Task-Oriented Treadmill Training With Posterior Resistance Improves Gait Speed and Strength-Ground Reaction Force Coupling in Chronic Stroke Survivors: A Randomised Controlled Trial

Task-Oriented Treadmill Training With Posterior Resistance Improves Gait Speed and Strength-Ground Reaction Force Coupling in Chronic Stroke Survivors: A Randomised Controlled Trial | 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 Research Article Task-Oriented Treadmill Training With Posterior Resistance Improves Gait Speed and Strength-Ground Reaction Force Coupling in Chronic Stroke Survivors: A Randomised Controlled Trial Fang-Yu Cheng, Yan-Ting Chen, Sang-I Lin, Hui-Yu Tseng, Pei-Yun Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9242688/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Background Reduced gait speed, impaired ground reaction force (GRF) generation, and lower-limb weakness are common in chronic stroke survivors and contribute to limited functional mobility. While treadmill training improves walking capacity, its effects on propulsion mechanics and the integration of muscle strength with GRFs remain unclear. Posterior pulling resistance may increase propulsive demand during gait and enhance neuromuscular-biomechanical coupling. The purpose of this study was to investigate the effects of task-oriented treadmill training with and without posterior resistance on gait speed, GRFs, lower-limb muscle strength, walking energy expenditure, and the relationships among these variables in individuals with chronic stroke. Methods Forty chronic stroke participants were randomly assigned to conventional treadmill training (CON) or treadmill training with posterior resistance (EXP). Both groups received training for 30 minutes/session, twice weekly for eight weeks. Primary outcomes included preferred and maximum gait speed, bilateral vertical and anterior-posterior GRFs during overground walking, and lower-limb muscle strength. Secondary outcomes included walking energy expenditure (V̇O₂). Multivariate repeated-measures ANOVA was used to assess training effects. Pearson correlation was used to examine associations among gait speed, GRFs, and strength pre- and post-training. Results Both groups demonstrated significant improvements in preferred and maximum gait speed, reduced walking energy expenditure, and increased affected-side knee flexor, knee extensor, and ankle plantarflexor strength (all p < 0.05). A significant between-group difference was observed only for the second vertical GRF peak on the affected side at maximum speed, which increased more in EXP ( p = 0.037). Post-training analyses revealed strengthened correlations between gait speed and affected-side knee extensor and ankle plantarflexor strength, as well as between anterior-posterior GRF and knee extensor strength, suggesting enhanced strength-GRF-speed coupling. Conclusions Task-oriented treadmill training improves walking speed, metabolic efficiency, and the functional integration of lower-limb strength and propulsive mechanics in chronic stroke survivors. Posterior pulling resistance may further augment affected limb loading during high-speed walking. These findings support gait-oriented treadmill training as a core intervention, with resistance as a feasible adjunct to target propulsion deficits. Trial registration: CliniclTrials.gov Protocol Registration: trial number NCT04974840. Chronic stroke Treadmill walking Resistance training Ground reaction force Propulsion Lower-limb strength Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Post-stroke hemiparesis frequently leads to reduced gait speed (1), impaired ground reaction force (GRF) generation (2), and lower limb weakness (3), contributing to mobility limitations (4) and reduced quality of life (5). Among these, gait speed has been widely recognised as a critical marker of functional independence and predictor of long-term outcomes in stroke survivors (6). However, the biomechanical and neuromuscular factors influencing walking performance remain insufficiently understood, particularly in chronic stroke survivors with atypically low gait speed (< 0.8 m/s). GRF, especially its vertical and anterior-posterior components, represents the mechanical output of body-ground interaction during gait and reflects propulsion and support strategies. Abnormal GRF patterns, such as reduced vertical push-off and diminished anterior-posterior propulsion, are common in individuals with stroke (7, 8). These abnormalities are often linked to weakness in key lower-limb muscles, particularly the ankle plantarflexors and knee extensors, which play essential roles in maintaining stance stability and generating forward propulsion during walking (9, 10). While many studies have examined the role of strength or GRF in isolation, relatively few have explored their integrated relationships with gait speed, particularly before and after targeted rehabilitation. A recent systematic review identified knee extensor strength as one of the few modifiable predictors of gait speed in the chronic stroke phase, alongside age and balance capacity (10). However, the authors noted a major limitation in the field: most studies rely solely on unidimensional metrics (e.g., strength, gait speed), with limited integration of kinetic data such as GRF. This gap limits our understanding of how neuromuscular and mechanical factors jointly influence functional recovery. Similarly, Giarmatzis et al. demonstrated that strength training improves gait parameters and variability in chronic stroke survivors, but without examining GRF or its coordination with muscle output (11). Lee et al. further showed that lower limb strength asymmetry, particularly in the knee extensors, predicts gait asymmetry and variability, suggesting a potential mechanistic link between muscle function and gait quality (12). While conventional treadmill training is commonly used to promote walking speed and cardiovascular endurance (13), it often lacks sufficient resistance to drive meaningful improvements in propulsion mechanics and lower-limb strength, especially in individuals with severely impaired gait. Accumulating evidence from a recent systematic review suggests that post-stroke propulsion deficits remain largely unresolved following conventional treadmill training, as improvements in walking speed often rely on compensatory strategies rather than the restoration of paretic propulsive force (14). Similarly, a Cochrane review confirmed gains in walking speed and endurance with treadmill training but noted that improvements in kinetic measures, such as push‑off force or GRF generation, were less reported or modest (15). To address these limitations, task-oriented treadmill training augmented with elastic resistance (e.g., Thera-band) has been proposed conceptually as a strategy to enhance lower-limb propulsion during gait training. When applied as a backward-directed force (e.g., at the pelvis or trunk), the Thera-band may provide an adjustable external force that increases the demand for forward propulsion and encourages greater activation of ankle plantarflexors and knee extensors. This form of resistance potentially simulates real-life functional walking demands without altering treadmill speed or incline, making it particularly appealing for individuals with limited mobility levels. Similar concepts have been explored in orthopaedic and neurologic populations, where resistance-based gait or strength training has shown promising effects on walking efficiency and neuromuscular activation. For instance, functional resistance applied during walking has been shown to alter joint moments, powers, and muscle activation patterns during gait (16). A recent systematic review concluded that resistance training in individuals post-stroke can lead to small-to-moderate improvements in gait speed, especially when applied to the lower limbs (17). However, none of these studies, to our knowledge, have employed elastic posterior resistance at the pelvis or trunk during treadmill training in chronic stroke survivors with impaired propulsion mechanics. Our study represents the first to apply this method in a clinical trial, aiming to address both biomechanical and neuromuscular gaps in current stroke rehabilitation protocols. Therefore, the purpose of this study was twofold: (1) To examine the effects of task-oriented Thera-band resisted treadmill training on gait speed, vertical and anterior-posterior GRF characteristics, and lower-limb muscle strength in chronic stroke survivors with limited walking function; (2) To explore whether the relationships among gait speed, GRF, and muscle strength are modified following the intervention, thereby providing insight into the biomechanical and neuromuscular adaptations that underlie gait improvement in this population. Given that forward propulsion primarily relies on ankle plantarflexors and knee extensors, we particularly examined how these muscle groups correlated with gait speed and GRF following the intervention. Methods This study was a randomised controlled trial that received ethical approval from the Institutional Review Board of the National Cheng Kung University Hospital (protocol number: A-ER-110-027). Additionally, the study was registered with the CliniclTrials.gov Protocol Registration and Results System (trial number NCT04974840). Subjects and Study Design Chronic stroke patients were recruited from the department of rehabilitation and neurology in the hospital. The inclusion criteria were 1) first-time unilateral stroke and onset time over six months, 2) ability to independently walk over 15 meters with or without an assistive device, 3) having apparent gait deficits upon visual inspection by a trained physical therapist or inability in community ambulation, i.e. walking speed < 0.8 m/s, and 4) resting blood pressure lower than 150/90 mmHg. The exclusion criteria were 1) aged over 75 years, 2) inability to understand or follow experimental instructions or procedures, 3) other neurological or musculoskeletal disease affecting walking ability, and 4) having unstable health conditions (medically unstable). A total of 122 individuals with chronic stroke were screened for eligibility. Of these, 40 patients fulfilled the eligibility criteria and agreed to participate. Written consent was obtained from all patients prior to their participation. Demographic characteristics (age, sex, body mass index, affected side, onset duration, and stroke type), and cognitive and sensorimotor function assessment were obtained during the initial evaluation. Primary and secondary outcome measures were examined both before and after the training. Sample size and randomisation Sample size estimation was performed using G*Power 3.1, based on a repeated-measures ANOVA design with a within-between interaction. The calculation assumed a medium effect size (f = 0.25), an alpha level of 0.05, statistical power of 0.80, two groups (experimental and control), and two time points (pre and post), yielding a required total sample size of 34 participants (17 per group). To account for potential attrition, we aimed to recruit 40 participants. After baseline assessments, participants were randomly allocated into either the conventional treadmill training group (CON) or the treadmill training with posterior resistance group (EXP). Randomisation was performed in blocks of 10 using a computer-generated random number list. Group assignment and delivery of the intervention were carried out by the same physical therapist who also conducted the outcome assessments; therefore, assessor blinding was not implemented. Cognitive and Sensorimotor Function Tests All participants completed a battery of cognitive and sensorimotor assessments for sample characterisation. Global cognition was assessed with the Mini-Mental State Examination (MMSE). Lower-limb motor function was quantified using the motor subscale of the Fugl-Meyer Assessment for the lower extremity (FMLE-motor). was employed to evaluate the motor function of the lower limbs. Plantar cutaneous sensation was tested bilaterally at the first metatarsal heads using Semmes–Weinstein monofilaments (Semmes-Weinstein Aesthesiometer, Rolyan, WI, USA). Muscle tone of the paretic lower limb was rated with the Modified Ashworth Scale (MAS). Outcome Measurements The primary outcome measures included gait speed and bilateral GRFs during level walking, as well as bilateral lower extremity muscle strength. Secondary outcome measures focused on energy expenditure during treadmill walking. Gait speed . Walking performance was assessed during level overground walking at both self-selected comfortable and maximum speeds. Participants walked barefoot along the walkway and were allowed to use walking aids as needed. Gait speed was measured using a GAITRite® electronic walkway (CIR Systems, Inc., NJ, USA). Participants initiated and terminated walking two meters before and after the walkway to minimise acceleration and deceleration effects. Two trials were performed at each walking speed, and the average velocity was used for statistical analysis. Ground reaction forces during overground walking . Vertical and anterior-posterior GRF, representing body weight support and forward propulsion, respectively, were measured during level overground walking at both preferred and maximum speeds. Participants walked along a 9-meter walkway with two embedded force platforms (Kistler model 9286AA and 9286BA, Winterthur, Switzerland) positioned in the middle. At least one successful trial in which each foot contacted a force platform was recorded at each speed. Force platform signals were sampled at 1000 Hz and filtered using a fourth-order Butterworth low-pass filter with a cut-off frequency of 10 Hz. GRF data were processed using custom MATLAB algorithms (R2013a, MathWorks, Inc., Natick, MA, USA). For body weight support, the first and second peaks of the vertical GRF (vertical peak 1 and 2) were extracted for both the affected and unaffected limbs. For forward propulsion, the peak anterior-posterior GRF (AP peak) was extracted for each limb. All GRF values were normalised to body weight for statistical analysis. Energy expenditure during walking . Energy expenditure during treadmill walking was assessed by measuring oxygen uptake (V̇O 2 , ml/kg/min) using the Ultima™ CardiO2 ® gas exchange analysis system (Medical Graphics Corp, St. Paul, MN, USA). Participants walked on a treadmill at both preferred and maximum speeds. Walking speed was gradually increased from a low starting speed until the target speed was reached and stabilised. Oxygen uptake was then continuously recorded for five minutes. Participants were allowed to hold the handrails for balance as needed. To evaluate training effects, energy expenditure was assessed at the same preferred and maximum walking speeds before and after the intervention. The average V̇O 2 over the five-minute walking period was used for statistical analysis. Muscle strength of the lower extremities . The maximum isometric strength of bilateral hip flexors, knee flexors, knee extensors, and ankle dorsiflexors was measured using a handheld dynamometer (MicroFET2, HOGGAN Health Industries, UT, USA) following standardised manual muscle testing positions. Bilateral ankle plantarflexor strength was assessed using a standardised manual muscle testing scale based on single-leg heel rise performance (18). Strength grades ranged from 0 (no detectable muscle contraction) to 5 (25 heel rises), with intermediate grades assigned according to established criteria. Intervention Both the EXP and CON groups received training sessions lasting 30 minutes, twice a week, for eight weeks. All training was conducted on a level treadmill under the supervision of a trained physical therapist. Participants continued their routine stroke-related physical therapy throughout the study period. They were informed that the study was comparing two types of treadmill-based gait training but were not told which protocol was expected to be more effective. Thus, they were blinded to group allocation. For both groups, treadmill walking intensity was determined using the Borg category-ratio 10-point scale (CR10; 0–10) (19). At the beginning of each session, participants started walking at a comfortable speed. The treadmill speed was gradually increased until they reported an exertion level of 3–4 on the CR10 scale, corresponding to a “moderate” to “somewhat strong” effort. This is consistent with aerobic exercise recommendations for individuals with stroke (20). The treadmill speed was progressively increased in subsequent sessions as tolerated to maintain this target level of perceived effort. During training, participants walked on the treadmill while wearing a custom-made, non-elastic waist pad connected to two Thera-bands, each attached to either side (Fig. 1 (a)). The Thera-band resistance was quantified using a numerical scale attached to the front of the waist pad and secured to the treadmill handrail. Participants were instructed to maintain a constant position on the treadmill belt. In the EXP group, Thera-band resistance was applied in three directions: directly backwards, 45° towards the paretic side, and 45° towards the non-paretic side (Fig. 1 ). The resistance level started at 1% of body weight and was gradually increased to a level corresponding to “almost moderately more effort” during walking. The resistance was further progressed across sessions as tolerated. Participants walked for five minutes in each resistance direction in a random order, and repeated twice, with rest periods allowed between blocks as needed. In the CON group, the Thera-band setup was identical to that of the EXP group, but no resistance was applied. Participants completed six five-minute walking blocks, with rest periods permitted between blocks as needed. Statistical Analysis For demographic characteristics, between-group comparisons were performed using independent t tests, Mann-Whitney U tests, and chi -square tests for continuous, ordinal, and categorical variables, respectively. Training effects on gait speed, GRF, walking energy expenditure, and lower extremity muscle strength were analysed using multivariate repeated-measures ANOVA (MANOVA). All randomised participants were included in the MANOVA according to their original group assignment using an intention-to-treat approach, with missing values imputed using the last observation carried forward method. Pearson correlation was used to assess pairwise associations among gait speed, GRF, and muscle strength by pooling data from both groups before and after training. The significance level was set at p < 0.05. Results Forty individuals with chronic stroke participated in the training program. Two participants from each group withdrew from the study (Figure 2). Demographic Characteristics Table 1 summarises the basic characteristics of the two groups. No significant differences were found between the two groups concerning age, sex, duration since stroke onset, side of the stroke, MMSE, FMLE-motor scores, both affected and unaffected plantar sensation, or MAS scores for the affected hip adductors, hip flexors, knee extensors, ankle dorsiflexors, and ankle plantarflexors at the baseline assessment. For other outcome measures, there were no significant differences between the two groups, except for the unaffected hip flexor strength, which was significantly greater in the EXP compared to the CON ( p =0.043). Training characteristics Both groups completed the planned 8-week treadmill training with a similar progression of treadmill speed. The average increase in training speed did not differ significantly between groups (EXP: 0.29 ± 0.17 m/s; CON: 0.33 ± 0.15 m/s; p =0.488), supporting that overall walking speed progression during the intervention was comparable across protocols. In addition, only the EXP group trained with posterior elastic resistance, which was progressively increased across sessions (mean change: 1.64 ± 0.86 kg, corresponding to 2.22 ± 1.15% of body weight), whereas the CON group walked without external resistance. Walking Performance Significant time effects were observed in both preferred and maximum gait speeds and in energy expenditure (Table 2). Both groups improved post-training. However, only one between-group difference was observed: the EXP group had significantly higher second vertical GRF peak on the affected side under maximum speed ( p =0.037). No other GRF parameters showed significant group or interaction effects. Lower Extremity Muscle Strength Both groups showed significant improvements post-training in the affected-side knee flexors ( p =0.008), knee extensors ( p =0.013), and ankle plantarflexors ( p =0.029) (Table 3). No significant group differences or interactions were observed. Correlations between Gait Speed, GRF, and Muscle Strength Before training, preferred gait speed showed significant correlations with the AP peak GRF on the affected side (r=0.356, p =0.024), and with affected-side ankle plantarflexor strength (r=0.389, p =0.013) (Table 4). No significant associations were found between AP peak GRF and lower-limb strength. Importantly, correlations between gait speed and affected-side knee extensor (r=0.377, p =0.023) and ankle plantarflexor strength (r=0.485, p =0.003) became evident post-training, suggesting a stronger linkage between walking performance and key propulsive muscle groups following the intervention. AP peak GRF also became significantly associated with affected-side knee extensor strength (r=0.333, p =0.047), a relationship not present before training (Figure 3). For maximum gait speed, significant pre-training correlations were found with the AP peak GRF on the affected side (r=0.490, p =0.001), as well as with affected-side ankle plantarflexor strength (r=0.436, p =0.005) (Table 4). After training, these relationships strengthened: the AP peak GRF remained significantly correlated on the affected side (r=0.522, p =0.001), and the correlation with ankle plantarflexor strength increased further (r=0.555, p <0.001). In addition, the association with affected-side knee extensor strength shifted from a non-significant trend pre-training (r=0.117, p =0.471) to a significant correlation post-training (r=0.394, p =0.017) (Figure 4). Table 1. Demographic characteristics EXP group (n=20) CON group (n=20) p Age (years) 55.0±10.0 57.8±10.3 0.39 Sex (female/male) ¶ 6/14 8/12 0.51 BMI 26.26±5.,29 25.78±4.55 0.76 Stroke Affected side (right/left) ¶ 12/8 9/11 0.34 Onset duration (months) 38.4±22.0 39.6±42.9 0.91 MMSE 28.6±1.6 28.0±1.7 0.21 FMLE-motor 20.2±5.6 21.6±4.8 0.42 Plantar sensitivity big toe (dB) Affected side 4.63±0.71 4.90±0.98 0.46 Non-affected side 4.26±0.43 4.41±0.58 0.24 Modified Ashworth scale (mean/median/mode) # Hip adductors 0.3/0/0 0.3/0/0 1.00 Hip flexors 0.2/0/0 0.1/0/0 0.38 Knee extensors 0.3/0/0 0.3/0/0 0.93 Ankle dorsiflexor 0.8/0.5/0 0.4/0/0 0.21 Ankle plantarflexor 0.8/0.5/0 0.6/1/0 0.89 BMI: Body Mass Index; MMSE: Mini-Mental Status Examination; FMLE-motor: Fugl-Meyer lower limb motor scale ¶ Between group comparisons using χ 2 tests. # Between group comparisons using Mann-Whitney U tests. Table 2. Walking performance at preferred and maximum walking speed Preferred speed Maximum speed EXP group (n=20) CON group (n=20) EXP group (n=20) CON group (n=20) Pre Post Pre Post Pre Post Pre Post Gait speed (m/s) 0.58±0.23 0.61±0.21* 0.59±0.31 0.67±0.33* 0.78±0.30 0.81±0.26* 0.81±0.42 0.93±0.43* Ground reaction force (%BW) Vertical peak 1 Affected 98.98±11.38 100.18±8.51 99.00±9.14 100.28±8.55 102.34±9.90 103.60±13.63 103.15±18.79 100.88±16.38 Unaffected 97.36±10.82 99.02±6.85 102.59±14.34 100.27±14.98 101.97±11.66 102.61±12.36 105.91±13.44 106.24±13.22 Vertical peak 2 Affected 99.18±13.31 98.68±8.56 97.87±8.81 95.87±10.36 100.49±11.76 101.23±10.41 93.23±12.78 96.75±11.82† Unaffected 97.52±10.71 102.87±7.53 100.67±10.74 101.90±7.74 97.69±13.25 101.84±6.02 103.98±8.59 102.00±9.60 AP peak Affected 6.72±3.75 8.22±3.40 7.93±3.58 7.56±3.15 9.81±5.64 10.73±5.80 10.20±5.49 9.90±6.44 Unaffected 9.78±5.40 11.01±5.50 11.90±4.30 11.59±4.03 12.69±5.66 13.99±5.51 13.69±8.26 14.07±8.55 Energy expenditure (ml/kg/min) 9.00±1.91 8.33±1.64* 9.24±2.24 8.73±2.18* 10.01±2.28 8.92±1.86* 10.68±2.63 9.28±2.47* BW: body weight; *Significant time main effects; †Significant group main effects Table 3. Lower extremity muscle strength EXP group (n=20) CON group (n=20) Pre Post Pre Post Hip flexors Affected 7.55±3.11 7.62±2.95 6.79±3.55 7.69±3.05 Unaffected 12.37±3.20 12.31±3.16 10.26±3.16 10.54±3.19 Knee flexors Affected 5.03±2.61* 6.19±3.51* 4.93±2.73* 5.78±3.15* Unaffected 10.28±3.19* 13.03±4.64* 9.83±2.67* 11.18±3.80* Knee extensors Affected 7.99±2.97* 10.20±4.90* 7.20±2.89* 8.30±4.28* Unaffected 11.66±3.07 13.51±5.00 10.77±3.85 11.19±4.61 Ankle dorsiflexors Affected 5.69±3.56 6.08±2.95 6.03±3.60 7.00±3.02 Unaffected 10.63±4.36 11.22±3.99 9.95±2.28 10.93±3.37 Ankle plantarflexors Affected 2.55±1.00* 2.85±1.09* 2.55±1.05* 2.85±0.93* Unaffected 4.15±0.67 4.40±0.60 4.15±0.81 4.25±0.85 Unit: kg; *Significant time main effects Table 4. Correlations among gait speed, AP peak GRF, and affected-side muscle strength in both conditions. Preferred speed condition Maximum speed condition Gait speed Gait speed Pre (n=40) Post (n=36) Pre (n=40) Post (n=36) r p r p r p r p AP peak GRF 0.356 0.024* 0.291 0.085 0.490 0.001* 0.522 0.001* Knee extensors 0.184 0.246 0.377 0.023* 0.194 0.230 0.322 0.056 Ankle plantarflexors 0.389 0.013* 0.485 0.003* 0.436 0.005* 0.555 <0.001* AP peak GRF AP peak GRF Pre (n=40) Post (n=36) Pre (n=40) Post (n=36) r p r p r p r p Knee extensors 0.242 0.133 0.333 0.047* 0.117 0.471 0.394 0.017* Ankle plantarflexors 0.056 0.733 0.221 0.195 0.280 0.080 0.258 0.129 *Significant correlation between the two variables Discussion This study examined the effects of task-oriented treadmill training, with or without additional posterior pelvic elastic resistance, on walking performance, GRFs, lower limb muscle strength, and their interrelationships in individuals with chronic stroke and limited walking ability. Both training protocols led to significant improvements in gait speed, walking energy expenditure, and selected GRF variables, confirming that intensive gait‑focused training remains beneficial even in individuals with relatively slow walking speeds. Compared with conventional treadmill training, the experimental intervention produced a larger increase in the second vertical GRF peak on the affected side at maximum walking speed. Furthermore, when data from both groups were pooled, post‑training correlations showed stronger associations among walking speed, affected knee extensor and ankle plantarflexor strength, and AP GRF peaks. These findings suggest that treadmill‑based gait training as a whole can enhance the coupling between neuromuscular capacity, propulsive forces, and functional walking performance. We hypothesised that adding posterior pelvic elastic resistance would augment paretic limb propulsion, yield greater improvements in speed and efficiency, and alter the relationships among walking speed, GRFs, and muscle strength. The results partially support these hypotheses. First, regardless of group allocation, participants increased preferred and maximum walking speed and reduced walking energy expenditure. Importantly, the increase in treadmill training speed over the 8-week intervention did not differ significantly between groups, indicating that both protocols provided a comparable amount of speed-progressive, task-oriented walking practice. These findings align with recent studies showing that repetitive, task‑oriented gait training and high‑intensity treadmill programs can improve walking capacity and metabolic efficiency in chronic stroke. For example, randomised treadmill aerobic training has been shown to enhance walking endurance and cardiorespiratory fitness with concurrent reductions in oxidative stress (21), while performance-based high-intensity treadmill interventions yield superior gains in walking speed, endurance, and balance that persist beyond the training period (22). Such evidence reinforces the role of structured, gait-centred interventions as a core component of stroke rehabilitation, consistent with current clinical guidelines and recent systematic reviews (23, 24). Second, at maximum overground speed, only the EXP group showed a greater increase in the second vertical GRF peak on the affected side than the CON group. Given that the increase in treadmill speed during training was similar for both groups, this group difference in late-stance vertical GRF is likely attributable to the additional posterior resistance rather than to greater exposure to faster walking per se. This pattern suggests that posterior elastic resistance may facilitate enhanced paretic limb loading and vertical support during late stance under high-demand conditions. Recent work on propulsion‑oriented gait training similarly emphasises the importance of challenging the paretic limb to bear load and generate push‑off, especially when training at faster speeds (25). Taken together, these findings support the notion that augmenting intensity-matched, task-specific gait practice with targeted posterior resistance may further promote functional propulsion capacity in chronic stroke, particularly during faster or more demanding walking. Walking speed after stroke is closely related to lower-limb strength, particularly knee extensors and ankle plantarflexors, and to propulsion mechanics reflected by GRF, especially the anterior-posterior component. Therefore, changes in the strength-GRF-speed relationships can provide mechanistic insight into whether training improves not only isolated capacities but also their functional integration during gait (9, 10). Before training, the relationships among strength, GRFs, and speed were relatively weak, implying inability in using the existing lower limb strength to generate appropriate propulsive forces. After the training period, the stronger, more systematic correlations suggest that participants not only improved in isolated capacities, but also in how these capacities were integrated during gait. These emerging correlations may reflect a more efficient integration of available neuromuscular resources during gait, whereby key antigravity and propulsive muscles are recruited in a more phase-appropriate manner to support functional walking. This interpretation aligns with current motor control and neurorehabilitation frameworks emphasising improved coordination and resource allocation rather than isolated capacity gains alone (26, 27). Importantly, these reorganised correlations were observed when data from both groups were pooled, implying that intensive treadmill‑based gait training in general, regardless of the presence of elastic resistance, can promote more efficient coordination between neuromuscular output and biomechanical function. Recent literature similarly reports that high‑repetition, task‑oriented gait training can refine muscle activation timing and inter‑segmental coordination (28). Overall, these findings suggest that intensive, task‑oriented treadmill training primarily enhances the coordination and functional use of existing neuromuscular resources, rather than strength alone, by promoting more efficient, phase‑appropriate recruitment of key muscles during gait. Clinically, these findings suggest that even in individuals with chronic stroke who walk at speeds below 0.8 m/s, a structured task‑oriented treadmill program can still yield meaningful gains in gait speed and reductions in the walking energy expenditure. This indicates that higher‑intensity, task‑specific gait training is feasible and beneficial not only for higher‑functioning stroke survivors but also for those with more severe walking limitations, thereby supporting the inclusion of treadmill‑based protocols in routine practice, including in resource‑limited settings (27). The additional posterior pelvic elastic resistance did not produce uniformly superior outcomes across all variables, but it did lead to greater improvement in the paretic second vertical GRF peak at maximum speed. For patients who can safely tolerate higher training demands, elastic resistance may therefore be considered as an adjunct to amplify mechanical loading of the paretic limb and encourage more symmetrical, propulsive late‑stance behaviour. Recent studies on resistance‑augmented gait training (29) and speed‑dependent treadmill intervention (30) suggest that such targeted loading strategies can be particularly useful for addressing persistent propulsion deficits. From a practical standpoint, elastic bands and simple harness systems are low‑cost, widely available, and easily adjustable to individual capacity. Combining them with treadmill training offers a feasible method to increase training intensity and specificity. Several limitations should be acknowledged. The sample size, while comparable to that of similar trials, may have been underpowered to detect small‑to‑moderate between‑group effects. Future studies should recruit larger cohorts and consider multicenter designs to enhance statistical power and generalizability. Second, only short‑term pre‑ to post‑intervention effects were assessed. We did not evaluate whether the improvements in walking performance and the strengthened coupling among strength, GRFs, and speed are maintained over time or translate into better community ambulation and participation. Long‑term follow‑up and the use of wearable sensors to monitor real‑world walking are recommended in future research. Finally, although the magnitude of posterior elastic resistance was recorded and progressively increased within a target perceived-exertion range, the study was not designed to systematically compare different resistance doses or directions. As a result, dose-response relationships remain unclear. Future studies should systematically vary resistance magnitude, direction, and progression to identify optimal dosing parameters and the patient subgroups most likely to benefit. Conclusions In summary, task‑oriented treadmill training improved walking speed, reduced energy expenditure, and enhanced the functional coupling among lower limb strength, GRFs, and gait performance in individuals with chronic stroke and limited walking ability. Adding posterior pelvic elastic resistance further increased paretic vertical loading during late stance at maximum walking speed, although most clinical and biomechanical outcomes improved similarly in both groups. These findings support the use of intensive, gait‑oriented treadmill training as a core intervention in chronic stroke rehabilitation and suggest that posterior elastic resistance may serve as a useful adjunct for targeting paretic limb loading and propulsion. Future larger, multimodal, and longer‑term studies are warranted to refine the role and dosing of resistance‑augmented treadmill training in this population. Abbreviations ANOVA analysis of variance AP anterior-posterior CON conventional treadmill training group CR10 Borg category-ratio 10-point scale EXP treadmill training with posterior resistance group FMLE-motor Fugl-Meyer Assessment for the lower extremity GRF ground reaction force MANOVA multivariate repeated-measures analysis of variance MAS Modified Ashworth Scale MMSE Mini-Mental State Examination Declarations Ethics approval and consent to participate: Ethical approval was obtained from the Institutional Review Board of the National Cheng Kung University Hospital (protocol number: A-ER-110-027), and all participants provided consent prior to participation. Consent for publication: Not applicable. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution FYC – conceptualisation, formal analysis, manuscript preparation; YTC – research design, data collection, formal analysis, manuscript preparation; SIL – conceptualization, research design, data collection, formal analysis, project administration, supervision, manuscript preparation; HYT – data collection, formal analysis, manuscript preparation; PYL – conceptualisation, research design, data collection, formal analysis, computer programming, project administration, supervision, manuscript preparation. All authors read and approved the final manuscript. Acknowledgement The authors express gratitude to Yu-Ying Chen, Li-Yu Lin and Ting-Yuan Huang for their assistance with participant recruitment and data collection. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Tasseel-Ponche S, Delafontaine A, Godefroy O, Yelnik AP, Doutrellot PL, Duchossoy C, et al. Walking speed at the acute and subacute stroke stage: A descriptive meta-analysis. Frontiers in neurology. 2022;13:989622. Hsiao H, Awad LN, Palmer JA, Higginson JS, Binder-Macleod SA. Contribution of Paretic and Nonparetic Limb Peak Propulsive Forces to Changes in Walking Speed in Individuals Poststroke. Neurorehabilitation and neural repair. 2016;30(8):743 − 52. Aguiar LT, Camargo LBA, Estarlino LD, Teixeira-Salmela LF, Faria C. Strength of the lower limb and trunk muscles is associated with gait speed in individuals with sub-acute stroke: a cross-sectional study. Braz J Phys Ther. 2018;22(6):459 − 66. Rossler R, Bridenbaugh SA, Engelter ST, Weibel R, Infanger D, Giannouli E, et al. Recovery of mobility function and life-space mobility after ischemic stroke: the MOBITEC-Stroke study protocol. BMC neurology. 2020;20(1):348. Butsing N, Tipayamongkholgul M, Wang JD, Ratanakorn D. Combined quality of life and survival for estimation of long-term health outcome of patients with stroke. Health Qual Life Outcomes. 2022;20(1):46. Li N, Zhang J, Du Y, Li J, Wang A, Zhao X. Gait speed after mild stroke/transient ischemic attack was associated with long-term adverse outcomes: A cohort study. Ann Clin Transl Neurol. 2024;11(12):3163-74. Lee DH, Chang WN, Jeon HJ. Comparison of ground reaction force during gait between the nonparetic side in hemiparetic patients and the dominant side in healthy subjects. Journal of exercise rehabilitation. 2020;16(4):344 − 50. Mazzoli D, Basini G, Prati P, Galletti M, Mascioli F, Rambelli C, et al. Indices of Loading and Propulsive Ability in the Gait of Patients With Chronic Stroke With Equinus Foot Deviation: A Correlation Study. Frontiers in human neuroscience. 2021;15:771392. Awad LN, Hsiao H, Binder-Macleod SA. Central Drive to the Paretic Ankle Plantarflexors Affects the Relationship Between Propulsion and Walking Speed After Stroke. Journal of neurologic physical therapy : JNPT. 2020;44(1):42 − 8. Jasper AM, Lazaro RT, Mehta SP, Perry LA, Swanson K, Reedy K, et al. Predictors of gait speed post-stroke: A systematic review and meta-analysis. Gait Posture. 2025;121:70 − 7. Giarmatzis G, Giannakou E, Karagiannakidou I, Makri E, Tsiakiri A, Christidi F, et al. Effects of a 12-Week Moderate-to-High Intensity Strength Training Program on the Gait Parameters and Their Variability of Stroke Survivors. Brain Sci. 2025;15(4). Lee Y, Kim GB, Shin S. Association Between Lower Limb Strength Asymmetry and Gait Asymmetry: Implications for Gait Variability in Stroke Survivors. Journal of clinical medicine. 2025;14(2):380. Shi C, Xiao Y, Zang D, Ren H. Effectiveness of Treadmill Training Intervention for the Management of Patients With Stroke: A Systematic Review and Meta-Analysis. Int J Nurs Pract. 2025;31(3):e70020. Alingh JF, Groen BE, Van Asseldonk EHF, Geurts ACH, Weerdesteyn V. Effectiveness of rehabilitation interventions to improve paretic propulsion in individuals with stroke - A systematic review. Clin Biomech (Bristol). 2020;71:176 − 88. Mehrholz J, Thomas S, Elsner B. Treadmill training and body weight support for walking after stroke. Cochrane Database Syst Rev. 2017;8(8):CD002840. Washabaugh EP, Augenstein TE, Krishnan C. Functional resistance training during walking: Mode of application differentially affects gait biomechanics and muscle activation patterns. Gait Posture. 2020;75:129 − 36. Lerin-Calvo A, Carrasco-Gonzalez E, Reina-Varona A, Fernandez-Perez JJ. Resistance training for gait rehabilitation in people with stroke. A systematic review and meta-analysis. Disability and rehabilitation. 2026;48(2):331 − 49. Marybeth Brown DA. Daniels and Worthingham's Muscle Testing. Techniques of Manual Examination and Performance Testing. 10th ed: Saunders: Elsevier Inc.; 2019. Borg G. Borg's perceived exertion and pain scales. Champaign, IL, US: Human Kinetics; 1998. viii, 104-viii, p. Billinger SA, Arena R, Bernhardt J, Eng JJ, Franklin BA, Johnson CM, et al. Physical activity and exercise recommendations for stroke survivors: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014;45(8):2532-53. Serra MC, Hafer-Macko CE, Robbins R, O'Connor JC, Ryan AS. Randomization to Treadmill Training Improves Physical and Metabolic Health in Association With Declines in Oxidative Stress in Stroke. Archives of physical medicine and rehabilitation. 2022;103(11):2077-84. Lee H-J, Oh D-w. Exploring the impact of performance-based high-intensity treadmill training in chronic stroke patients: a group-matched, single-blind pilot trial with a 3-month follow-up. Physiotherapy Quarterly. 2025. Moore SA, Boyne P, Fulk G, Verheyden G, Fini NA. Walk the Talk: Current Evidence for Walking Recovery After Stroke, Future Pathways and a Mission for Research and Clinical Practice. Stroke; a journal of cerebral circulation. 2022;53(11):3494 − 505. Baricich A, Borg MB, Battaglia M, Facciorusso S, Spina S, Invernizzi M, et al. High-Intensity Exercise Training Impact on Cardiorespiratory Fitness, Gait Ability, and Balance in Stroke Survivors: A Systematic Review and Meta-Analysis. Journal of clinical medicine. 2024;13(18). Alingh JF, Groen BE, Kamphuis JF, Geurts ACH, Weerdesteyn V. Task-specific training for improving propulsion symmetry and gait speed in people in the chronic phase after stroke: a proof-of-concept study. Journal of neuroengineering and rehabilitation. 2021;18(1):69. Belda-Lois JM, Mena-del Horno S, Bermejo-Bosch I, Moreno JC, Pons JL, Farina D, et al. Rehabilitation of gait after stroke: a review towards a top-down approach. Journal of neuroengineering and rehabilitation. 2011;8:66. Teodoro J, Fernandes S, Castro C, Fernandes JB. Current Trends in Gait Rehabilitation for Stroke Survivors: A Scoping Review of Randomized Controlled Trials. Journal of clinical medicine. 2024;13(5):1358. Lee J, Kim K, Cho Y, Kim H. Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research. Neurol Int. 2024;16(6):1451-63. Swaminathan K, Porciuncula F, Park S, Kannan H, Erard J, Wendel N, et al. Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke. Journal of neuroengineering and rehabilitation. 2023;20(1):85. Hu J, Jin L, Wang Y, Shen X. Feasibility of challenging treadmill speed-dependent gait and perturbation-induced balance training in chronic stroke patients with low ambulation ability: a randomized controlled trial. Frontiers in neurology. 2023;14:1167261. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 14 May, 2026 Reviews received at journal 14 May, 2026 Reviews received at journal 13 May, 2026 Reviews received at journal 10 May, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor assigned by journal 30 Mar, 2026 Submission checks completed at journal 30 Mar, 2026 First submitted to journal 27 Mar, 2026 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9242688","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627345970,"identity":"8f8e4b83-6ee6-42d6-b8ac-cea7be06e12d","order_by":0,"name":"Fang-Yu Cheng","email":"","orcid":"","institution":"MacKay Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fang-Yu","middleName":"","lastName":"Cheng","suffix":""},{"id":627345971,"identity":"f3b7c0b8-68b8-4da8-94e5-831f1eb8d986","order_by":1,"name":"Yan-Ting Chen","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Yan-Ting","middleName":"","lastName":"Chen","suffix":""},{"id":627345972,"identity":"f12ebcbf-6ef5-49d6-83a2-e17217f40132","order_by":2,"name":"Sang-I Lin","email":"","orcid":"","institution":"MacKay Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sang-I","middleName":"","lastName":"Lin","suffix":""},{"id":627345973,"identity":"67a640a1-b7ee-4162-812c-d310285c7d7b","order_by":3,"name":"Hui-Yu Tseng","email":"","orcid":"","institution":"Tainan Hospital, Ministry of Health and Welfare","correspondingAuthor":false,"prefix":"","firstName":"Hui-Yu","middleName":"","lastName":"Tseng","suffix":""},{"id":627345974,"identity":"2005a128-e09b-45a6-883e-c667e2bb63b1","order_by":4,"name":"Pei-Yun Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYFACxgYgYcHAwA6kEwqAbB6QKBtBLRJAlQeAWgyQtPDgtwqoRSIBSBOjxZy9uU2ad4eEHL/k68QPDwwY8vh7zhgwfCg7zGAPNgQTWPYcBGo5I2EsOTt3swTQYcUSZ3sMGGecO8zAg0OLwY1EoJY2icQNt3M3gLQkbuDnMWDmbQNqkcah5f5DsJb6/TfPbv4B1/IXn5YbjGAtCQYSvNsgtvD2GDAz4tFi2ZPYbDm3TcJwxpncbRZAjYkzzhwrONhzLp2H5/4DHCF2/OGNt2028vztZzff/FFhk9jfk7zxwY8yazn2ngPYHcbAwCKBxIewQWpxxiRQC/MHXJKjYBSMglEwCsAAACFMWJ92rIf7AAAAAElFTkSuQmCC","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":true,"prefix":"","firstName":"Pei-Yun","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2026-03-27 09:10:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9242688/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9242688/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107949014,"identity":"56d46702-1211-456b-a55f-fce8698f1488","added_by":"auto","created_at":"2026-04-28 00:24:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":451909,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagrams of treadmill walking training. A custom-made, non-elastic waist pad was worn and connected to two Thera-bands, one attached to each side. The Thera-band resistance was applied in three directions: (a) directly backwards, (b) at a 45° angle towards the paretic side, and (c) at a 45° angle towards the non-paretic side.\u003c/p\u003e","description":"","filename":"floatimage117.png","url":"https://assets-eu.researchsquare.com/files/rs-9242688/v1/2a244ed0f1d8433fdffbff98.png"},{"id":107949022,"identity":"d4f335e0-471e-46e0-b439-492c4447c794","added_by":"auto","created_at":"2026-04-28 00:24:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":187458,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow chart.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9242688/v1/8df0bfeb73041812bdb08bea.png"},{"id":107949015,"identity":"b9647060-c6aa-42bd-a08c-78c506b27b0d","added_by":"auto","created_at":"2026-04-28 00:24:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70802,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between affected-side muscle strength, AP peak ground reaction force (GRF), and preferred gait speed before and after training.\u003c/p\u003e\n\u003cp\u003e(a) Pre-training: Weak to moderate correlations were found between muscle strength and both AP peak GRF (r=0.056-0.242) and preferred gait speed (r=0.184-0.389). The AP peak GRF was also modestly correlated with gait speed (r=0.356).\u003c/p\u003e\n\u003cp\u003e(b) Post-training: Correlations between muscle strength and both AP peak GRF (r=0.221-0.333) and gait speed (r=0.377-0.485) increased after training. However, the correlation between AP peak GRF and gait speed slightly decreased (r=0.291).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBold arrows\u003c/strong\u003e indicate strengthened correlations following the intervention.\u003c/p\u003e","description":"","filename":"floatimage34.png","url":"https://assets-eu.researchsquare.com/files/rs-9242688/v1/677a6d1b3da9c0f8dcc7baa6.png"},{"id":107949023,"identity":"7707dfc7-17dd-4d34-80ae-0f237de85a52","added_by":"auto","created_at":"2026-04-28 00:24:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":70987,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between affected-side muscle strength, AP peak ground reaction force (GRF), and maximum gait speed before and after training.\u003c/p\u003e\n\u003cp\u003e(a) Pre-training: Significant correlations were observed between maximum gait speed and AP peak GRF (r=0.490), as well as ankle plantarflexor strength (r=0.436). Correlations between muscle strength and AP peak GRF were weak to moderate (r=0.117-0.280).\u003c/p\u003e\n\u003cp\u003e(b) Post-training: Stronger associations were observed after the intervention. Maximum gait speed remained correlated with AP peak GRF (r=0.522), and the correlation with ankle plantarflexor strength increased (r=0.555). Additionally, moderate correlations emerged between muscle strength and AP peak GRF (r=0.258-0.394).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBold arrows\u003c/strong\u003e represent pathways where correlation strength increased after training.\u003c/p\u003e","description":"","filename":"floatimage42.png","url":"https://assets-eu.researchsquare.com/files/rs-9242688/v1/c14a2695ee6faa37d17c8877.png"},{"id":107949055,"identity":"2479b7f9-4fd3-4a9b-b677-57e159019d58","added_by":"auto","created_at":"2026-04-28 00:24:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1161431,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9242688/v1/ad2dc2df-3438-4f3a-984d-dda97b455afe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Task-Oriented Treadmill Training With Posterior Resistance Improves Gait Speed and Strength-Ground Reaction Force Coupling in Chronic Stroke Survivors: A Randomised Controlled Trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePost-stroke hemiparesis frequently leads to reduced gait speed (1), impaired ground reaction force (GRF) generation (2), and lower limb weakness (3), contributing to mobility limitations (4) and reduced quality of life (5). Among these, gait speed has been widely recognised as a critical marker of functional independence and predictor of long-term outcomes in stroke survivors (6). However, the biomechanical and neuromuscular factors influencing walking performance remain insufficiently understood, particularly in chronic stroke survivors with atypically low gait speed (\u0026lt;\u0026thinsp;0.8 m/s).\u003c/p\u003e \u003cp\u003eGRF, especially its vertical and anterior-posterior components, represents the mechanical output of body-ground interaction during gait and reflects propulsion and support strategies. Abnormal GRF patterns, such as reduced vertical push-off and diminished anterior-posterior propulsion, are common in individuals with stroke (7, 8). These abnormalities are often linked to weakness in key lower-limb muscles, particularly the ankle plantarflexors and knee extensors, which play essential roles in maintaining stance stability and generating forward propulsion during walking (9, 10). While many studies have examined the role of strength or GRF in isolation, relatively few have explored their integrated relationships with gait speed, particularly before and after targeted rehabilitation. A recent systematic review identified knee extensor strength as one of the few modifiable predictors of gait speed in the chronic stroke phase, alongside age and balance capacity (10). However, the authors noted a major limitation in the field: most studies rely solely on unidimensional metrics (e.g., strength, gait speed), with limited integration of kinetic data such as GRF. This gap limits our understanding of how neuromuscular and mechanical factors jointly influence functional recovery. Similarly, Giarmatzis \u003cem\u003eet al.\u003c/em\u003e demonstrated that strength training improves gait parameters and variability in chronic stroke survivors, but without examining GRF or its coordination with muscle output (11). Lee \u003cem\u003eet al.\u003c/em\u003e further showed that lower limb strength asymmetry, particularly in the knee extensors, predicts gait asymmetry and variability, suggesting a potential mechanistic link between muscle function and gait quality (12).\u003c/p\u003e \u003cp\u003eWhile conventional treadmill training is commonly used to promote walking speed and cardiovascular endurance (13), it often lacks sufficient resistance to drive meaningful improvements in propulsion mechanics and lower-limb strength, especially in individuals with severely impaired gait. Accumulating evidence from a recent systematic review suggests that post-stroke propulsion deficits remain largely unresolved following conventional treadmill training, as improvements in walking speed often rely on compensatory strategies rather than the restoration of paretic propulsive force (14). Similarly, a Cochrane review confirmed gains in walking speed and endurance with treadmill training but noted that improvements in kinetic measures, such as push‑off force or GRF generation, were less reported or modest (15).\u0026ensp;To address these limitations, task-oriented treadmill training augmented with elastic resistance (e.g., Thera-band) has been proposed conceptually as a strategy to enhance lower-limb propulsion during gait training. When applied as a backward-directed force (e.g., at the pelvis or trunk), the Thera-band may provide an adjustable external force that increases the demand for forward propulsion and encourages greater activation of ankle plantarflexors and knee extensors. This form of resistance potentially simulates real-life functional walking demands without altering treadmill speed or incline, making it particularly appealing for individuals with limited mobility levels.\u003c/p\u003e \u003cp\u003eSimilar concepts have been explored in orthopaedic and neurologic populations, where resistance-based gait or strength training has shown promising effects on walking efficiency and neuromuscular activation. For instance, functional resistance applied during walking has been shown to alter joint moments, powers, and muscle activation patterns during gait (16). A recent systematic review concluded that resistance training in individuals post-stroke can lead to small-to-moderate improvements in gait speed, especially when applied to the lower limbs (17). However, none of these studies, to our knowledge, have employed elastic posterior resistance at the pelvis or trunk during treadmill training in chronic stroke survivors with impaired propulsion mechanics. Our study represents the first to apply this method in a clinical trial, aiming to address both biomechanical and neuromuscular gaps in current stroke rehabilitation protocols. Therefore, the purpose of this study was twofold: (1) To examine the effects of task-oriented Thera-band resisted treadmill training on gait speed, vertical and anterior-posterior GRF characteristics, and lower-limb muscle strength in chronic stroke survivors with limited walking function; (2) To explore whether the relationships among gait speed, GRF, and muscle strength are modified following the intervention, thereby providing insight into the biomechanical and neuromuscular adaptations that underlie gait improvement in this population. Given that forward propulsion primarily relies on ankle plantarflexors and knee extensors, we particularly examined how these muscle groups correlated with gait speed and GRF following the intervention.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e This study was a randomised controlled trial that received ethical approval from the Institutional Review Board of the National Cheng Kung University Hospital (protocol number: A-ER-110-027). Additionally, the study was registered with the CliniclTrials.gov Protocol Registration and Results System (trial number NCT04974840).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects and Study Design\u003c/h2\u003e \u003cp\u003eChronic stroke patients were recruited from the department of rehabilitation and neurology in the hospital. The inclusion criteria were 1) first-time unilateral stroke and onset time over six months, 2) ability to independently walk over 15 meters with or without an assistive device, 3) having apparent gait deficits upon visual inspection by a trained physical therapist or inability in community ambulation, i.e. walking speed\u0026thinsp;\u0026lt;\u0026thinsp;0.8 m/s, and 4) resting blood pressure lower than 150/90 mmHg. The exclusion criteria were 1) aged over 75 years, 2) inability to understand or follow experimental instructions or procedures, 3) other neurological or musculoskeletal disease affecting walking ability, and 4) having unstable health conditions (medically unstable).\u003c/p\u003e \u003cp\u003eA total of 122 individuals with chronic stroke were screened for eligibility. Of these, 40 patients fulfilled the eligibility criteria and agreed to participate. Written consent was obtained from all patients prior to their participation. Demographic characteristics (age, sex, body mass index, affected side, onset duration, and stroke type), and cognitive and sensorimotor function assessment were obtained during the initial evaluation. Primary and secondary outcome measures were examined both before and after the training.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample size and randomisation\u003c/h3\u003e\n\u003cp\u003eSample size estimation was performed using G*Power 3.1, based on a repeated-measures ANOVA design with a within-between interaction. The calculation assumed a medium effect size (f\u0026thinsp;=\u0026thinsp;0.25), an alpha level of 0.05, statistical power of 0.80, two groups (experimental and control), and two time points (pre and post), yielding a required total sample size of 34 participants (17 per group). To account for potential attrition, we aimed to recruit 40 participants. After baseline assessments, participants were randomly allocated into either the conventional treadmill training group (CON) or the treadmill training with posterior resistance group (EXP). Randomisation was performed in blocks of 10 using a computer-generated random number list. Group assignment and delivery of the intervention were carried out by the same physical therapist who also conducted the outcome assessments; therefore, assessor blinding was not implemented.\u003c/p\u003e\n\u003ch3\u003eCognitive and Sensorimotor Function Tests\u003c/h3\u003e\n\u003cp\u003eAll participants completed a battery of cognitive and sensorimotor assessments for sample characterisation. Global cognition was assessed with the Mini-Mental State Examination (MMSE). Lower-limb motor function was quantified using the motor subscale of the Fugl-Meyer Assessment for the lower extremity (FMLE-motor). was employed to evaluate the motor function of the lower limbs. Plantar cutaneous sensation was tested bilaterally at the first metatarsal heads using Semmes\u0026ndash;Weinstein monofilaments (Semmes-Weinstein Aesthesiometer, Rolyan, WI, USA). Muscle tone of the paretic lower limb was rated with the Modified Ashworth Scale (MAS).\u003c/p\u003e\n\u003ch3\u003eOutcome Measurements\u003c/h3\u003e\n\u003cp\u003eThe primary outcome measures included gait speed and bilateral GRFs during level walking, as well as bilateral lower extremity muscle strength. Secondary outcome measures focused on energy expenditure during treadmill walking.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGait speed\u003c/b\u003e. Walking performance was assessed during level overground walking at both self-selected comfortable and maximum speeds. Participants walked barefoot along the walkway and were allowed to use walking aids as needed. Gait speed was measured using a GAITRite\u0026reg; electronic walkway (CIR Systems, Inc., NJ, USA). Participants initiated and terminated walking two meters before and after the walkway to minimise acceleration and deceleration effects. Two trials were performed at each walking speed, and the average velocity was used for statistical analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eGround reaction forces during overground walking\u003c/b\u003e. Vertical and anterior-posterior GRF, representing body weight support and forward propulsion, respectively, were measured during level overground walking at both preferred and maximum speeds. Participants walked along a 9-meter walkway with two embedded force platforms (Kistler model 9286AA and 9286BA, Winterthur, Switzerland) positioned in the middle. At least one successful trial in which each foot contacted a force platform was recorded at each speed. Force platform signals were sampled at 1000 Hz and filtered using a fourth-order Butterworth low-pass filter with a cut-off frequency of 10 Hz. GRF data were processed using custom MATLAB algorithms (R2013a, MathWorks, Inc., Natick, MA, USA). For body weight support, the first and second peaks of the vertical GRF (vertical peak 1 and 2) were extracted for both the affected and unaffected limbs. For forward propulsion, the peak anterior-posterior GRF (AP peak) was extracted for each limb. All GRF values were normalised to body weight for statistical analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEnergy expenditure during walking\u003c/b\u003e. Energy expenditure during treadmill walking was assessed by measuring oxygen uptake (V̇O\u003csub\u003e2\u003c/sub\u003e, ml/kg/min) using the Ultima\u0026trade; CardiO2\u003csup\u003e\u0026reg;\u003c/sup\u003e gas exchange analysis system (Medical Graphics Corp, St. Paul, MN, USA). Participants walked on a treadmill at both preferred and maximum speeds. Walking speed was gradually increased from a low starting speed until the target speed was reached and stabilised. Oxygen uptake was then continuously recorded for five minutes. Participants were allowed to hold the handrails for balance as needed. To evaluate training effects, energy expenditure was assessed at the same preferred and maximum walking speeds before and after the intervention. The average V̇O\u003csub\u003e2\u003c/sub\u003e over the five-minute walking period was used for statistical analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMuscle strength of the lower extremities\u003c/b\u003e. The maximum isometric strength of bilateral hip flexors, knee flexors, knee extensors, and ankle dorsiflexors was measured using a handheld dynamometer (MicroFET2, HOGGAN Health Industries, UT, USA) following standardised manual muscle testing positions. Bilateral ankle plantarflexor strength was assessed using a standardised manual muscle testing scale based on single-leg heel rise performance (18). Strength grades ranged from 0 (no detectable muscle contraction) to 5 (25 heel rises), with intermediate grades assigned according to established criteria.\u003c/p\u003e\n\u003ch3\u003eIntervention\u003c/h3\u003e\n\u003cp\u003eBoth the EXP and CON groups received training sessions lasting 30 minutes, twice a week, for eight weeks. All training was conducted on a level treadmill under the supervision of a trained physical therapist. Participants continued their routine stroke-related physical therapy throughout the study period. They were informed that the study was comparing two types of treadmill-based gait training but were not told which protocol was expected to be more effective. Thus, they were blinded to group allocation.\u003c/p\u003e \u003cp\u003eFor both groups, treadmill walking intensity was determined using the Borg category-ratio 10-point scale (CR10; 0\u0026ndash;10) (19). At the beginning of each session, participants started walking at a comfortable speed. The treadmill speed was gradually increased until they reported an exertion level of 3\u0026ndash;4 on the CR10 scale, corresponding to a \u0026ldquo;moderate\u0026rdquo; to \u0026ldquo;somewhat strong\u0026rdquo; effort. This is consistent with aerobic exercise recommendations for individuals with stroke (20). The treadmill speed was progressively increased in subsequent sessions as tolerated to maintain this target level of perceived effort.\u003c/p\u003e \u003cp\u003eDuring training, participants walked on the treadmill while wearing a custom-made, non-elastic waist pad connected to two Thera-bands, each attached to either side (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(a)). The Thera-band resistance was quantified using a numerical scale attached to the front of the waist pad and secured to the treadmill handrail. Participants were instructed to maintain a constant position on the treadmill belt.\u003c/p\u003e \u003cp\u003eIn the EXP group, Thera-band resistance was applied in three directions: directly backwards, 45\u0026deg; towards the paretic side, and 45\u0026deg; towards the non-paretic side (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The resistance level started at 1% of body weight and was gradually increased to a level corresponding to \u0026ldquo;almost moderately more effort\u0026rdquo; during walking. The resistance was further progressed across sessions as tolerated. Participants walked for five minutes in each resistance direction in a random order, and repeated twice, with rest periods allowed between blocks as needed.\u003c/p\u003e \u003cp\u003eIn the CON group, the Thera-band setup was identical to that of the EXP group, but no resistance was applied. Participants completed six five-minute walking blocks, with rest periods permitted between blocks as needed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eFor demographic characteristics, between-group comparisons were performed using independent \u003cem\u003et\u003c/em\u003e tests, Mann-Whitney U tests, and \u003cem\u003echi\u003c/em\u003e-square tests for continuous, ordinal, and categorical variables, respectively. Training effects on gait speed, GRF, walking energy expenditure, and lower extremity muscle strength were analysed using multivariate repeated-measures ANOVA (MANOVA). All randomised participants were included in the MANOVA according to their original group assignment using an intention-to-treat approach, with missing values imputed using the last observation carried forward method. Pearson correlation was used to assess pairwise associations among gait speed, GRF, and muscle strength by pooling data from both groups before and after training. The significance level was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u0026nbsp; Forty individuals with chronic stroke participated in the training program. Two participants from each group withdrew from the study (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDemographic Characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Table 1 summarises the basic characteristics of the two groups. No significant differences were found between the two groups concerning age, sex, duration since stroke onset, side of the stroke, MMSE, FMLE-motor scores, both affected and unaffected plantar sensation, or MAS scores for the affected hip adductors, hip flexors, knee extensors, ankle dorsiflexors, and ankle plantarflexors at the baseline assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; For other outcome measures, there were no significant differences between the two groups, except for the unaffected hip flexor strength, which was significantly greater in the EXP compared to the CON (\u003cem\u003ep\u003c/em\u003e=0.043).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTraining characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBoth groups completed the planned 8-week treadmill training with a similar progression of treadmill speed. The average increase in training speed did not differ significantly between groups (EXP: 0.29 \u0026plusmn; 0.17 m/s; CON: 0.33 \u0026plusmn; 0.15 m/s; \u003cem\u003ep\u003c/em\u003e=0.488), supporting that overall walking speed progression during the intervention was comparable across protocols. In addition, only the EXP group trained with posterior elastic resistance, which was progressively increased across sessions (mean change: 1.64 \u0026plusmn; 0.86 kg, corresponding to 2.22 \u0026plusmn; 1.15% of body weight), whereas the CON group walked without external resistance.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWalking Performance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Significant time effects were observed in both preferred and maximum gait speeds and in energy expenditure (Table 2). Both groups improved post-training. However, only one between-group difference was observed: the EXP group had significantly higher second vertical GRF peak on the affected side under maximum speed (\u003cem\u003ep\u003c/em\u003e=0.037). No other GRF parameters showed significant group or interaction effects.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLower Extremity Muscle Strength\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Both groups showed significant improvements post-training in the affected-side knee flexors (\u003cem\u003ep\u003c/em\u003e=0.008), knee extensors (\u003cem\u003ep\u003c/em\u003e=0.013), and ankle plantarflexors (\u003cem\u003ep\u003c/em\u003e=0.029) (Table 3). No significant group differences or interactions were observed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCorrelations between Gait Speed, GRF, and Muscle Strength\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Before training, \u003cem\u003epreferred gait speed\u003c/em\u003e showed significant correlations with the AP peak GRF on the affected side (r=0.356, \u003cem\u003ep\u003c/em\u003e=0.024), and with affected-side ankle plantarflexor strength (r=0.389, \u003cem\u003ep\u003c/em\u003e=0.013) (Table 4). No significant associations were found between AP peak GRF and lower-limb strength. Importantly, correlations between gait speed and affected-side knee extensor (r=0.377, \u003cem\u003ep\u003c/em\u003e=0.023) and ankle plantarflexor strength (r=0.485, \u003cem\u003ep\u003c/em\u003e=0.003) became evident post-training, suggesting a stronger linkage between walking performance and key propulsive muscle groups following the intervention. AP peak GRF also became significantly associated with affected-side knee extensor strength (r=0.333, \u003cem\u003ep\u003c/em\u003e=0.047), a relationship not present before training (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; For maximum gait speed, significant pre-training correlations were found with the AP peak GRF on the affected side (r=0.490, \u003cem\u003ep\u003c/em\u003e=0.001), as well as with affected-side ankle plantarflexor strength (r=0.436, \u003cem\u003ep\u003c/em\u003e=0.005) (Table 4). After training, these relationships strengthened: the AP peak GRF remained significantly correlated on the affected side (r=0.522, \u003cem\u003ep\u003c/em\u003e=0.001), and the correlation with ankle plantarflexor strength increased further (r=0.555, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). In addition, the association with affected-side knee extensor strength shifted from a non-significant trend pre-training (r=0.117, \u003cem\u003ep\u003c/em\u003e=0.471) to a significant correlation post-training (r=0.394, \u003cem\u003ep\u003c/em\u003e=0.017) (Figure 4).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003eTable 1. Demographic characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXP group\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCON group\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e55.0\u0026plusmn;10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.8\u0026plusmn;10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSex (female/male)\u003csup\u003e\u0026para;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e6/14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e26.26\u0026plusmn;5.,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.78\u0026plusmn;4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Affected side (right/left)\u003csup\u003e\u0026para;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e12/8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9/11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Onset duration (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e38.4\u0026plusmn;22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.6\u0026plusmn;42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e28.6\u0026plusmn;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.0\u0026plusmn;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFMLE-motor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e20.2\u0026plusmn;5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.6\u0026plusmn;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePlantar sensitivity big toe (dB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Affected side\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e4.63\u0026plusmn;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.90\u0026plusmn;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Non-affected side\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e4.26\u0026plusmn;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.41\u0026plusmn;0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eModified Ashworth scale (mean/median/mode)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hip adductors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.3/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.3/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hip flexors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.2/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Knee extensors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.3/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.3/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Ankle dorsiflexor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.8/0.5/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.4/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Ankle plantarflexor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.8/0.5/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.6/1/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003eBMI: Body Mass Index; MMSE: Mini-Mental Status Examination; FMLE-motor: Fugl-Meyer lower limb motor scale\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u0026para;\u003c/sup\u003eBetween group comparisons using \u0026chi;\u003csup\u003e2\u003c/sup\u003e tests.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e#\u003c/sup\u003eBetween group comparisons using Mann-Whitney U tests.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable style=\"width: 107%;border: none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"17\"\u003e\n \u003cp\u003eTable 2. Walking performance at preferred and maximum walking speed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreferred speed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum speed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXP group\u0026nbsp;\u003c/strong\u003e(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCON group\u0026nbsp;\u003c/strong\u003e(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXP group\u0026nbsp;\u003c/strong\u003e(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCON group\u0026nbsp;\u003c/strong\u003e(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGait speed (m/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.58\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.61\u0026plusmn;0.21*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.59\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.67\u0026plusmn;0.33*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.78\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.81\u0026plusmn;0.26*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e0.81\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93\u0026plusmn;0.43*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003eGround reaction force (%BW)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eVertical peak 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e98.98\u0026plusmn;11.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e100.18\u0026plusmn;8.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e99.00\u0026plusmn;9.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e100.28\u0026plusmn;8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e102.34\u0026plusmn;9.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e103.60\u0026plusmn;13.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e103.15\u0026plusmn;18.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100.88\u0026plusmn;16.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e97.36\u0026plusmn;10.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e99.02\u0026plusmn;6.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e102.59\u0026plusmn;14.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e100.27\u0026plusmn;14.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e101.97\u0026plusmn;11.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e102.61\u0026plusmn;12.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e105.91\u0026plusmn;13.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e106.24\u0026plusmn;13.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eVertical peak 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e99.18\u0026plusmn;13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e98.68\u0026plusmn;8.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e97.87\u0026plusmn;8.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e95.87\u0026plusmn;10.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e100.49\u0026plusmn;11.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e101.23\u0026plusmn;10.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e93.23\u0026plusmn;12.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e96.75\u0026plusmn;11.82\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e97.52\u0026plusmn;10.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e102.87\u0026plusmn;7.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e100.67\u0026plusmn;10.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e101.90\u0026plusmn;7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e97.69\u0026plusmn;13.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e101.84\u0026plusmn;6.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e103.98\u0026plusmn;8.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e102.00\u0026plusmn;9.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAP peak\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e6.72\u0026plusmn;3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e8.22\u0026plusmn;3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e7.93\u0026plusmn;3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e7.56\u0026plusmn;3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e9.81\u0026plusmn;5.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e10.73\u0026plusmn;5.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e10.20\u0026plusmn;5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.90\u0026plusmn;6.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e9.78\u0026plusmn;5.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e11.01\u0026plusmn;5.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e11.90\u0026plusmn;4.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e11.59\u0026plusmn;4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e12.69\u0026plusmn;5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e13.99\u0026plusmn;5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e13.69\u0026plusmn;8.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.07\u0026plusmn;8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eEnergy expenditure (ml/kg/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e9.00\u0026plusmn;1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e8.33\u0026plusmn;1.64*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e9.24\u0026plusmn;2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e8.73\u0026plusmn;2.18*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e10.01\u0026plusmn;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e8.92\u0026plusmn;1.86*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e10.68\u0026plusmn;2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.28\u0026plusmn;2.47*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"17\"\u003e\n \u003cp\u003eBW: body weight; *Significant time main effects; \u0026dagger;Significant group main effects\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003eTable 3. Lower extremity muscle strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXP group\u0026nbsp;\u003c/strong\u003e(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCON group\u0026nbsp;\u003c/strong\u003e(n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHip flexors\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.55\u0026plusmn;3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.62\u0026plusmn;2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.79\u0026plusmn;3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.69\u0026plusmn;3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.37\u0026plusmn;3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.31\u0026plusmn;3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.26\u0026plusmn;3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.54\u0026plusmn;3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKnee flexors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.03\u0026plusmn;2.61*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.19\u0026plusmn;3.51*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.93\u0026plusmn;2.73*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.78\u0026plusmn;3.15*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.28\u0026plusmn;3.19*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.03\u0026plusmn;4.64*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.83\u0026plusmn;2.67*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.18\u0026plusmn;3.80*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKnee extensors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.99\u0026plusmn;2.97*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.20\u0026plusmn;4.90*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.20\u0026plusmn;2.89*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.30\u0026plusmn;4.28*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.66\u0026plusmn;3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.51\u0026plusmn;5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.77\u0026plusmn;3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.19\u0026plusmn;4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAnkle dorsiflexors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.69\u0026plusmn;3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.08\u0026plusmn;2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.03\u0026plusmn;3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.00\u0026plusmn;3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.63\u0026plusmn;4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.22\u0026plusmn;3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.95\u0026plusmn;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.93\u0026plusmn;3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAnkle plantarflexors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.55\u0026plusmn;1.00*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.85\u0026plusmn;1.09*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.55\u0026plusmn;1.05*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.85\u0026plusmn;0.93*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUnaffected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.15\u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.40\u0026plusmn;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.15\u0026plusmn;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.25\u0026plusmn;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003eUnit: kg; *Significant time main effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable style=\"float: ;width: 100%;border: none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\n \u003cp\u003eTable 4. Correlations among gait speed, AP peak GRF, and affected-side muscle strength in both conditions.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreferred speed condition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum speed condition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003eGait speed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003eGait speed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre (n=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost (n=36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre (n=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost (n=36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAP peak GRF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.024*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKnee extensors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.023*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAnkle plantarflexors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.013*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003eAP peak GRF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003eAP peak GRF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre (n=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost (n=36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePre (n=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePost (n=36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKnee extensors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.047*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.017*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAnkle plantarflexors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\n \u003cp\u003e*Significant correlation between the two variables\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the effects of task-oriented treadmill training, with or without additional posterior pelvic elastic resistance, on walking performance, GRFs, lower limb muscle strength, and their interrelationships in individuals with chronic stroke and limited walking ability. Both training protocols led to significant improvements in gait speed, walking energy expenditure, and selected GRF variables, confirming that intensive gait‑focused training remains beneficial even in individuals with relatively slow walking speeds. Compared with conventional treadmill training, the experimental intervention produced a larger increase in the second vertical GRF peak on the affected side at maximum walking speed. Furthermore, when data from both groups were pooled, post‑training correlations showed stronger associations among walking speed, affected knee extensor and ankle plantarflexor strength, and AP GRF peaks. These findings suggest that treadmill‑based gait training as a whole can enhance the coupling between neuromuscular capacity, propulsive forces, and functional walking performance.\u003c/p\u003e \u003cp\u003eWe hypothesised that adding posterior pelvic elastic resistance would augment paretic limb propulsion, yield greater improvements in speed and efficiency, and alter the relationships among walking speed, GRFs, and muscle strength. The results partially support these hypotheses. First, regardless of group allocation, participants increased preferred and maximum walking speed and reduced walking energy expenditure. Importantly, the increase in treadmill training speed over the 8-week intervention did not differ significantly between groups, indicating that both protocols provided a comparable amount of speed-progressive, task-oriented walking practice. These findings align with recent studies showing that repetitive, task‑oriented gait training and high‑intensity treadmill programs can improve walking capacity and metabolic efficiency in chronic stroke. For example, randomised treadmill aerobic training has been shown to enhance walking endurance and cardiorespiratory fitness with concurrent reductions in oxidative stress (21), while performance-based high-intensity treadmill interventions yield superior gains in walking speed, endurance, and balance that persist beyond the training period (22). Such evidence reinforces the role of structured, gait-centred interventions as a core component of stroke rehabilitation, consistent with current clinical guidelines and recent systematic reviews (23, 24).\u003c/p\u003e \u003cp\u003eSecond, at maximum overground speed, only the EXP group showed a greater increase in the second vertical GRF peak on the affected side than the CON group. Given that the increase in treadmill speed during training was similar for both groups, this group difference in late-stance vertical GRF is likely attributable to the additional posterior resistance rather than to greater exposure to faster walking per se. This pattern suggests that posterior elastic resistance may facilitate enhanced paretic limb loading and vertical support during late stance under high-demand conditions. Recent work on propulsion‑oriented gait training similarly emphasises the importance of challenging the paretic limb to bear load and generate push‑off, especially when training at faster speeds (25). Taken together, these findings support the notion that augmenting intensity-matched, task-specific gait practice with targeted posterior resistance may further promote functional propulsion capacity in chronic stroke, particularly during faster or more demanding walking.\u003c/p\u003e \u003cp\u003eWalking speed after stroke is closely related to lower-limb strength, particularly knee extensors and ankle plantarflexors, and to propulsion mechanics reflected by GRF, especially the anterior-posterior component. Therefore, changes in the strength-GRF-speed relationships can provide mechanistic insight into whether training improves not only isolated capacities but also their functional integration during gait (9, 10). Before training, the relationships among strength, GRFs, and speed were relatively weak, implying inability in using the existing lower limb strength to generate appropriate propulsive forces. After the training period, the stronger, more systematic correlations suggest that participants not only improved in isolated capacities, but also in how these capacities were integrated during gait. These emerging correlations may reflect a more efficient integration of available neuromuscular resources during gait, whereby key antigravity and propulsive muscles are recruited in a more phase-appropriate manner to support functional walking. This interpretation aligns with current motor control and neurorehabilitation frameworks emphasising improved coordination and resource allocation rather than isolated capacity gains alone (26, 27). Importantly, these reorganised correlations were observed when data from both groups were pooled, implying that intensive treadmill‑based gait training in general, regardless of the presence of elastic resistance, can promote more efficient coordination between neuromuscular output and biomechanical function. Recent literature similarly reports that high‑repetition, task‑oriented gait training can refine muscle activation timing and inter‑segmental coordination (28). Overall, these findings suggest that intensive, task‑oriented treadmill training primarily enhances the coordination and functional use of existing neuromuscular resources, rather than strength alone, by promoting more efficient, phase‑appropriate recruitment of key muscles during gait.\u003c/p\u003e \u003cp\u003eClinically, these findings suggest that even in individuals with chronic stroke who walk at speeds below 0.8 m/s, a structured task‑oriented treadmill program can still yield meaningful gains in gait speed and reductions in the walking energy expenditure. This indicates that higher‑intensity, task‑specific gait training is feasible and beneficial not only for higher‑functioning stroke survivors but also for those with more severe walking limitations, thereby supporting the inclusion of treadmill‑based protocols in routine practice, including in resource‑limited settings (27). The additional posterior pelvic elastic resistance did not produce uniformly superior outcomes across all variables, but it did lead to greater improvement in the paretic second vertical GRF peak at maximum speed. For patients who can safely tolerate higher training demands, elastic resistance may therefore be considered as an adjunct to amplify mechanical loading of the paretic limb and encourage more symmetrical, propulsive late‑stance behaviour. Recent studies on resistance‑augmented gait training (29) and speed‑dependent treadmill intervention (30) suggest that such targeted loading strategies can be particularly useful for addressing persistent propulsion deficits. From a practical standpoint, elastic bands and simple harness systems are low‑cost, widely available, and easily adjustable to individual capacity. Combining them with treadmill training offers a feasible method to increase training intensity and specificity.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. The sample size, while comparable to that of similar trials, may have been underpowered to detect small‑to‑moderate between‑group effects. Future studies should recruit larger cohorts and consider multicenter designs to enhance statistical power and generalizability. Second, only short‑term pre‑ to post‑intervention effects were assessed. We did not evaluate whether the improvements in walking performance and the strengthened coupling among strength, GRFs, and speed are maintained over time or translate into better community ambulation and participation. Long‑term follow‑up and the use of wearable sensors to monitor real‑world walking are recommended in future research. Finally, although the magnitude of posterior elastic resistance was recorded and progressively increased within a target perceived-exertion range, the study was not designed to systematically compare different resistance doses or directions. As a result, dose-response relationships remain unclear. Future studies should systematically vary resistance magnitude, direction, and progression to identify optimal dosing parameters and the patient subgroups most likely to benefit.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, task‑oriented treadmill training improved walking speed, reduced energy expenditure, and enhanced the functional coupling among lower limb strength, GRFs, and gait performance in individuals with chronic stroke and limited walking ability. Adding posterior pelvic elastic resistance further increased paretic vertical loading during late stance at maximum walking speed, although most clinical and biomechanical outcomes improved similarly in both groups. These findings support the use of intensive, gait‑oriented treadmill training as a core intervention in chronic stroke rehabilitation and suggest that posterior elastic resistance may serve as a useful adjunct for targeting paretic limb loading and propulsion. Future larger, multimodal, and longer‑term studies are warranted to refine the role and dosing of resistance‑augmented treadmill training in this population.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eANOVA analysis of variance\u003c/p\u003e \u003cp\u003eAP anterior-posterior\u003c/p\u003e \u003cp\u003eCON conventional treadmill training group\u003c/p\u003e \u003cp\u003eCR10 Borg category-ratio 10-point scale\u003c/p\u003e \u003cp\u003eEXP treadmill training with posterior resistance group\u003c/p\u003e \u003cp\u003eFMLE-motor Fugl-Meyer Assessment for the lower extremity\u003c/p\u003e \u003cp\u003eGRF ground reaction force\u003c/p\u003e \u003cp\u003eMANOVA multivariate repeated-measures analysis of variance\u003c/p\u003e \u003cp\u003eMAS Modified Ashworth Scale\u003c/p\u003e \u003cp\u003eMMSE Mini-Mental State Examination\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003e Ethical approval was obtained from the Institutional Review Board of the National Cheng Kung University Hospital (protocol number: A-ER-110-027), and all participants provided consent prior to participation. Consent for publication: Not applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFYC \u0026ndash; conceptualisation, formal analysis, manuscript preparation; YTC \u0026ndash; research design, data collection, formal analysis, manuscript preparation; SIL \u0026ndash; conceptualization, research design, data collection, formal analysis, project administration, supervision, manuscript preparation; HYT \u0026ndash; data collection, formal analysis, manuscript preparation; PYL \u0026ndash; conceptualisation, research design, data collection, formal analysis, computer programming, project administration, supervision, manuscript preparation. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors express gratitude to Yu-Ying Chen, Li-Yu Lin and Ting-Yuan Huang for their assistance with participant recruitment and data collection.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTasseel-Ponche S, Delafontaine A, Godefroy O, Yelnik AP, Doutrellot PL, Duchossoy C, et al. Walking speed at the acute and subacute stroke stage: A descriptive meta-analysis. Frontiers in neurology. 2022;13:989622.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsiao H, Awad LN, Palmer JA, Higginson JS, Binder-Macleod SA. Contribution of Paretic and Nonparetic Limb Peak Propulsive Forces to Changes in Walking Speed in Individuals Poststroke. Neurorehabilitation and neural repair. 2016;30(8):743\u0026thinsp;\u0026minus;\u0026thinsp;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAguiar LT, Camargo LBA, Estarlino LD, Teixeira-Salmela LF, Faria C. Strength of the lower limb and trunk muscles is associated with gait speed in individuals with sub-acute stroke: a cross-sectional study. Braz J Phys Ther. 2018;22(6):459\u0026thinsp;\u0026minus;\u0026thinsp;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRossler R, Bridenbaugh SA, Engelter ST, Weibel R, Infanger D, Giannouli E, et al. Recovery of mobility function and life-space mobility after ischemic stroke: the MOBITEC-Stroke study protocol. BMC neurology. 2020;20(1):348.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButsing N, Tipayamongkholgul M, Wang JD, Ratanakorn D. Combined quality of life and survival for estimation of long-term health outcome of patients with stroke. Health Qual Life Outcomes. 2022;20(1):46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi N, Zhang J, Du Y, Li J, Wang A, Zhao X. Gait speed after mild stroke/transient ischemic attack was associated with long-term adverse outcomes: A cohort study. Ann Clin Transl Neurol. 2024;11(12):3163-74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee DH, Chang WN, Jeon HJ. Comparison of ground reaction force during gait between the nonparetic side in hemiparetic patients and the dominant side in healthy subjects. Journal of exercise rehabilitation. 2020;16(4):344\u0026thinsp;\u0026minus;\u0026thinsp;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMazzoli D, Basini G, Prati P, Galletti M, Mascioli F, Rambelli C, et al. Indices of Loading and Propulsive Ability in the Gait of Patients With Chronic Stroke With Equinus Foot Deviation: A Correlation Study. Frontiers in human neuroscience. 2021;15:771392.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAwad LN, Hsiao H, Binder-Macleod SA. Central Drive to the Paretic Ankle Plantarflexors Affects the Relationship Between Propulsion and Walking Speed After Stroke. Journal of neurologic physical therapy : JNPT. 2020;44(1):42\u0026thinsp;\u0026minus;\u0026thinsp;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJasper AM, Lazaro RT, Mehta SP, Perry LA, Swanson K, Reedy K, et al. Predictors of gait speed post-stroke: A systematic review and meta-analysis. Gait Posture. 2025;121:70\u0026thinsp;\u0026minus;\u0026thinsp;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiarmatzis G, Giannakou E, Karagiannakidou I, Makri E, Tsiakiri A, Christidi F, et al. Effects of a 12-Week Moderate-to-High Intensity Strength Training Program on the Gait Parameters and Their Variability of Stroke Survivors. Brain Sci. 2025;15(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee Y, Kim GB, Shin S. Association Between Lower Limb Strength Asymmetry and Gait Asymmetry: Implications for Gait Variability in Stroke Survivors. Journal of clinical medicine. 2025;14(2):380.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi C, Xiao Y, Zang D, Ren H. Effectiveness of Treadmill Training Intervention for the Management of Patients With Stroke: A Systematic Review and Meta-Analysis. Int J Nurs Pract. 2025;31(3):e70020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlingh JF, Groen BE, Van Asseldonk EHF, Geurts ACH, Weerdesteyn V. Effectiveness of rehabilitation interventions to improve paretic propulsion in individuals with stroke - A systematic review. Clin Biomech (Bristol). 2020;71:176\u0026thinsp;\u0026minus;\u0026thinsp;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMehrholz J, Thomas S, Elsner B. Treadmill training and body weight support for walking after stroke. Cochrane Database Syst Rev. 2017;8(8):CD002840.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWashabaugh EP, Augenstein TE, Krishnan C. Functional resistance training during walking: Mode of application differentially affects gait biomechanics and muscle activation patterns. Gait Posture. 2020;75:129\u0026thinsp;\u0026minus;\u0026thinsp;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLerin-Calvo A, Carrasco-Gonzalez E, Reina-Varona A, Fernandez-Perez JJ. Resistance training for gait rehabilitation in people with stroke. A systematic review and meta-analysis. Disability and rehabilitation. 2026;48(2):331\u0026thinsp;\u0026minus;\u0026thinsp;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarybeth Brown DA. Daniels and Worthingham's Muscle Testing. Techniques of Manual Examination and Performance Testing. 10th ed: Saunders: Elsevier Inc.; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorg G. Borg's perceived exertion and pain scales. Champaign, IL, US: Human Kinetics; 1998. viii, 104-viii, p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBillinger SA, Arena R, Bernhardt J, Eng JJ, Franklin BA, Johnson CM, et al. Physical activity and exercise recommendations for stroke survivors: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014;45(8):2532-53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSerra MC, Hafer-Macko CE, Robbins R, O'Connor JC, Ryan AS. Randomization to Treadmill Training Improves Physical and Metabolic Health in Association With Declines in Oxidative Stress in Stroke. Archives of physical medicine and rehabilitation. 2022;103(11):2077-84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee H-J, Oh D-w. Exploring the impact of performance-based high-intensity treadmill training in chronic stroke patients: a group-matched, single-blind pilot trial with a 3-month follow-up. Physiotherapy Quarterly. 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoore SA, Boyne P, Fulk G, Verheyden G, Fini NA. Walk the Talk: Current Evidence for Walking Recovery After Stroke, Future Pathways and a Mission for Research and Clinical Practice. Stroke; a journal of cerebral circulation. 2022;53(11):3494\u0026thinsp;\u0026minus;\u0026thinsp;505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaricich A, Borg MB, Battaglia M, Facciorusso S, Spina S, Invernizzi M, et al. High-Intensity Exercise Training Impact on Cardiorespiratory Fitness, Gait Ability, and Balance in Stroke Survivors: A Systematic Review and Meta-Analysis. Journal of clinical medicine. 2024;13(18).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlingh JF, Groen BE, Kamphuis JF, Geurts ACH, Weerdesteyn V. Task-specific training for improving propulsion symmetry and gait speed in people in the chronic phase after stroke: a proof-of-concept study. Journal of neuroengineering and rehabilitation. 2021;18(1):69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBelda-Lois JM, Mena-del Horno S, Bermejo-Bosch I, Moreno JC, Pons JL, Farina D, et al. Rehabilitation of gait after stroke: a review towards a top-down approach. Journal of neuroengineering and rehabilitation. 2011;8:66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeodoro J, Fernandes S, Castro C, Fernandes JB. Current Trends in Gait Rehabilitation for Stroke Survivors: A Scoping Review of Randomized Controlled Trials. Journal of clinical medicine. 2024;13(5):1358.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J, Kim K, Cho Y, Kim H. Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research. Neurol Int. 2024;16(6):1451-63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwaminathan K, Porciuncula F, Park S, Kannan H, Erard J, Wendel N, et al. Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke. Journal of neuroengineering and rehabilitation. 2023;20(1):85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu J, Jin L, Wang Y, Shen X. Feasibility of challenging treadmill speed-dependent gait and perturbation-induced balance training in chronic stroke patients with low ambulation ability: a randomized controlled trial. Frontiers in neurology. 2023;14:1167261.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chronic stroke, Treadmill walking, Resistance training, Ground reaction force, Propulsion, Lower-limb strength","lastPublishedDoi":"10.21203/rs.3.rs-9242688/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9242688/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eReduced gait speed, impaired ground reaction force (GRF) generation, and lower-limb weakness are common in chronic stroke survivors and contribute to limited functional mobility. While treadmill training improves walking capacity, its effects on propulsion mechanics and the integration of muscle strength with GRFs remain unclear. Posterior pulling resistance may increase propulsive demand during gait and enhance neuromuscular-biomechanical coupling. The purpose of this study was to investigate the effects of task-oriented treadmill training with and without posterior resistance on gait speed, GRFs, lower-limb muscle strength, walking energy expenditure, and the relationships among these variables in individuals with chronic stroke.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eForty chronic stroke participants were randomly assigned to conventional treadmill training (CON) or treadmill training with posterior resistance (EXP). Both groups received training for 30 minutes/session, twice weekly for eight weeks. Primary outcomes included preferred and maximum gait speed, bilateral vertical and anterior-posterior GRFs during overground walking, and lower-limb muscle strength. Secondary outcomes included walking energy expenditure (V̇O₂). Multivariate repeated-measures ANOVA was used to assess training effects. Pearson correlation was used to examine associations among gait speed, GRFs, and strength pre- and post-training.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBoth groups demonstrated significant improvements in preferred and maximum gait speed, reduced walking energy expenditure, and increased affected-side knee flexor, knee extensor, and ankle plantarflexor strength (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A significant between-group difference was observed only for the second vertical GRF peak on the affected side at maximum speed, which increased more in EXP (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037). Post-training analyses revealed strengthened correlations between gait speed and affected-side knee extensor and ankle plantarflexor strength, as well as between anterior-posterior GRF and knee extensor strength, suggesting enhanced strength-GRF-speed coupling.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eTask-oriented treadmill training improves walking speed, metabolic efficiency, and the functional integration of lower-limb strength and propulsive mechanics in chronic stroke survivors. Posterior pulling resistance may further augment affected limb loading during high-speed walking. These findings support gait-oriented treadmill training as a core intervention, with resistance as a feasible adjunct to target propulsion deficits.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e \u003cp\u003eCliniclTrials.gov Protocol Registration: trial number NCT04974840.\u003c/p\u003e","manuscriptTitle":"Task-Oriented Treadmill Training With Posterior Resistance Improves Gait Speed and Strength-Ground Reaction Force Coupling in Chronic Stroke Survivors: A Randomised Controlled Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 00:23:53","doi":"10.21203/rs.3.rs-9242688/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-14T22:00:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T21:20:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T22:20:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-10T14:39:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12847305416693694438248235841416766915","date":"2026-04-21T23:34:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268811567849364975393499271084973235299","date":"2026-04-21T20:39:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20338180323597905668039513577553205378","date":"2026-04-20T04:12:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218781461452357567174203245303569961520","date":"2026-04-20T01:00:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-19T23:33:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-31T02:16:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-31T02:16:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of NeuroEngineering and Rehabilitation","date":"2026-03-27T08:54:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0760448f-dd19-4e81-a1d6-36e2d585f81f","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-14T22:00:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T21:20:37+00:00","index":52,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T22:20:46+00:00","index":51,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-10T14:39:05+00:00","index":50,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T22:08:49+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 00:23:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9242688","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9242688","identity":"rs-9242688","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}