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Spinal reciprocal inhibition (RI) and intracortical inhibition are important physiological mechanisms for voluntary movement control and functional recovery of voluntary movement in patients with stroke. Spasticity, which impairs motor performance, is one of the major manifestations of stroke. RI may be involved in reducing spasticity. This might allow finger extension, and, therefore, better hand function by reducing co-contraction with finger extensors. One potential mechanism of functional reorganization of the motor cortex is that pre-existing masking pathways are unmasked by decreased intracortical inhibition. The inhibitory neurotransmitter GABA plays an important role in this process. Changes in RI might be mediated through unmasking of cortical pathways through decreased inhibition, with the neurotransmitter GABA. These changes can be assessed using short-latency intracortical inhibition (SICI) and RI. Functional recovery in the chronic phase of stroke induced by rehabilitation was accompanied by SICI and spinal RI changes. Cortical reorganization and spinal plasticity might play important roles in functional recovery induced by rehabilitation, even in patients with chronic severe hemiparesis. This review aims to provide a focused overview of neuroplasticity of spinal RI and intracortical inhibition associated with functional motor recovery from stroke.

In the original publication of the article, it was published under the title ‘Mini-review article: the role of spinal reciprocal inhibition and intracortical inhibition in functional recovery from stroke’.

Degenerative cerebellar ataxias (DCAs) are progressive diseases that reduce quality of life (QoL). This study aimed to assess the impact of rehabilitation on QoL in patients with DCAs using structural equation modeling (SEM). This cross-sectional survey included members of a national Japanese DCAs patient association. Assessed latent variables included personal, medical, and environmental factors, impairments, activity limitations, rehabilitation (participation quantity and patient-reported quality), and QoL. SEM was used to explore causal relationships between these latent variables. Overall, 477 participants (mean age 65.4 years; 45.1% female) were included. Impairments were categorized as primary and secondary, based on preliminary analyses. The final model demonstrated acceptable-to-good fit indices, explaining 74% of the variance in QoL. The model paths showed that activity limitations, secondary impairments, and rehabilitation quality had a direct effect on QoL, in that order. The quantity of rehabilitation had an indirect effect on QoL through its direct effect on secondary impairments and quality of rehabilitation. These findings suggest that rehabilitation interventions improve QoL in the DCA population, but its effects vary depending on the quantity and quality of rehabilitation. However, the cross-sectional study design limits the ability to draw causal conclusions and longitudinal studies are needed for confirmation.

In Table 1, the codes under “Observed variables [range], adopted response” were incorrectly placed under “Latent variables”. Latent variables Observed variables [range], adopted response Data available, n (%) Applicable sample, n (%) Mean (SD) Median (25%, 75% IQR) Personal factors p1 Age, y 477 (100.0) 65.4 (12.4) 67 (57, 74) p2 Sex, male 475 (99.6) 261 (54.9) p3 Body mass index, kg/m2 465 (97.5) 21.4 (3.3) 21.2 (19.1, 23.7) p4 Educational background, post-secondary 474 (99.4) 291 (61.0) Medical factors m1 Disease type, complex 466 (97.7) 330 (70.8) m2 Disease duration, years 448 (93.9) 13.8 (11.0) 10.8 (6.0, 18.2) m3 Number of common complications 402 (84.3) 0.6 (0.8) 0 (0, 1) m4 Number of disease-related complications 402 (84.3) 0.5 (0.8) 0 (0, 1) m5 Number of medications 467 (97.9) 4.4 (3.5) 4 (2, 6) m6 Drugs for cerebellar symptoms, yes 435 (91.2) 284 (65.3) m7 Drugs for Parkinsonism, yes 434 (91.0) 76 (17.5) m8 History of falls within the past year, ≥ 1 458 (96.0) 365 (79.7) Environmental factors s1 Type of residence, home 475 (99.6) 444 (93.5) s2 Environmental improvement, yes 467 (97.9) 367 (78.6) s3 Cohabitation, yes 457 (95.8) 399 (87.3) s4 Caregiver support, yes 436 (91.4) 384 (88.1) s5 Work, yes 447 (93.7) 104 (23.3) s6 Need for social support [0–10] 459 (96.2) 7.6 (2.5) 8 (6, 10) s7 Satisfaction with social support [0–10] 456 (95.6) 5.6 (2.3) 5 (5, 7) Impairments i1 Ataxia [0–3], ≥ 1 471 (98.7) 468 (99.4) 2.4 (0.8) 3 (2, 3) i2 Weakness [0–3], ≥ 1 473 (99.2) 419 (88.6) 1.8 (1.0) 2 (1, 3) i3 Rigidity [0–3], ≥ 1 467 (97.9) 335 (71.7) 1.3 (1.1) 1 (0, 2) i4 Spasticity [0–3], ≥ 1 462 (96.9) 294 (63.6) 1.2 (1.1) 1 (0, 2) i5 Imbalance [0–3], ≥ 1 470 (98.5) 462 (98.3) 2.5 (0.8) 3 (2, 3) i6 Malalignment [0–3], ≥ 1 466 (97.7) 290 (62.2) 1.1 (1.1) 1 (0, 2) i7 Fatigue [0–3], ≥ 1 464 (97.3) 388 (83.6) 1.6 (1.0) 2 (1, 2) i8 Pain [0–3], ≥ 1 452 (94.8) 193 (42.7) 0.8 (1.0) 0 (0, 2) i9 Numbness [0–3], ≥ 1 446 (93.5) 150 (33.6) 0.6 (0.9) 0 (0, 1) i10 Sensory disturbances [0–3], ≥ 1 467 (97.9) 268 (57.4) 1.0 (1.0) 1 (0, 2) i11 Tremor [0–3], ≥ 1 468 (98.1) 289 (61.8) 1.1 (1.1) 1 (0, 2) i12 Involuntary movements [0–3], ≥ 1 454 (95.2) 235 (51.8) 0.9 (1.0) 1 (0, 1) i13 Orthostatic hypotension [0–3], ≥ 1 469 (98.3) 186 (39.7) 0.7 (1.0) 0 (0, 1) i14 Poor sleep [0–3], ≥ 1 468 (98.1) 228 (48.7) 0.8 (1.0) 0 (0, 1) i15 Respiratory disorder [0–3], ≥ 1 466 (97.7) 175 (37.6) 0.6 (0.9) 0 (0, 1) i16 Speech dysarthria [0–3], ≥ 1 473 (99.2) 437 (92.4) 2.0 (1.0) 2 (1, 3) i17 Dysphagia [0–3], ≥ 1 474 (99.4) 389 (82.1) 1.5 (1.0) 1 (1, 2) i18 Visual impairment [0–3], ≥ 1 472 (99.0) 314 (66.5) 1.2 (1.1) 1 (0, 2) i19 Urinary impairment [0–3], ≥ 1 472 (99.0) 294 (62.3) 1.3 (1.2) 1 (0, 2) i20 Bowel impairment [0–3], ≥ 1 476 (99.8) 282 (59.2) 1.2 (1.2) 1 (0, 2) i21 Cognitive impairment [0–3], ≥ 1 475 (99.6) 210 (44.2) 0.6 (0.8) 0 (0, 1) i22 PHQ-2 score [0–6], ≥ 1 458 (96.0) 286 (62.4) 1.8 (1.8) 1 (0, 3) Activity limitations a1 mRS score [0–5], ≤ 2 (= independence) 461 (96.6) 110 (23.9) 3.4 (1.1) 4 (3, 4) a2 Indoor mobility1,2,3,4,5, ≥ 4 (= ambulatory) 461 (96.6) 165 (35.8) 3.6 1.4 4 (2, 5) a3 Outdoor mobility1,2,3,4,5, ≥ 4 (= ambulatory) 469 (98.3) 149 (31.8) 2.8 1.3 3 (2, 4) a4 BI [0–100] 474 (99.4) 70.1 (36.6) 90 (45, 100) a5 LSA score [0–120] 475 (99.6) 36.7 (28.4) 30 (17, 48.5) Quantity of rehabilitation r1 Types of rehabilitation implemented, ≥ 1 477 (100.0) 368 (77.1) r2 Types of therapy, maximum of 3 477 (100.0) 1.3 (1.0) 1 (0, 2) r3 Total rehabilitation time, min/month 477 (100.0) 543.4 (609.5) 320 (160, 720) r4 Duration of rehabilitation, months 476 (99.8) 49.4 (64.0) 30 (2, 71.5) r5 Types of rehabilitation program 477 (100.0) 5.9 (4.4) 5 (2.5, 9) r6 Self-rehabilitation, yes 450 (94.3) 324 (72.0) Quality of rehabilitation 368 (77.1) r7 Effects of rehabilitation [0–10] 356 (96.7) 6.4 (2.4) 6 (5, 8) r8 Self-efficacy of rehabilitation [0–10] 355 (96.5) 6.1 (2.5) 6 (5, 8) r9 Satisfaction with rehabilitation [0–10] 354 (96.2) 6.5 (2.4) 7 (5, 8) r10 Motivation for rehabilitation [0–10] 354 (96.2) 7.2 (2.4) 8 (6, 9) Quality of life q1 EQ index [0.00–1.00] 456 (95.6) 0.49 (0.23) 0.51 (0.31, 0.66) q2 EQ-VAS [0–100] 440 (92.2) 57.9 (23.9) 60 (45, 78.5) q3 Life satisfaction score [0–10] 456 (95.6) 5.1 (2.3) 5 (4, 7) Table 2. Unstandardized and standardized regression coefficients of specified paths within the final model (rehabilitation effects model). Latent variables Observed indicators B Unstandardized estimate Lower 95% CI Upper 95% CI Β Standardized estimate Lower 95% CI Upper 95% CI P value Personal factors  →  p1 Age − 3.523 − 4.908 − 2.138 − 0.285 − 0.394 − 0.176  < 0.001  →  p2 Sex 0.112 − 0.032 0.255 0.112 − 0.032 0.255 0.200  →  p3 Body mass index 1.592 1.206 1.978 0.487 0.376 0.599  < 0.001  →  p4 Educational background 0.184 0.064 0.303 0.184 0.064 0.303 0.011 Medical factors  →  m1 Disease type − 0.683 − 0.785 − 0.581 − 0.683 − 0.785 − 0.581  < 0.001  →  m4 Number of disease-related complications − 0.599 − 0.701 − 0.496 − 0.599 − 0.701 − 0.496  < 0.001  →  m5 Number of medications − 0.153 − 0.179 − 0.126 − 0.552 − 0.636 − 0.468  < 0.001  →  m6 Drugs for cerebellar symptoms 0.307 0.180 0.434 0.307 0.180 0.434  < 0.001  →  m7 Drugs for Parkinsonism − 0.747 − 0.872 − 0.623 − 0.747 − 0.872 − 0.623  < 0.001  →  m8 History of falls within the past year 0.149 0.042 0.257 0.146 0.043 0.250 0.020 Environmental factors  →  s1 Type of residence 0.565 0.390 0.739 0.565 0.390 0.739  < 0.001  →  s3 Cohabitation − 0.363 − 0.513 − 0.212 − 0.363 − 0.513 − 0.212  < 0.001  →  s4 Caregiver support − 0.773 − 0.905 − 0.641 − 0.773 − 0.905 − 0.641  < 0.001  →  s6 Need for social support − 1.075 − 1.334 − 0.816 − 0.438 − 0.534 − 0.343  < 0.001  →  s7 Satisfaction with social support − 0.377 − 0.599 − 0.155 − 0.164 − 0.259 − 0.069 0.005 Primary impairments  →  i1 Ataxia 0.308 0.169 0.446 0.751 0.699 0.804  < 0.001  →  i5 Imbalance 0.256 0.141 0.371 0.624 0.564 0.684  < 0.001  →  i11 Tremor 0.262 0.146 0.377 0.64 0.584 0.695  < 0.001  →  i16 Speech dysarthria 0.285 0.158 0.413 0.697 0.648 0.746  < 0.001  →  i17 Dysphagia 0.311 0.172 0.45 0.76 0.719 0.802  < 0.001  →  i18 Visual impairment 0.181 0.099 0.264 0.443 0.372 0.514  < 0.001  →  i19 Urinary impairment 0.294 0.163 0.425 0.717 0.667 0.767  < 0.001  →  i20 Bowel impairment 0.325 0.18 0.47 0.794 0.751 0.836  < 0.001 Secondary impairments  →  i2 Weakness 0.363 0.309 0.417 0.824 0.785 0.863  < 0.001  →  i3 Rigidity 0.335 0.287 0.382 0.759 0.717 0.802  < 0.001  →  i6 Malalignment 0.337 0.288 0.385 0.764 0.721 0.807  < 0.001  →  i7 Fatigue 0.336 0.291 0.381 0.762 0.721 0.804  < 0.001  →  i8 Pain 0.279 0.234 0.323 0.632 0.567 0.697  < 0.001  →  i10 Sensory disturbances 0.339 0.292 0.387 0.770 0.726 0.814  < 0.001  →  i22 PHQ-2 score 0.258 0.217 0.300 0.586 0.525 0.648  < 0.001 Activity limitations  →  a2 Indoor mobility − 0.382 − 0.476 − 0.287 − 0.862 − 0.903 − 0.820  < 0.001  →  a3 Outdoor mobility − 0.250 − 0.317 − 0.184 − 0.565 − 0.627 − 0.504  < 0.001  →  a4 BI − 0.400 − 0.516 − 0.284 − 0.903 − 0.959 − 0.846  < 0.001  →  a5 LSA − 0.320 − 0.403 − 0.236 − 0.722 − 0.771 − 0.673  < 0.001 QoL  →  q1 EQ index 0.124 0.102 0.146 1.029 0.981 1.076  < 0.001  →  q2 EQ-VAS score 0.304 0.253 0.354 0.591 0.533 0.649  < 0.001  →  q3 Life satisfaction score 0.3 0.203 0.396 0.249 0.168 0.331  < 0.001 Quantity of rehabilitation  →  r1 Types of rehabilitation implemented 0.802 0.750 0.854 0.865 0.819 0.912  < 0.001  →  r2 Types of therapy 0.807 0.757 0.858 0.871 0.827 0.915  < 0.001  →  r3 Total rehabilitation time 0.693 0.544 0.843 0.665 0.574 0.757  < 0.001  →  r4 Duration of rehabilitation 0.470 0.383 0.557 0.644 0.572 0.716  < 0.001  →  r5 Types of rehabilitation program 2.150 1.811 2.489 0.529 0.460 0.598  < 0.001 Quality of rehabilitation  →  r7 Effects of rehabilitation 2.057 1.858 2.256 0.911 0.877 0.945  < 0.001  →  r9 Satisfaction with rehabilitation 2.175 1.943 2.408 0.942 0.907 0.977  < 0.001  →  r10 Motivation for rehabilitation 1.906 1.671 2.142 0.791 0.743 0.839  < 0.001 Personal factors  →  Primary impairments − 1.565 − 0.648 − 2.482 − 0.641 − 0.749 − 0.533  < 0.001 Medical factors  →  Primary impairments − 1.585 − 0.792 − 2.378 − 0.649 − 0.721 − 0.577  < 0.001 Medical factors  →  Secondary impairments − 0.391 − 0.173 − 0.610 − 0.172 − 0.265 − 0.079 0.002 Primary impairments  →  Secondary impairments 0.744 0.393 1.095 0.800 0.723 0.877  < 0.001 Quantity of rehabilitation  →  Secondary impairments − 0.254 − 0.116 − 0.392 − 0.121 − 0.181 − 0.060 0.001 Primary impairments  →  Activity limitations 0.418 0.186 0.650 0.452 0.270 0.634  < 0.001 Environmental factors  →  Activity limitations − 1.181 − 0.490 − 1.871 − 0.523 − 0.721 − 0.324  < 0.001 Environmental factors  →  Quantity of rehabilitation − 0.406 − 0.511 − 0.301 − 0.376 − 0.460 − 0.293  < 0.001 Quantity of rehabilitation  →  Quality of rehabilitation 0.844 0.712 0.976 0.680 0.620 0.741  < 0.001 Personal factors  →  Quality of rehabilitation 0.262 0.106 0.417 0.195 0.086 0.305

Unilateral neck muscle vibration (NMV) activates the primary endings of muscle spindles and modulates both subjective visual vertical and subjective straight-ahead perception. However, its effects on subjective postural vertical (SPV), crucial for postural balance, remain poorly understood. We aimed to investigate the effects of unilateral NMV-induced proprioceptive stimulation on SPV tilt direction and intraindividual variability in the frontal plane in healthy participants. We included 48 healthy adults (29 males, 19 females; age 22.5 ± 1.1 years; height 167.7 ± 7.4 cm; weight 58.7 ± 8.4 kg), randomly divided into four groups: vibrations to the left (L-Vib) and right sides (R-Vib), as well as sham stimulations to the left (L-Sham) and right (R-Sham). Vibration was applied for 10 min at 80 Hz with an amplitude of 0.8 mm. SPV was measured using a motorized vertical-tilting chair equipped with a backrest and lateral supports. Participants were seated without ground contact, with their trunk fixed and arms crossed; the ir head and legs re mained unrestrained. The experimenter tilted the chair from an initial position of 15° or 20° in the frontal plane toward the vertical at a speed of 1.5°/s. A digital inclinometer recorded the tilt angle when participants reported their body felt upright. Each session comprised eight trials with pseudorandom starting directions and angles. The mean tilt direction and standard deviation across trials were calculated. SPV was assessed before, during, and after stimulation. A two-way analysis of variance was conducted to analyze the effect s of unilateral NMV on SPV outcomes. There were no significant demographic differences across groups. For SPV tilt direction, there was no statistically significant interaction between group and time. However, for SPV variability, significant effects were observed for time (F1,44 = 9.591, = 0.003, partial η = 0.179) and the interaction between group and time (F6,44 = 2.325, = 0.039, partial η = 0.137). Participants in the L-Vib group exhibited significantly reduced variability both during and after stimulation compared with those in the L-Sham ( = 0.004) and R-Sham ( < 0.001) groups. Similarly, participants in the R-Vib group showed significantly lower variability than those in the R-Sham group ( = 0.02). These findings highlight the role of sensorimotor integration in body orientation and suggest that unilateral NMV may enhance the precision of verticality estimation. Based on this preliminary study, NMV could be a promising intervention for individuals with SPV abnormalities.

Background Upper extremity rehabilitation in persons with stroke should be dose-dependent and task-oriented. Virtual reality (VR) has the potential to be used safely and effectively in home-based rehabilitation. This study aimed to investigate the effects of home-based virtual reality upper extremity rehabilitation in persons with chronic stroke. Methods This was a single-blind, randomized, controlled trial conducted at two centers. The subjects were 14 outpatients with chronic stroke more than 6 months after the onset of the stroke. The participants were randomly divided into two groups. The intervention group (n = 7) performed a home rehabilitation program for the paretic hand (30 min/day, five days/week) using a VR device (RAPAEL Smart Glove™; NEOFECT Co., Yung-in, Korea) for four weeks. The control group (n = 7) participated in a conventional home rehabilitation program at the same frequency. All participants received outpatient occupational therapy once a week during the study period. The outcome measures included the Fugl-Meyer Assessment of upper extremity motor function (FMA-UE), Motor Activity Log-14 (MAL), Jebsen-Taylor Hand Function Test (JTT), and Box and Block Test (BBT) scores. Results All 14 participants completed the study. Compared to the control group, the intervention group showed more significant improvements in FMA-UE (p = 0.027), MAL (p = 0.014), JTT (p = 0.002), and BBT (p = 0.014). No adverse events were observed during or after the intervention. Conclusion Compared to a conventional home program, combining a task-oriented virtual reality home program and outpatient occupational therapy might lead to greater improvements in upper extremity function and the frequency of use of the paretic hand. Trial registration : This study was registered in the University Hospital Medical Information Network (UMIN) Clinical Trial Registry in Japan (Unique Identifier: UMIN000038469) on November 1, 2019; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000043836 .

Reciprocal inhibition (RI) between leg muscles is crucial for smooth movement. Pedaling is a rhythmic movement that can increase RI in healthy individuals. Transcutaneous spinal cord stimulation (tSCS) stimulates spinal neural circuits by targeting the afferent fibers. Pedaling with simultaneous tSCS may modulate the plasticity of the spinal neural circuit and alter neural activity based on movement and muscle engagement. This study investigated the RI changes after pedaling and tSCS and determined the phase of pedaling in which tSCS should be applied for optimal RI modulation in healthy individuals. Eleven subjects underwent three interventions: pedaling combined with tSCS during the early phase of lower extension (phase 1), pedaling combined with tSCS during the late phase of lower flexion (phase 4) of the pedaling cycle, and pedaling combined with sham tSCS. The RI from the tibialis anterior to the soleus muscle was assessed before, immediately after, 15 min, and 30 min after the intervention. RI increased immediately after phase 4 and pedaling combined with sham tSCS, whereas no changes were observed after phase 1. These results demonstrate that tSCS modulates RI changes induced by pedaling in a stimulus phase-dependent manner in healthy individuals. However, the mechanism involved in this intervention needs to be explored to achieve higher efficacy.

An association between respiratory muscle weakness and sarcopenia may provide a clue to the mechanism of sarcopenia development. We aimed to clarify this relationship among community-dwelling older adults. In total, 117 community-dwelling older adults were assessed and classified into 4 groups: robust, respiratory muscle weakness, sarcopenia, and respiratory sarcopenia. The respiratory sarcopenia group (12%) had a significantly higher percentage of males and had lower BMI, skeletal muscle index, skeletal muscle mass, phase angle, and oral function than the robust group (32.5%). All physical functions were significantly lower. The respiratory muscle weakness group (54.7%) had a significantly lower BMI and slower walking speed, compared with the robust group. The sarcopenia group (0.8%) was excluded from the analysis. The percent maximum inspiratory pressure was significantly lower in both the respiratory muscle weakness and respiratory sarcopenia groups, compared with the robust group. Almost all participants with sarcopenia showed respiratory muscle weakness. In addition, approximately 50% had respiratory muscle weakness, even in the absence of systemic sarcopenia, suggesting that respiratory muscle weakness may be the precursor of sarcopenia. The values indicating physical function and skeletal muscle mass in the respiratory muscle weakness group were between those in the robust and the respiratory sarcopenia groups.

The present study aimed to determine the magnitude of and risk factors for the effects of the COVID-19 pandemic on the international classification of functioning, disability and health (ICF) in patients with multiple system atrophy (PwMSA). The study was part of a cross-sectional, nationwide, multipurpose mail survey for Japanese PwMSA from October to December, 2020. The primary outcome was the impact of the early COVID-19 pandemic on ICF functioning, consisting of body function, activity, and participation. Age, sex, disease type, disease duration, and dwelling place were asked as participants’ characteristics, and the multiple system impairment questionnaire (MSIQ), patient health questionnaire-2, modified rankin scale, barthel index, life-space assessment (LSA), and EuroQoL were examined. Multivariate logistic regression analyses were performed to identify independent risk factors for a worse function score due to the COVID-19 pandemic for each ICF functioning domain. A total of 155 patients (mean age 65.6 [SD 8.1] years; 43.9% women; mean disease duration 8.0 [SD 6.2] years; 65% MSA with cerebellar ataxia, 13% MSA with parkinsonism, 9% MSA with predominant autonomic features) were analyzed. Of the ICF functioning domains, the respondents reported that the early COVID-19 pandemic affected body function in 17.4%, activity in 17.6%, and participation in 46.0%. The adjusted multivariate model identified MSIQ and LSA as the two variables that independently contributed to all domains. The COVID-19 pandemic affected ICF functioning of PwMSA in Japan, and the severity of disease-related impairments and a large daily living space were common risk factors. These results help support the focus on patient characteristics for medical and social welfare support.

Recent advancements have made two-dimensional (2D) clinical gait analysis systems more accessible and portable than traditional three-dimensional (3D) clinical systems. This study evaluates the reliability and validity of gait measurements using monocular and composite camera setups with VisionPose, comparing them to the Vicon 3D motion capture system as a reference. Key gait parameters—including hip and knee joint angles, and time and distance factors—were assessed under normal, maximum speed, and tandem gait conditions during level walking. The results show that the intraclass correlation coefficient (ICC(1,k)) for the 2D model exceeded 0.969 for the monocular camera and 0.963 for the composite camera for gait parameters. Time–distance gait parameters demonstrated excellent relative agreement across walking styles, while joint range of motion showed overall strong agreement. However, accuracy was lower for measurements during tandem walking. The Cronbach’s alpha coefficient for time–distance parameters ranged from 0.932 to 0.999 (monocular) and from 0.823 to 0.998 (composite). In contrast, for joint range of motion, the coefficient varied more widely, ranging from 0.826 to 0.985 (monocular) and from 0.314 to 0.974 (composite). The correlation coefficients for spatiotemporal gait parameters were greater than 0.933 (monocular) and 0.837 (composite). However, for joint angle parameters, the coefficients were lower during tandem walking. This study underscores the potential of 2D models in clinical applications and highlights areas for improvement to enhance their reliability and application scope.