0.393, middle: r = 0.693, end: r = 0.387), and between coordination variability and MiniBEST score (middle: r=-0.341; end: r=-0.387). These results do not align with the loss of complexity hypothesis 24 , 48 , but could instead be a phenomenon arising due to the relative difficulty posed by a given task. Specifically, exploratory behaviour may arise because the 360° turning task is designed to challenge motor control to elicit FOG. Furthermore, coordination variability was higher in the strides at the end of the turn across all groups. As a 360° turn is longer than most turns that occur in daily living 32 the end of the turn is more challenging, indicating that the task demands get progressively greater, exposing weaknesses. FOG occurs most frequently towards the end of turning (albeit in 180° turns) 5 , 51 , which may be due to this variability acting as a sequence effect 54 from the increasing challenge of movement control. Variability may accumulate and reach a threshold where FOG is triggered, explaining why 360° turning elicits FOG more than other turning tasks 30 . This finding parallels observations in motor learning paradigms where the stages of motor skill acquisition are associated with a U-shaped trajectory in coordination variability 49 . Here, coordination variability is highest in the least and most skilled performers, and lowest in intermediate-level performers 49 . This reflects exploratory behaviour in novices, but an ability to exploit degrees of freedom in the motor system in skilled performers. Exploratory behaviour seen in the 360° turn could reflect both lower levels of skill and cautious behaviour. For a given task, while we may see more en-bloc turning, head-pelvis coordination variability likely better reflects the underlying motor control. Future research should focus on the relationship between variability and FOG. Head-pelvis coordination variability seems to be more closely related to balance ability than disease severity. While coordination variability across strides at the middle and end of the turn was correlated with balance ability, there was no correlation with MDS-UPDRS score. Furthermore, when including MiniBEST score as a covariate, the group effect in discrete coordination variability, and, in SPM analysis, the group effect in the middle of the stride, was no longer significant. This reflects previous findings, as Cheng et al. 52 found that balance ability influenced turn duration across a 180° turn more than MDS-UPDRS score, or NFOGQ score. Future work could employ balance training to improve turning and evaluate the potential impact on coordination variability. Head-pelvis coordination variability does not seem to be directly linked to FOG pathology. When including MDS-UPDRS score as a covariate, there were no longer differences between PD + FOG and PD-FOG/HC. FOG more frequently presents in people with moderate to severe PD 34 , so it is important to control for disease severity to understand whether behaviour is inherently linked to FOG pathology or more general progression of motor symptoms. Previous research comparing people with PD with and without FOG typically shows no statistically significant differences in MDS-UPDRS or H&Y score between groups, often sampling to match disease severity 10 , 31 , 41 , 51 . We believe that there are two main issues with this approach. First, selective sampling to match groups based on severity of motor symptoms compromises the generalisability of the group with FOG. Secondly, the absence of significant differences between groups cannot be unambiguously interpreted as evidence of no meaningful differences in disease severity, especially in highly heterogeneous samples where large variability in disease severity scores hinders the ability to detect between-group differences. We argue that statistically controlling for MDS-UPDRS score overcomes both issues, so should be considered for further work. The number of steps taken to complete a 360° turn seems to be linked to FOG pathology. The PD + FOG group took more steps to turn compared to PD-FOG and HC, even when accounting for balance ability and disease severity. This aligns with previous results as, in a meta-analysis 10 , people with PD and FOG took more steps in turns than those without FOG (mean difference of 4.98 steps in 360° turning). In straight line walking, inducing shorter-than-preferred step length increased the number of FOG events 54 , and stride length progressively reduces prior to FOG 55 . An increased number of steps may therefore contribute to the onset of FOG. Alternatively, the increased number of steps could reflect prioritisation of stability. Shorter, more frequent steps represent a more stable strategy because the centre of mass (COM) is closer to the moving base of support 56 . A reduction in stride length has been found to increase margins of stability in the backwards direction (distance in anterior-posterior direction between COM and posterior border of the leading foot) during forward walking 57 . Furthermore, decreases in stride length have been found in anticipation of 58 , and response to perturbations 59 – 61 . Smaller stride length is therefore likely to represent a strategy to increase mediolateral and backward margins of stability and thus prevent postural instability in the presence of perturbations (including unexpected FOG events). An increased number of steps in the turn may therefore be a strategy to prioritise stability over movement efficiency. There are several limitations in this study. Firstly, people with PD were only assessed while ‘ON’ medication. While this is more clinically meaningful, as most tasks and interventions (including turning) are performed ‘ON’ medication, medication status can influence turning behaviour for the better 31 . Inclusion to the PD + FOG group was based on self-report of FOG from the NFOGQ. FOG was observed in most participants, either during the task or on other occasions during the laboratory visit. However, formally recording the presence of ‘definite FOG’ during the visit for group allocation would be recommended for further work. Finally, strides were defined based on the contralateral foot heel strike, meaning dynamics of head-pelvis coordination were not considered before the first contralateral heel strike. Likewise, segment rotation onsets were not reported, as heterogeneity of methods of calculating onset in the literature makes values incomparable. In conclusion, people with PD did not turn more en-bloc in a 360° on-the-spot turn compared to healthy older adults. Head-pelvis coordination variability was higher in people with PD and FOG. While we may see more en-bloc turning in a task, we propose that head-pelvis coordination variability likely better reflects the underlying motor control, so should be the focus of future work. After correcting for disease severity (MDS-UPDRS), there were no differences between groups. Therefore, future research should account for disease severity when investigating characteristics of turning and gait in people with PD and FOG. People with PD and FOG took more steps to turn, even when controlling for disease severity. Although it remains unclear whether this increases the likelihood of FOG or is compensatory behaviour. Further research should investigate stepping behaviour and head-pelvis coordination leading to FOG episodes in 360° turning to understand the contribution of head-pelvis coordination to FOG. Data Availability The datasets generated and analysed during the current study are available in the Open Science Framework repository, https://osf.io/ydb4z/ . For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. Declarations Data Availability The datasets generated and analysed during the current study are available in the Open Science Framework repository, https://osf.io/ydb4z/. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. Acknowledgements This work was funded by Parkinson’s UK (G-2007) and was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. We thank the participants, the people who accompanied them in the laboratory, the members of Parkinson’s UK branches who supported our recruitment as well as our Project Advisory Group for their contributions to study conception, design, interpretation of results and dissemination. Author Contributions Conception and design – PL, YR, GW, WY; Acquisition of data - YR, PL, JY, ZW, WY Data curation, formal analysis and visualisation – PL, YR; Writing original draft – PL, WY, GW, YR; Writing review & editing - All the authors; Final approval of the completed article - All the authors; Funding acquisition – WY, SL; Supervision – WY, GW, YR, SL Competing Interests The authors declare no competing interests. References Glaister, B. C., Bernatz, G. C., Klute, G. K. & Orendurff, M. S. Video task analysis of turning during activities of daily living. Gait & Posture 25, 289–294 (2007). Courtine, G. & Schieppati, M. Human walking along a curved path. I. 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Giladi, N. & Nieuwboer, A. Understanding and treating freezing of gait in parkinsonism, proposed working definition, and setting the stage. Mov. Disord. 23, S423–S425 (2008). Snijders, A. H., Haaxma, C. A., Hagen, Y. J., Munneke, M. & Bloem, B. R. Freezer or non-freezer: Clinical assessment of freezing of gait. Parkinsonism & Related Disorders 18, 149–154 (2012). Spildooren, J., Vinken, C., Van Baekel, L. & Nieuwboer, A. Turning problems and freezing of gait in Parkinson’s disease: a systematic review and meta-analysis. Disability and Rehabilitation 41, 2994–3004 (2019). Hong, M., Perlmutter, J. S. & Earhart, G. M. A kinematic and electromyographic analysis of turning in people with Parkinson disease. Neurorehabilitation and Neural Repair 23, 166–176 (2009). Hulbert, S., Ashburn, A., Roberts, L. & Verheyden, G. Dance for Parkinson’s—The effects on whole body co-ordination during turning around. Complementary Therapies in Medicine 32, 91–97 (2017). Mak, M. K. Y., Patla, A. & Hui-Chan, C. Sudden turn during walking is impaired in people with Parkinson’s disease. Exp Brain Res 190, 43–51 (2008). Ambati, V. N. P., Saucedo, F., Murray, N. G., Powell, D. W. & Reed-Jones, R. J. Constraining eye movement in individuals with Parkinson’s disease during walking turns. Experimental Brain Research 234, 2957–2965 (2016). Baker, T., Pitman, J., MacLellan, M. J. & Reed-Jones, R. J. Visual Cues Promote Head First Strategies During Walking Turns in Individuals With Parkinson’s Disease. Frontiers in Sports and Active Living 2, (2020). Akram, S. B., Frank, J. S. & Fraser, J. Coordination of segments reorientation during on-the-spot turns in healthy older adults in eyes-open and eyes-closed conditions. Gait and Posture 32, 632–636 (2010). Solomon, D., Vijay Kumar, Jenkins, R. A. & Jewell, J. Head control strategies during whole-body turns. Experimental Brain Research 173, 475–486 (2006). Chang, R., Van Emmerik, R. & Hamill, J. Quantifying rearfoot–forefoot coordination in human walking. Journal of Biomechanics 41, 3101–3105 (2008). Needham, R. A., Naemi, R. & Chockalingam, N. A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique. Journal of Biomechanics 48, 3506–3511 (2015). Needham, R., Naemi, R. & Chockalingam, N. Quantifying lumbar–pelvis coordination during gait using a modified vector coding technique. Journal of Biomechanics 47, 1020–1026 (2014). Silveira-Ciola, A. P., Simieli, L., Rinaldi, N. M. & Barbieri, F. A. The starting distance of obstacle circumvention did not affect intersegmental coordination in individuals with Parkinson’s disease. Human Movement Science 80, (2021). Bernstein, N. The Co-Ordination and Regulation of Movements . (Pergamon Press Ltd., 1967). Stergiou, N., Harbourne, R. T. & Cavanaugh, J. T. Optimal Movement Variability: A New Theoretical Perspective for Neurologic Physical Therapy. Journal of Neurologic Physical Therapy 30, 120–129 (2006). Stergiou, N. & Decker, L. M. Human movement variability, nonlinear dynamics, and pathology: Is there a connection? Human Movement Science 30, 869–888 (2011). Van Emmerik, R. E. A., Wagenaar, R. C., Winogrodzka, A. & Walters, E. C. Identification of Axial Rigidity During Locomotion in Parkinson Disease . (1999). Caetano, M. J. D. et al. Stepping reaction time and gait adaptability are significantly impaired in people with Parkinson’s disease: Implications for fall risk. Parkinsonism & Related Disorders 47, 32–38 (2018). Franzén, E. et al. Reduced performance in balance, walking and turning tasks is associated with increased neck tone in Parkinson’s disease. Experimental Neurology 219, 430–438 (2009). Ziegler, K., Schroeteler, F., Ceballos-Baumann, A. O. & Fietzek, U. M. A new rating instrument to assess festination and freezing gait in Parkinsonian patients. Mov. Disord. 25, 1012–1018 (2010). Van Dijsseldonk, K., Wang, Y., Van Wezel, R., Bloem, B. R. & Nonnekes, J. Provoking Freezing of Gait in Clinical Practice: Turning in Place is More Effective than Stepping in Place. JPD 8, 363–365 (2018). Conde, C. I. et al. Triggers for freezing of gait in individuals with Parkinson’s disease: a systematic review. Front. Neurol. 14, 1326300 (2023). McNeely, M. E. & Earhart, G. M. The Effects of Medication on Turning in People with Parkinson Disease with and without Freezing of Gait. Journal of Parkinson’s Disease 1, 259–270 (2011). Mancini, M., Weiss, A., Herman, T. & Hausdorff, J. M. Turn Around Freezing: Community-Living Turning Behavior in People with Parkinson’s Disease. Front. Neurol. 9, 18 (2018). Stack, E. & Ashburn, A. Dysfunctional turning in Parkinson’s disease. Disability and Rehabilitation 30, 1222–1229 (2008). Nutt, J. G. et al. Freezing of gait: moving forward on a mysterious clinical phenomenon. The Lancet Neurology 10, 734–744 (2011). Russo, Y. et al. Does visual cueing improve gait initiation in people with Parkinson’s disease? Human Movement Science 84, 102970 (2022). Gelb, D. J., Oliver, E. & Gilman, S. Diagnostic Criteria for Parkinson Disease. Arch Neurol 56, 33 (1999). Nieuwboer, A. et al. Reliability of the new freezing of gait questionnaire: Agreement between patients with Parkinson’s disease and their carers. Gait & Posture 30, 459–463 (2009). Goetz, C. G. et al. Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results. Movement Disorders 23, 2129–2170 (2008). Löfgren, N., Lenholm, E., Conradsson, D., Ståhle, A. & Franzén, E. The Mini-BESTest - a clinically reproducible tool for balance evaluations in mild to moderate Parkinson’s disease? BMC Neurol 14, 235 (2014). Nasreddine, Z. S. et al. The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment. J American Geriatrics Society 53, 695–699 (2005). Lohnes, C. A. & Earhart, G. M. Saccadic eye movements are related to turning performance in parkinson disease. Journal of Parkinson’s Disease 1, 109–118 (2011). Batschelet, E. Circular Statistics in Biology . (London ; New York : Academic Press, 1981). Pataky, T. C. One-dimensional statistical parametric mapping in Python. Computer Methods in Biomechanics and Biomedical Engineering 15, 295–301 (2012). Pataky, TC. Generalized n-dimensional biomechanical field analysis using statistical parametric mapping. Journal of Biomechanics 43, 1976–1982 (2010). Anastasopoulos, D., Ziavra, N., Hollands, M. & Bronstein, A. Gaze displacement and inter-segmental coordination during large whole body voluntary rotations. Exp Brain Res 193, 323–336 (2009). Ahmad, R. Temporal Kinematics of Rotation of Body Segments During Turning on the Spot: A review of the literature. 20, (2012). Khobkhun, F., Hollands, M. & Richards, J. A Comparison of Turning Kinematics at Different Amplitudes during Standing Turns between Older and Younger Adults. Applied Sciences 12, 5474 (2022). Stergiou, N., Kent, J. A. & McGrath, D. Human Movement Variability and Aging. Kinesiology Review 5, 15–22 (2016). Wilson, C., Simpson, S. E., Van Emmerik, R. E. A. & Hamill, J. Coordination variability and skill development in expert triple jumpers. Sports Biomechanics 7, 2–9 (2008). Hafer, J. F. & Boyer, K. A. Age related differences in segment coordination and its variability during gait. Gait & Posture 62, 92–98 (2018). Bengevoord, A. et al. Center of mass trajectories during turning in patients with Parkinson’s disease with and without freezing of gait. Gait & Posture 43, 54–59 (2016). Cheng, F.-Y. et al. Factors Influencing Turning and Its Relationship with Falls in Individuals with Parkinson’s Disease. PLoS ONE 9, e93572 (2014). Tinetti, M. E. Performance-Oriented Assessment of Mobility Problems in Elderly Patients. Journal of the American Geriatrics Society 34, 119–126 (1986). Chee, R., Murphy, A., Danoudis, M., Georgiou-Karistianis, N. & Iansek, R. Gait freezing in Parkinson’s disease and the stride length sequence effect interaction. Brain 132, 2151–2160 (2009). Nieuwboer, A. et al. Abnormalities of the spatiotemporal characteristics of gait at the onset of freezing in Parkinson’s disease. Movement Disorders 16, 1066–1075 (2001). Bhatt, T., Wening, J. D. & Pai, Y.-C. Influence of gait speed on stability: recovery from anterior slips and compensatory stepping. Gait & Posture 21, 146–156 (2005). Hak, L., Houdijk, H., Beek, P. J. & Van Dieën, J. H. Steps to Take to Enhance Gait Stability: The Effect of Stride Frequency, Stride Length, and Walking Speed on Local Dynamic Stability and Margins of Stability. PLoS ONE 8, e82842 (2013). Swart, S. B., Den Otter, R. & Lamoth, C. J. C. Anticipatory control of human gait following simulated slip exposure. Sci Rep 10, 9599 (2020). Hak, L. et al. Speeding up or slowing down?: Gait adaptations to preserve gait stability in response to balance perturbations. Gait & Posture 36, 260–264 (2012). Hak, L. et al. Walking in an Unstable Environment: Strategies Used by Transtibial Amputees to Prevent Falling During Gait. Archives of Physical Medicine and Rehabilitation 94, 2186–2193 (2013). Siragy, T., Russo, Y., Young, W. & Lamb, S. E. Comparison of over-ground and treadmill perturbations for simulation of real-world slips and trips: A systematic review. Gait & Posture 100, 201–209 (2023). Tables Table 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table13.docx PLeveridgeBeyondenblocturningSupplementaryMaterials.pdf 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6456602","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":444315978,"identity":"569810d8-dad8-4c38-a9f8-a6ba6fb24d15","order_by":0,"name":"Phaedra Leveridge","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYDACHubGAx8MJOSQxZgJaGFsODijwsIYyGRsIFrLYZ4zFYkNRGsx5znYcIC3TSK9XyL5+IOPexjk+Rt4jA3wabHsbWw4INkmkTuz51hi44xnDIYzDvAYJ+DTYnCeseGAIVDLhuM9hs08BxgYNzDwGB8gqCUR6DD7w/wfm/8cYLAnrOUs0GEHzkgkGLD3MDYzHGBIBGnB6zDLnoMNBxsqJAxnnDlmOLPngETyjMNsxXi9b86TfPDxH4M6ef4ZyQ8+/DhgY9vf3rxZAq/D0PgSBCMSQ8soGAWjYBSMAkwAAMamTqxmf+0LAAAAAElFTkSuQmCC","orcid":"","institution":"University of Exeter","correspondingAuthor":true,"prefix":"","firstName":"Phaedra","middleName":"","lastName":"Leveridge","suffix":""},{"id":444315979,"identity":"6f1fd74b-0f07-4cac-a596-21c8ea04abf7","order_by":1,"name":"Yuri Russo","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Yuri","middleName":"","lastName":"Russo","suffix":""},{"id":444315980,"identity":"a87a1cfc-e055-4a06-98c7-842d126fdc7d","order_by":2,"name":"Genevieve Williams","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Genevieve","middleName":"","lastName":"Williams","suffix":""},{"id":444315981,"identity":"5d86a0a0-a084-4099-9bda-7a445c13a9dd","order_by":3,"name":"Jiaxi Ye","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Jiaxi","middleName":"","lastName":"Ye","suffix":""},{"id":444315982,"identity":"b2c00a13-a8a5-4944-a44d-55d6107c93d0","order_by":4,"name":"Zijing Wang","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Zijing","middleName":"","lastName":"Wang","suffix":""},{"id":444315983,"identity":"a17d85db-4a16-427e-a85b-cdf6e293fcde","order_by":5,"name":"Sarah E Lamb","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"E","lastName":"Lamb","suffix":""},{"id":444315984,"identity":"a2c4e598-85b0-4e0a-9623-eca825ded4d4","order_by":6,"name":"William Young","email":"","orcid":"","institution":"University of Exeter","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"Young","suffix":""}],"badges":[],"createdAt":"2025-04-15 16:08:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6456602/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6456602/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81349555,"identity":"af011936-7142-4fd6-b884-c5329ec343ef","added_by":"auto","created_at":"2025-04-25 06:01:11","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":168225,"visible":true,"origin":"","legend":"\u003cp\u003e1a depicts the walking and turning task in a clockwise direction, and 1b in an anticlockwise direction. Yellow and black striped circles depict the target where participants completed 360° turns in each direction. Yellow and blue circles show the location of the cones. The footprint denotes the start point. Arrows show direction of travel.\u003c/p\u003e","description":"","filename":"floatimage111.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6456602/v1/de102cb37d0459af9a33ca9c.jpeg"},{"id":81349553,"identity":"9ff0e6bb-d35f-4d8d-9b57-09d2ada26383","added_by":"auto","created_at":"2025-04-25 06:01:11","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79306,"visible":true,"origin":"","legend":"\u003cp\u003eHead-pelvis angular difference across the stride at the start, middle and end of the turn in HC (green), PD+FOG (blue) and PD-FOG (orange) groups. Transparent data points represent angular difference for each participant, and bold points represent the mean for each group. There was no significant main effect of group. Significant main effects of part of turn are presented in the bottom plot.\u003c/p\u003e","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6456602/v1/2fd84a3ab81f0cb912be8209.jpeg"},{"id":81350325,"identity":"052ebced-c77f-4c64-a703-50c8306986e6","added_by":"auto","created_at":"2025-04-25 06:09:11","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":58980,"visible":true,"origin":"","legend":"\u003cp\u003eHead-pelvis coordination variability across the stride at the start, middle and end of the turn in HC (green), PD+FOG (blue) and PD-FOG (orange) groups. Transparent data points represent coordination variability for each participant, and bold points represent the mean for each group. There was no significant main effect of group when accounting for MDS-UPDRS (or MiniBEST) score. Significant main effects of part of turn when accounting for MDS-UPDRS score are presented in the bottom plot (main effect of part of turn is the same when accounting for MiniBEST score).\u003c/p\u003e","description":"","filename":"groupimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6456602/v1/847114f49430b6cba8d5ab78.jpeg"},{"id":82126758,"identity":"77c032de-0d72-4deb-a092-8c8ed39fb0d3","added_by":"auto","created_at":"2025-05-07 04:16:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":898083,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6456602/v1/7d37be2b-c39f-4af8-b46f-79f1d973ac4e.pdf"},{"id":81350326,"identity":"1b84b931-84cf-4556-860f-53b891c55967","added_by":"auto","created_at":"2025-04-25 06:09:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":26783,"visible":true,"origin":"","legend":"","description":"","filename":"Table13.docx","url":"https://assets-eu.researchsquare.com/files/rs-6456602/v1/d1c12da0a1e256447531897f.docx"},{"id":81349560,"identity":"9670f52b-8827-47e5-8f4c-745d717042e3","added_by":"auto","created_at":"2025-04-25 06:01:12","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1440135,"visible":true,"origin":"","legend":"","description":"","filename":"PLeveridgeBeyondenblocturningSupplementaryMaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6456602/v1/7a94d4b9e9a0c4c989b50bf5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond En-Bloc Turning: Head-Pelvis Coordination Variability in 360° turns in people with Parkinson’s","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTurning, while standing or walking, is an essential component of human locomotion. Approximately one third of steps during daily living incorporate turns\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Typically, healthy adults first rotate their head in the direction of the turn, followed by their shoulders and pelvis\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Head-pelvis coordination in turning appears to be altered in people with PD, with a more \u0026lsquo;en-bloc\u0026rsquo; (in-line) strategy. Initiation of head rotation is postponed, resulting in a more closely coupled start of head and pelvis rotation in comparison with the top-down coordination in healthy controls \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Furthermore, maximum head-pelvis separation appears to be lower in people with PD compared to healthy older adults during 180\u0026deg; walking turns\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFreezing of gait (FOG) is experienced by over 50% of people who have PD\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. FOG is defined as a \u0026ldquo;brief, episodic absence, or marked reduction of forward progression of the feet despite the intention to walk\u0026rdquo;\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and is often experienced during turning\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. People with PD and FOG take longer and more steps to turn than those without, with the difference between groups increasing with turning angle\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Spildooren and co-workers\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e found that head-pelvis angular difference in the first 65\u0026deg; of a 180\u0026deg; turn was lower in people with FOG compared to people with PD without FOG. Reduced separation between head-pelvis motion is significant because it may reflect a reduced ability to coordinate segmental reorientation during turning.\u003c/p\u003e \u003cp\u003eIdentifying the most meaningful aspects of head-pelvis coordination to quantify can be challenging. Previous studies have used rotation onset times\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, maximum head-pelvis angular difference\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, and angular velocity \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Since the demands on head-pelvis coordination change throughout a turn, different sections may pose unique motor control challenges. Spildooren and co-workers\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e captured angular difference at every 5\u0026deg; of pelvis rotation, providing a view of head-pelvis separation throughout the turn. However, focusing on angular differences limits understanding of how the head and the pelvis move together. For example, it is possible to have a large angular difference yet experience rigid en-bloc motion (i.e. after the initial decoupling the relationship among the body segments does not change). Vector coding is used to quantify relative movement and coupling between segments, describing the relative predominance of motion in one segment or another\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Vector coding could therefore provide an informative measure representing the dynamic relationship between the head and pelvis across the turn.\u003c/p\u003e \u003cp\u003eCoordinated movement requires the complex organisation of multiple degrees of freedom to perform actions\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, variability in joint coordination is typically seen in healthy individuals, allowing motor patterns to be stable and repeatable, yet giving flexibility to adapt to task constraints\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In straight-line walking, head-pelvis coordination variability in the transverse plane is lower in people with PD than in healthy controls\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Similarly, people with PD have reduced gait adaptability (ability to adjust gait to target/obstacles)\u003csup\u003e26\u003c/sup\u003e, and increased axial rigidity\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e which may hinder an ability to adapt to the dynamic requirements of turning. However, head-pelvis coordination variability has not yet been investigated during turning in PD.\u003c/p\u003e \u003cp\u003eThe so-called \u0026lsquo;Ziegler protocol\u0026rsquo;\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, and paradigms using 360\u0026deg; standing turns, are increasingly used to elicit FOG in clinical and research settings\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Previous research investigating head-pelvis coordination in people with FOG has focused on walking turns of 180\u0026deg;\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. While 360\u0026deg; turning has been shown to provoke FOG, understanding coordination patterns during successful turns helps to contextualise findings. Investigating head-pelvis coordination in 360\u0026deg; turns may provide a clearer understanding of how segmental coupling is impacted in people with PD and FOG, as well as insight into the role of head-pelvis coordination in FOG.\u003c/p\u003e \u003cp\u003eDisease severity has been linked with turning behaviour in PD. Specifically, turning step count, velocity and turn duration are associated with disease severity\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. It remains unclear whether head-pelvis coordination is related to disease severity. FOG more frequently presents in people with moderate to severe PD, affecting more than 60% of those with a disease duration over 10 years\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Previous reports\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e have highlighted that disease severity should be statistically controlled for to isolate the contributions of FOG to behaviour. By controlling for disease severity, we can determine whether observed deficits are inherent to FOG as a symptom or reflect broader motor impairments associated with advanced PD.\u003c/p\u003e \u003cp\u003eUsing approaches novel to the context of turning in PD (vector coding and continuous analysis), we quantified head-pelvis coupling and coordination variability during 360\u0026deg; turning to explore whether segmental control during turning is a characteristic of people with PD and FOG or associated with disease severity or balance. This study compared head-pelvis coordination in 360\u0026deg; on-the-spot turns in people with PD and FOG (PD\u0026thinsp;+\u0026thinsp;FOG), PD without FOG (PD-FOG), and healthy controls (HC). It was hypothesised that: (i) head-pelvis angular difference would be lower, and the percentage of the stride in-phase would be higher in PD\u0026thinsp;+\u0026thinsp;FOG than HC and PD-FOG; (ii) head-pelvis coordination variability would be lower in PD\u0026thinsp;+\u0026thinsp;FOG than PD-FOG and HC (iii) increased disease severity would exacerbate differences between PD\u0026thinsp;+\u0026thinsp;FOG and PD-FOG.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis study followed an observational cross-sectional design. All participants with PD were tested ON medication \u0026ndash; (approximately 60 minutes after their last dose) of dopaminergic medication. The study was approved by the local institutional review board of the University of Exeter (21-12-08-B-02, Department of Public Health \u0026amp; Sport Sciences).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eForty-five people with PD were recruited through local Parkinson\u0026rsquo;s UK branches. Twenty-three self-reported frequently experiencing FOG (PD\u0026thinsp;+\u0026thinsp;FOG), and twenty-two did not experience FOG (PD-FOG). Participants in each group required a diagnosis of idiopathic PD using the UK Brain Bank Criteria\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Participants were included in the PD\u0026thinsp;+\u0026thinsp;FOG group if they self-reported FOG according to the first item of the New Freezing of Gait Questionnaire (NFOG-Q)\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Twenty-seven older adults (aged 55 years+) were recruited as controls (HC). Participants were required to be able to walk unsupported (\u0026gt;\u0026thinsp;1 minute), have no cognitive impairment (Montreal Cognitive Assessment (MOCA) Score\u0026thinsp;\u0026gt;\u0026thinsp;20), have no comorbidities that would affect balance or walking, and be aged 55\u0026thinsp;+\u0026thinsp;years old. All participants provided written informed consent prior to participating in the study.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eAfter providing informed consent, participants with PD were rated by a trained examiner on the Motor Section (III) of the Movement Disorder Society-Unified PD Rating Scale (MDS-UPDRS)\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Mini Balance Evaluation Systems Test (MiniBEST)\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e and the MOCA\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e were administered to all participants. All participants were asked to complete a walking task (shown in Fig.\u0026nbsp;1) in a clockwise direction, followed by an anti-clockwise direction. They were asked to walk through cones to a yellow and black striped circular target in the capture area. Then, they were instructed to stop on the target and complete a modified Ziegler protocol\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e - where a 360˚ turn was performed in one direction, then a second 360˚ turn was performed in the opposite direction. Participants were asked to stop before and after each turn. Once the turning task had been completed, the participant continued through the cones to the next target and repeated the task. Participants were instructed when to change from travelling in the clockwise direction to anticlockwise, completing around 4\u0026ndash;5 targets in each direction.\u003c/p\u003e\u003cp\u003eKinematic data were recorded during the task using a 19-camera motion capture system (Prime 13, Optitrack, USA) with a sampling rate of 100 Hz. Thirty-nine retroreflective markers were placed on each participant\u0026rsquo;s skin and clothing according to the full-body Plug-in Gait model. If clothing was not skin-tight, or if preferred, participants wore an Optitrack Motion Capture Suit where markers were attached using Velcro.\u0026nbsp;\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData were processed in Visual3D (C-Motion, Inc., Germantown, MD, USA), and further processed in MATLAB (Version R2024a, MathWorks Inc., USA). Data were filtered using a low pass 4th order Butterworth filter with a cut-off frequency of 6Hz\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. The head and pelvis were defined as rigid bodies, and transverse plane head and pelvis angle in relation to the global coordinate system was extracted, where a pelvis angle of 0\u0026deg; corresponded to the position at the start of the turn.\u003c/p\u003e \u003cp\u003eThe start of each turn was defined as when participants stopped in quiet stance on the target prior to each 360\u0026deg; turn, or the point where the head reached 5\u0026deg; rotation (whichever point was earlier). Turns were excluded from analysis if there was no clear stop before, after, or in between turns. Video recordings were used to identify turns to be excluded from analysis due to the presence of FOG events, assessed through the annotation of video recordings by a panel of trained researchers. Participants were excluded from the analysis if they were unable to complete any 360\u0026deg; turns without FOG, and if they had any turning problems unrelated to PD.\u003c/p\u003e \u003cp\u003eMaximum head-pelvis angular difference was the maximum difference across the whole turn, and average angular difference was the average difference across the whole turn. Head-pelvis angular difference and coupling angle were calculated across the stride from heel strike to heel strike of the foot contralateral to the direction of turn (as described in the supplementary materials). Strides were categorised into three sections of the turn\u0026mdash;start, middle, and end\u0026mdash;based on the pelvis rotation angle (0\u0026ndash;120\u0026deg;, 120\u0026ndash;240\u0026deg;, and 240\u0026ndash;360\u0026deg;, respectively) during 60% of the stride. Data preceding the first full stride and following the last full stride were excluded from analysis.\u003c/p\u003e \u003cp\u003eVector coding coupling angle was calculated across each stride based on head (H) and pelvis (P) rotation angle according to the following Eq.\u0026nbsp;(1):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{\\theta\\:}_{i}={\\text{tan}}^{-1}(\\frac{{P}_{(i+1)}-{P}_{\\left(i\\right)}}{{H}_{(i+1)}-{H}_{\\left(i\\right)}})$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere 0\u0026deg; \u0026le; θ\u0026thinsp;\u0026le;\u0026thinsp;360\u0026deg; and i represents consecutive data points\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The percentage of each stride in the in-phase coordination bin (22.5\u0026ndash;67.5\u0026deg; and 202.5-247.5\u0026deg;) was calculated\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Coordination variability was calculated as circular standard deviation of coupling angle for the start, middle, and end of the turn for each participant \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. A discrete measure of coordination variability was defined as the mean of the circular standard deviation across the stride.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDiscrete statistical analysis was performed in SPSS (Version 28, IBM, Chicago, IL). A two-way mixed model ANOVA (3x3) was used to examine differences between groups (PD\u0026thinsp;+\u0026thinsp;FOG, PD-FOG and HC) and part of the turn (start, middle, and end) in the percentage of the stride inphase, and coordination variability. A one-way ANOVA was used to investigate differences between groups in maximum/average angular difference, turn duration, and number of steps. A mixed-model ANCOVA, and one-way ANCOVA was performed using MDS-UPDRS (FOG item removed (3.11)) as covariate to account for differing disease severity between PD\u0026thinsp;+\u0026thinsp;FOG and PD-FOG groups. MiniBEST score was also included as a covariate to determine the contribution of balance ability to turning behaviour. Data were tested for sphericity using Mauchly\u0026rsquo;s test, and Greenhouse-Geisser corrections were applied if violated. Bonferroni corrections were applied to post-hoc comparisons to investigate significant main effects. Data presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and standard error (SEM) where values have been adjusted for covariate. SEM has been presented to reflect precision of the adjusted estimates and facilitates between-group comparisons by showing uncertainty in the mean rather than individual variability. Pearson\u0026rsquo;s correlations were carried out between coordination variability, turn duration, and MDS-UPDRS/MiniBEST scores.\u003c/p\u003e \u003cp\u003eUsing the SPM1D package (v.0.4.2)\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, statistical parametric mapping (SPM) two-way ANOVA with repeated-measures on one factor was used to compare angular difference and coordination variability across the stride between groups and part of the turn. To account for MDS-UPDRS and MiniBEST scores, an SPM ANCOVA was used. Since the SPM1D package does not directly implement ANCOVA\u0026rsquo;s, an SPM regression was run and a two-way ANOVA with repeated-measures on one factor used to compare residuals between groups and part of the turn. Bonferroni corrections were applied to post-hoc comparisons. For all tests, the level of significance was set at p\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipant Demographics\u003c/h2\u003e\n \u003cp\u003eThirteen PD\u0026thinsp;+\u0026thinsp;FOG, twelve PD-FOG and seventeen HC were included in these analyses (see supplementary materials for further details). Participants in each group were well matched in demographic characteristics, and MOCA scores (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Balance abilities (MiniBEST) were better in HC, than PD\u0026thinsp;+\u0026thinsp;FOG, and balance was worse in PD\u0026thinsp;+\u0026thinsp;FOG. Disease severity was worse in the PD\u0026thinsp;+\u0026thinsp;FOG group than PD-FOG (both Hoehn and Yahr (H\u0026amp;Y) stage, and MDS-UPDRS score).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eTemporal Turning Characteristics\u003c/h3\u003e\n\u003cp\u003eThe total number of steps per turn was significantly higher in PD\u0026thinsp;+\u0026thinsp;FOG than PD-FOG and HC. These differences remained when including MDS-UPDRS score and MiniBEST score as a covariate. PD\u0026thinsp;+\u0026thinsp;FOG took longer to turn than HC. However, when including MDS-UPDRS as a covariate, while a main effect of group remained, there was no longer a difference between PD\u0026thinsp;+\u0026thinsp;FOG and HC when Bonferroni corrections were applied (p\u0026thinsp;=\u0026thinsp;0.061).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ch2 align=\"left\" class=\"colspec\"\u003eEn-bloc Turning - Angular Difference\u003c/h2\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003cp\u003eThere were no significant differences between groups in maximum or average angular difference (as shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eBased on SPM analysis of head-pelvis angular difference across the stride in each third of the turn, there was no significant interaction effect or main effect of group (as shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Angular difference was significantly lower from 54\u0026ndash;100% of the stride in the end part of the turn compared to the start part of the turn. Angular difference was lower from 42\u0026ndash;100% of the stride in strides at the end of the turn compared to strides in the middle of the turn.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eEn-Bloc Turning \u0026ndash; Percentage of the Stride Inphase\u003c/h2\u003e\n \u003cp\u003eThere was a significant interaction between group and part of the turn in percentage of the stride in the in-phase coordination bin (p\u0026thinsp;=\u0026thinsp;0.022, shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). In the start of the turn, there was significantly less of the stride in the in-phase bin in the PD\u0026thinsp;+\u0026thinsp;FOG group (92.28\u0026thinsp;\u0026plusmn;\u0026thinsp;4.14%) compared to the PD-FOG group (95.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.24%; p\u0026thinsp;=\u0026thinsp;0.019). In the middle of the turn there was less of the stride in the in-phase bin in the PD\u0026thinsp;+\u0026thinsp;FOG group (93.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64%) compared to the HC group (96.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.436%; p\u0026thinsp;=\u0026thinsp;0.002). In the HC group, start (94.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34%), middle, and end (83.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.47%) were significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 across all). In PD\u0026thinsp;+\u0026thinsp;FOG and PD-FOG groups, the start and middle (PD-FOG: 95.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02%) were different to the end of the turn (PD\u0026thinsp;+\u0026thinsp;FOG: 83.87\u0026thinsp;\u0026plusmn;\u0026thinsp;4.66%; PD-FOG: 86.79\u0026thinsp;\u0026plusmn;\u0026thinsp;5.62%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all comparisons).\u003c/p\u003e\n \u003cp\u003eWhen including MiniBEST score and MDS-UPDRS score as a covariate, there was no longer an interaction effect, nor was there a main group effect. When accounting for MDS-UPDRS score, the end of the turn (85.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97%) had a significantly lower percentage in-phase than the start (93.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and middle of the turn (94.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When accounting for MiniBEST score, the end of the turn (84.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70%) had a lower percentage of the stride in-phase compared to the start (93.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and middle (95.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Here, the start of the turn had less of the stride in-phase compared to the middle of the turn (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eCoordination Variability\u003c/h2\u003e\n \u003cp\u003eThere was no interaction effect between group and turn section in discrete coordination variability (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). PD\u0026thinsp;+\u0026thinsp;FOG (12.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u0026deg;) had higher coordination variability than PD-FOG (8.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u0026deg;, p\u0026thinsp;=\u0026thinsp;0.047) and HC (7.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u0026deg;, p\u0026thinsp;=\u0026thinsp;0.005). Coordination variability was higher at the end of the turn than at the start (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and middle (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When including MDS-UPDRS and MiniBEST score as a covariate, there was no longer a main effect of group. The main effect of part of turn remained when accounting for MiniBEST score (p\u0026thinsp;=\u0026thinsp;0.002), but not MDS-UPDRS (p\u0026thinsp;=\u0026thinsp;0.340).\u003c/p\u003e\n \u003cp\u003eCoordination variability was associated with the turn duration and balance ability, but not disease severity. There was a moderate positive correlation between turn duration and coordination variability at the start (r\u0026thinsp;=\u0026thinsp;0.393, p\u0026thinsp;=\u0026thinsp;0.015) and end of the turn (r\u0026thinsp;=\u0026thinsp;0.387, p\u0026thinsp;=\u0026thinsp;0.008), and a strong positive correlation in the middle (r\u0026thinsp;=\u0026thinsp;0.693, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). MDS-UPDRS scores showed no significant correlation with coordination variability. MiniBEST scores had a moderate negative correlation with coordination variability in the middle (r=-0.341, p\u0026thinsp;=\u0026thinsp;0.027) and end of the turn (r=-0.406, p\u0026thinsp;=\u0026thinsp;0.008). MDS-UPDRS scores showed a moderate positive correlation with turn duration (r\u0026thinsp;=\u0026thinsp;0.390, p\u0026thinsp;=\u0026thinsp;0.036), while MiniBEST scores had a moderate negative correlation (r=-0.445, p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e\n \u003cp\u003eIn SPM analysis of coordination variability across the stride in each third of the turn, there was no significant interaction effect between group and part of turn. The PD\u0026thinsp;+\u0026thinsp;FOG group had significantly higher coordination variability than the PD-FOG group between 37\u0026ndash;41% and 53\u0026ndash;59% of the stride. The PD\u0026thinsp;+\u0026thinsp;FOG group had higher coordination variability at 30%, 36\u0026ndash;38%, 40\u0026ndash;41%, 43\u0026ndash;55% of the stride. There were no significant differences in coordination variability between PD-FOG and HC groups. However, in the SPM analysis of the residuals from the regression between MDS-UPDRS/MiniBEST, and coordination variability, no group differences were observed (as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThere was no significant difference between strides in the start and middle of the turn. Strides at the end of the turn had higher coordination variability from 56\u0026ndash;100% of the stride than at the start of the turn. Strides in the middle of the turn had lower head-pelvis coordination variability from 47\u0026ndash;48%, 52\u0026ndash;54% and 56\u0026ndash;100% of the stride.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to investigate head-pelvis coordination in 360\u0026deg; on-the-spot turns in people with PD and FOG, PD without FOG, and healthy controls. Contrary to our hypothesis, results showed no differences between PD\u0026thinsp;+\u0026thinsp;FOG, PD-FOG and HC groups in angular difference across the stride, or in maximum angular difference during the turn. There were also no differences between PD\u0026thinsp;+\u0026thinsp;FOG, PD-FOG and HC groups in the percentage of the stride in which the head and pelvis were in-phase. Contrary to our second hypothesis, coordination variability was higher in PD\u0026thinsp;+\u0026thinsp;FOG than PD-FOG and HC, but this effect was no longer significant after accounting for disease severity and balance ability. PD\u0026thinsp;+\u0026thinsp;FOG took more steps to complete the turn than both PD-FOG and HC, even when controlling for these covariates.\u003c/p\u003e \u003cp\u003eTo quantify head-pelvis coordination during turning, we applied both previously used definitions of head-pelvis coordination (angular difference across the stride and maximum angular difference) as well as vector coding techniques that overcome limitations of focusing on maximum difference. Despite applying both methods, we found no evidence of more en-bloc turning in PD\u0026thinsp;+\u0026thinsp;FOG, or PD-FOG compared to HC. Spildooren and colleagues\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e found similar maximum head-pelvis angular differences in 180\u0026deg; walking turns in people with PD (without FOG\u0026thinsp;=\u0026thinsp;27.3\u0026deg;; with FOG\u0026thinsp;=\u0026thinsp;25.7\u0026deg;) to the present study (PD-FOG\u0026thinsp;=\u0026thinsp;23.44\u0026thinsp;\u0026plusmn;\u0026thinsp;14.56\u0026deg;; PD\u0026thinsp;+\u0026thinsp;FOG\u0026thinsp;=\u0026thinsp;29.42\u0026thinsp;\u0026plusmn;\u0026thinsp;14.21\u0026deg;). However, their control group showed greater maximum head-pelvis differences (35.4\u0026deg;) than our HC group (22.76\u0026thinsp;\u0026plusmn;\u0026thinsp;8.94\u0026deg;). The typical head-first strategy deployed by healthy older adults is disrupted when turning on-the-spot towards predictable targets\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. A smaller angular difference may reflect prioritisation of stability over visual input, as the target and movement path are known. Thus, the lower maximum angular difference in our HC group (compared to previous work\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e) may be due to the reduced requirement for a head-first strategy when turning on-the-spot to pre-determined targets, unlike in the 180\u0026deg; walking turn paradigm. En-bloc turning in people with PD and older adults seems to be task-dependent, but it is unclear to what extent the nature of the task affords the need to gather information (through visual input). To understand the most influential aspect of the task, coordination should be compared across standing and walking turns at different angles.\u003c/p\u003e \u003cp\u003eWe found evidence of reduced in-phase coordination between the head and the pelvis in the strides at the end of the turn across all groups. Furthermore, SPM analysis revealed that angular difference was lower at the end of strides in the last part of the turn compared to the start and middle. This suggests that there is reorientation of the head and pelvis towards the end of the 360\u0026deg; turn. If the turn were completed in an en-bloc manner, head-pelvis angular difference and in-phase coordination would remain consistent throughout. We therefore found no evidence of en-bloc turning in any group. In previous literature, en-bloc turning is typically defined based on group-to-group comparisons of angular difference. For example, Yang et al.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e found that, in 180\u0026deg; walking turns, the maximum head-pelvis angle was 18.41\u0026thinsp;\u0026plusmn;\u0026thinsp;6.06\u0026deg; in people with PD, which was significantly lower than 22.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u0026deg; in a healthy control group; while significance was reached, interpretation of a more en-bloc strategy is ambiguous. Future work on en-bloc turning should analyse movement patterns throughout the turn to determine the presence of an en-bloc strategy, rather than relying on group comparisons.\u003c/p\u003e \u003cp\u003eWe found higher head-pelvis coordination variability in PD\u0026thinsp;+\u0026thinsp;FOG compared to PD-FOG and HC, with significant correlations between coordination variability and turn duration (start: r\u0026thinsp;=\u0026thinsp;0.393, middle: r\u0026thinsp;=\u0026thinsp;0.693, end: r\u0026thinsp;=\u0026thinsp;0.387), and between coordination variability and MiniBEST score (middle: r=-0.341; end: r=-0.387). These results do not align with the loss of complexity hypothesis\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, but could instead be a phenomenon arising due to the relative difficulty posed by a given task. Specifically, exploratory behaviour may arise because the 360\u0026deg; turning task is designed to challenge motor control to elicit FOG. Furthermore, coordination variability was higher in the strides at the end of the turn across all groups. As a 360\u0026deg; turn is longer than most turns that occur in daily living\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e the end of the turn is more challenging, indicating that the task demands get progressively greater, exposing weaknesses. FOG occurs most frequently towards the end of turning (albeit in 180\u0026deg; turns)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, which may be due to this variability acting as a sequence effect\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e from the increasing challenge of movement control. Variability may accumulate and reach a threshold where FOG is triggered, explaining why 360\u0026deg; turning elicits FOG more than other turning tasks\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. This finding parallels observations in motor learning paradigms where the stages of motor skill acquisition are associated with a U-shaped trajectory in coordination variability\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Here, coordination variability is highest in the least and most skilled performers, and lowest in intermediate-level performers\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. This reflects exploratory behaviour in novices, but an ability to exploit degrees of freedom in the motor system in skilled performers. Exploratory behaviour seen in the 360\u0026deg; turn could reflect both lower levels of skill and cautious behaviour. For a given task, while we may see more en-bloc turning, head-pelvis coordination variability likely better reflects the underlying motor control. Future research should focus on the relationship between variability and FOG.\u003c/p\u003e \u003cp\u003eHead-pelvis coordination variability seems to be more closely related to balance ability than disease severity. While coordination variability across strides at the middle and end of the turn was correlated with balance ability, there was no correlation with MDS-UPDRS score. Furthermore, when including MiniBEST score as a covariate, the group effect in discrete coordination variability, and, in SPM analysis, the group effect in the middle of the stride, was no longer significant. This reflects previous findings, as Cheng et al.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e found that balance ability influenced turn duration across a 180\u0026deg; turn more than MDS-UPDRS score, or NFOGQ score. Future work could employ balance training to improve turning and evaluate the potential impact on coordination variability.\u003c/p\u003e \u003cp\u003eHead-pelvis coordination variability does not seem to be directly linked to FOG pathology. When including MDS-UPDRS score as a covariate, there were no longer differences between PD\u0026thinsp;+\u0026thinsp;FOG and PD-FOG/HC. FOG more frequently presents in people with moderate to severe PD\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, so it is important to control for disease severity to understand whether behaviour is inherently linked to FOG pathology or more general progression of motor symptoms. Previous research comparing people with PD with and without FOG typically shows no statistically significant differences in MDS-UPDRS or H\u0026amp;Y score between groups, often sampling to match disease severity\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. We believe that there are two main issues with this approach. First, selective sampling to match groups based on severity of motor symptoms compromises the generalisability of the group with FOG. Secondly, the absence of significant differences between groups cannot be unambiguously interpreted as evidence of no meaningful differences in disease severity, especially in highly heterogeneous samples where large variability in disease severity scores hinders the ability to detect between-group differences. We argue that statistically controlling for MDS-UPDRS score overcomes both issues, so should be considered for further work.\u003c/p\u003e \u003cp\u003eThe number of steps taken to complete a 360\u0026deg; turn seems to be linked to FOG pathology. The PD\u0026thinsp;+\u0026thinsp;FOG group took more steps to turn compared to PD-FOG and HC, even when accounting for balance ability and disease severity. This aligns with previous results as, in a meta-analysis\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, people with PD and FOG took more steps in turns than those without FOG (mean difference of 4.98 steps in 360\u0026deg; turning). In straight line walking, inducing shorter-than-preferred step length increased the number of FOG events\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, and stride length progressively reduces prior to FOG\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. An increased number of steps may therefore contribute to the onset of FOG. Alternatively, the increased number of steps could reflect prioritisation of stability. Shorter, more frequent steps represent a more stable strategy because the centre of mass (COM) is closer to the moving base of support\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. A reduction in stride length has been found to increase margins of stability in the backwards direction (distance in anterior-posterior direction between COM and posterior border of the leading foot) during forward walking\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Furthermore, decreases in stride length have been found in anticipation of\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, and response to perturbations\u003csup\u003e\u003cspan additionalcitationids=\"CR60\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Smaller stride length is therefore likely to represent a strategy to increase mediolateral and backward margins of stability and thus prevent postural instability in the presence of perturbations (including unexpected FOG events). An increased number of steps in the turn may therefore be a strategy to prioritise stability over movement efficiency.\u003c/p\u003e \u003cp\u003eThere are several limitations in this study. Firstly, people with PD were only assessed while \u0026lsquo;ON\u0026rsquo; medication. While this is more clinically meaningful, as most tasks and interventions (including turning) are performed \u0026lsquo;ON\u0026rsquo; medication, medication status can influence turning behaviour for the better\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Inclusion to the PD\u0026thinsp;+\u0026thinsp;FOG group was based on self-report of FOG from the NFOGQ. FOG was observed in most participants, either during the task or on other occasions during the laboratory visit. However, formally recording the presence of \u0026lsquo;definite FOG\u0026rsquo; during the visit for group allocation would be recommended for further work. Finally, strides were defined based on the contralateral foot heel strike, meaning dynamics of head-pelvis coordination were not considered before the first contralateral heel strike. Likewise, segment rotation onsets were not reported, as heterogeneity of methods of calculating onset in the literature makes values incomparable.\u003c/p\u003e \u003cp\u003eIn conclusion, people with PD did not turn more en-bloc in a 360\u0026deg; on-the-spot turn compared to healthy older adults. Head-pelvis coordination variability was higher in people with PD and FOG. While we may see more en-bloc turning in a task, we propose that head-pelvis coordination variability likely better reflects the underlying motor control, so should be the focus of future work. After correcting for disease severity (MDS-UPDRS), there were no differences between groups. Therefore, future research should account for disease severity when investigating characteristics of turning and gait in people with PD and FOG. People with PD and FOG took more steps to turn, even when controlling for disease severity. Although it remains unclear whether this increases the likelihood of FOG or is compensatory behaviour. Further research should investigate stepping behaviour and head-pelvis coordination leading to FOG episodes in 360\u0026deg; turning to understand the contribution of head-pelvis coordination to FOG.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThe datasets generated and analysed during the current study are available in the Open Science Framework repository, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://osf.io/ydb4z/\u003c/span\u003e\u003cspan address=\"https://osf.io/ydb4z/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFor the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available in the Open Science Framework repository, https://osf.io/ydb4z/.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by Parkinson\u0026rsquo;s UK (G-2007) and was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. We thank the participants, the people who accompanied them in the laboratory, the members of Parkinson\u0026rsquo;s UK branches who supported our recruitment as well as our Project Advisory Group for their contributions to study conception, design, interpretation of results and dissemination.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design \u0026ndash; PL, YR, GW, WY; Acquisition of data - YR, PL, JY, ZW, WY Data curation, formal analysis and visualisation \u0026ndash; PL, YR; Writing original draft \u0026ndash; PL, WY, GW, YR; Writing review \u0026amp; editing - All the authors; Final approval of the completed article - All the authors; Funding acquisition \u0026ndash; WY, SL; Supervision \u0026ndash; WY, GW, YR, SL\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlaister, B. 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Comparison of over-ground and treadmill perturbations for simulation of real-world slips and trips: A systematic review. \u003cem\u003eGait\u003c/em\u003e \u0026amp; \u003cem\u003ePosture\u003c/em\u003e 100, 201\u0026ndash;209 (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","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":"turning, Parkinson’s disease, freezing of gait, segmental coordination, vector coding","lastPublishedDoi":"10.21203/rs.3.rs-6456602/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6456602/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePeople with Parkinson’s Disease (PD) and Freezing of Gait (FOG) reportedly turn using an ‘en-bloc’ strategy, where the head and pelvis rotate together, unlike the head-leading movement seen in healthy adults. However, previous research relies on discrete maximum separation angles in 180° walking turns, despite recommendations to use 360° on-the-spot turns to better induce FOG. Current reports in people with Parkinson’s also fail to capture the time-varying coordination of body segments as the turn unfolds. Our study aimed to investigate head-pelvis coordination across strides during 360° on-the-spot turns in people with PD and FOG (PD + FOG), PD without FOG (PD-FOG), and healthy controls (HC). Twelve PD + FOG, 14 PD-FOG (tested ON medication), and 17 HC completed the turns during which head and pelvis angles in the transverse plane were calculated across strides in the first, middle and final sections of the turn. Head-pelvis angular difference did not differ between groups. However, PD + FOG showed increased coordination variability compared to HC (4.93°, p = 0.005) and PD-FOG (3.47°, p = 0.047); an observation that was no longer apparent after adjusting for MDS-UPDRS motor scores (p = 0.249) and MiniBEST (p = 0.051). PD + FOG also took more steps than PD-FOG (3.94, p = 0.008) and HC (6.47, p \u0026lt; 0.001), even after adjusting for covariates (MDS-UPDRS: p = 0.037; MiniBEST: p = 0.003). These findings suggest that people with PD do not necessarily exhibit more en-bloc turning compared to healthy controls. While head-pelvis coordination variability is higher in people with PD + FOG, this does not seem to be linked to FOG pathology \u003cem\u003eper se\u003c/em\u003e, but rather balance deficits associated with disease severity. Increased step count seems to be related to FOG, which could be interpreted as a factors that might provoke FOG, but also serve as a compensatory strategy to promote postural stability.\u003c/p\u003e","manuscriptTitle":"Beyond En-Bloc Turning: Head-Pelvis Coordination Variability in 360° turns in people with Parkinson’s","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-25 06:01:00","doi":"10.21203/rs.3.rs-6456602/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":"ed766bae-5235-4be6-bd95-5e9161984e46","owner":[],"postedDate":"April 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47303841,"name":"Health sciences/Signs and symptoms"},{"id":47303842,"name":"Health sciences/Diseases/Neurological disorders"}],"tags":[],"updatedAt":"2025-05-07T04:08:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-25 06:01:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6456602","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6456602","identity":"rs-6456602","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}