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Background: Clinical gait analysis (CGA) is a systematic approach to comprehensively evaluate gait patterns, quantify impairments, plan targeted interventions, and evaluate the impact of interventions. However, international standards for CGA are currently lacking, resulting in various national initiatives. Standards are important to ensure safe and effective healthcare practices and to enable evidence-based clinical decision-making, facilitating interoperability, and reimbursement under national healthcare policies. Collaborative clinical and research work between European countries would benefit from common standards., Research Objective: This study aimed to review the current laboratory practices for CGA in Europe., Methods: A comprehensive survey was conducted by the European Society for Movement Analysis in Adults and Children (ESMAC), in close collaboration with the European national societies. The survey involved 97 gait laboratories across 16 countries. The survey assessed several aspects related to CGA, including equipment used, data collection, processing, and reporting methods., Results: There was a consensus between laboratories concerning the data collected during CGA. The Conventional Gait Model (CGM) was the most used biomechanical model for calculating kinematics and kinetics. Respondents also reported the use of video recording, 3D motion capture systems, force plates, and surface electromyography. While there was a consensus on the reporting of CGA data, variations were reported in training, documentation, data preprocessing and equipment maintenance practices., Significance: The findings of this study will serve as a foundation for the development of standardized guidelines for CGA in Europe., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on evaluating gait patterns within short walking distances. However, assessment of gait consistency requires testing over a longer walking distance. The aim of this study is to validate the accuracy for gait assessment of a previously developed method that determines walking spatiotemporal parameters and kinematics measured with a 3D camera mounted on a mobile robot base (ROBOGait). Walking parameters measured with this system were compared with measurements with Xsens IMUs. The experiments were performed on a non-linear corridor of approximately 50 m, resembling the environment of a conventional rehabilitation facility. Eleven individuals exhibiting normal motor function were recruited to walk and to simulate gait patterns representative of common neurological conditions: Cerebral Palsy, Multiple Sclerosis, and Cerebellar Ataxia. Generalized estimating equations were used to determine statistical differences between the measurement systems and between walking conditions. When comparing walking parameters between paired measures of the systems, significant differences were found for eight out of 18 descriptors: range of motion (ROM) of trunk and pelvis tilt, maximum knee flexion in loading response, knee position at toe-off, stride length, step time, cadence; and stance duration. When analyzing how ROBOGait can distinguish simulated pathological gait from physiological gait, a mean accuracy of 70.4%, a sensitivity of 49.3%, and a specificity of 74.4% were found when compared with the Xsens system. The most important gait abnormalities related to the clinical conditions were successfully detected by ROBOGait. The descriptors that best distinguished simulated pathological walking from normal walking in both systems were step width and stride length. This study underscores the promising potential of 3D cameras and encourages exploring their use in clinical gait analysis.

Aim: To explore whether subgroups of adults with cerebral palsy (CP) with different fatigue diurnal profiles can be discerned, and to explore whether sleep, physical activity, or health-related fitness are associated with these profiles., Method: Thirty-two adults (median age 29 years 8 months; range 20-54 years; 11 males, 21 females) with spastic CP (Gross Motor Function Classification System levels I-III) with physical activity-related fatigue complaints participated. Real-time fatigue and physical activity were assessed for 7 consecutive days by short message service text four times during the day and by wearing an accelerometer respectively. Sleep was assessed by the Pittsburgh Sleep Quality Index, and fitness by assessing body composition and aerobic capacity. Latent class growth modelling was used to classify subgroups according to their diurnal profiles of real-time fatigue. Univariable multinomial logistic regression analysis explored whether participant characteristics, sleep, physical activity, or health-related fitness were associated with diurnal profiles., Results: Three distinct fatigue diurnal profiles were identified: stable low (n = 10), increasing (n = 14), and stable high (n = 8). Only aerobic capacity was associated with fatigue profiles (odds ratio 1.15, 95% confidence interval 1.00-1.34; p = 0.05)., Interpretation: Fatigue in adults with CP may be low or high stable or may increase during the day. These findings indicate the relevance of assessing fatigue variability., What This Paper Adds: We found three patterns of daily fatigue in adults with cerebral palsy (CP). Only aerobic capacity was associated with fatigue profiles in adults with CP. Moment-to-moment variations in fatigue can help with personalized fatigue management., (© 2022 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.)

Purpose: To evaluate the effects of a combination of wheelchair mobility skills (WMS) training and exercise training on physical activity (PA), WMS, confidence in wheelchair mobility, and physical fitness., Methods: Y outh using a manual wheelchair ( n  = 60) participated in this practice-based intervention, with a waiting list period (16 weeks), exercise training (8 weeks), WMS training (8 weeks), and follow-up (16 weeks). Repeated measures included: PA (Activ8), WMS (Utrecht Pediatric Wheelchair Mobility Skills Test), confidence in wheelchair mobility (Wheelchair Mobility Confidence Scale), and physical fitness (cardiorespiratory fitness, (an)aerobic performance) and were analysed per outcome parameter using a multilevel model analyses. Differences between the waiting list and training period were determined with an unpaired sample t -test., Results: Multilevel model analysis showed significant positive effects for PA ( p  = 0.01), WMS ( p  < 0.001), confidence in wheelchair mobility ( p  < 0.001), aerobic ( p  < 0.001), and anaerobic performance ( p  < 0.001). Unpaired sample t -tests underscored these effects for PA ( p  < 0.01) and WMS ( p  < 0.001). There were no effects on cardiorespiratory fitness. The order of training (exercise before WMS) had a significant effect on confidence in wheelchair mobility., Conclusions: A combination of exercise and WMS training appears to have significant positive long-term effects on PA, WMS, confidence in wheelchair mobility, and (an)aerobic performance in youth using a manual wheelchair.Implications for rehabilitationExercise training and wheelchair mobility skills (WMS) training can lead to a sustained improvement in physical activity (PA) in youth using a manual wheelchair.These combined trainings can also lead to a sustained increase in WMS, confidence in wheelchair mobility, and (an)aerobic performance.More attention is needed in clinical practice and in research towards improving PA in youth using a manual wheelchair.

Trunk motor control is essential for the proper functioning of the upper extremities and is an important predictor of gait capacity in children with delayed development. Early diagnosis and intervention could increase the trunk motor capabilities in later life, but current tools used to assess the level of trunk motor control are largely subjective and many lack the sensitivity to accurately monitor development and the effects of therapy. Inertial measurement units could yield an objective quantitative assessment that is inexpensive and easy-to-implement. We hypothesized that root mean square of jerk, a proxy for movement smoothness, could be used to distinguish age and thereby presumed motor development. We attached a sensor to the trunks of six young children with no known developmental deficits. Root mean square of jerk decreases with age, up to 24 months, and is correlated to a more established method, i.e., center-of-pressure velocity, as well as other standard inertial measurement unit outputs. This metric therefore shows potential as a method to differentiate trunk motor control levels.