Wheelchair biomechanics research advances accessibility and clinical care for manual wheelchair users. Standardized outcome assessments are vital tools for tracking progress, but there is a strong need for more quantitative methods. A system offering kinematic, quantitative detection, with the ease of use of a standardized outcome assessment, would be optimal for repeated, longitudinal assessment of manual wheelchair users’ therapeutic progress, but has yet to be offered. This work evaluates a markerless motion analysis system for manual wheelchair mobility in clinical, community, and home settings. This system includes Microsoft® Kinect® 2.0 sensors, OpenSim musculoskeletal modeling, and an automated detection, processing, and training interface. The system is designed to be cost-effective, easily used by caregivers, and capable of detecting key kinematic metrics involved in manual wheelchair propulsion. The primary technical advancements in this research are the software components necessary to detect and process the upper extremity kinematics during manual wheelchair propulsion, along with integration of the components into a complete system. The study defines and evaluates an adaptable systems methodology for processing kinematic data using motion capture technology and open-source musculoskeletal models to assess wheelchair propulsion pattern and biomechanics, and characterizes its accuracy, sensitivity and repeatability. Inter-trial repeatability of spatiotemporal parameters, joint range of motion, and musculotendon excursion were all found to be significantly correlated (p < 0.05). The system is recommended for use in clinical settings for frequent wheelchair propulsion assessment, provided the limitations in precision are considered. The motion capture-model software bridge methodology could be applied in the future to any motion-capture system or specific application, broadening access to detailed kinematics while reducing assessment time and cost.

A recently developed and evaluated upper extremity (UE) markerless motion analysis system based on the Microsoft® Kinect® has potential for improving functional assessment of patients with hemiplegic cerebral palsy. 12 typically-developing adolescents ages 12–17 were evaluated using both the Kinect-based system and the Shriners Hospitals for Children Upper Extremity Evaluation (SHUEE), a validated measure of UE motion. The study established population means of UE kinematic parameters for each activity. Statistical correlation analysis was used to identify key kinematic metrics used to develop automatic scoring algorithms. The Kinect motion analysis platform is technically sound and can be applied to standardized task-based UE evaluation while providing enhanced sensitivity in clinical analysis and automation through scoring algorithms.

Manual wheelchair users (MWUs) are prone to a sedentary life that can negatively affect their physical and cardiovascular health, making regular assessment important to identify appropriate interventions and lifestyle modifications. One mean of assessing MWUs’ physical health is the 6 min push test (6MPT), where the user propels themselves as far as they can in six minutes. However, reliance on observer input introduces subjectivity, while limited quantitative data inhibit comprehensive assessment. Incorporating sensors into the 6MPT can address these limitations. Here, ten MWUs performed the 6MPT with additional sensors: two inertial measurement units (IMUs)—one on the wheelchair and one on the wrist together with a heart rate wristwatch. The conventional measurements of distance and laps were recorded by the observer, and the IMU data were used to calculate laps, distance, speed, and cadence. The results demonstrated that the IMU can provide the metrics of the traditional 6MPT with strong significant correlations between calculated laps and observer lap counts (r = 0.947, p < 0.001) and distances (r = 0.970, p < 0.001). Moreover, heart rate during the final minute was significantly correlated with calculated distance (r = 0.762, p = 0.017). Enhanced 6MPT assessment can provide objective, quantitative, and comprehensive data for clinicians to effectively inform interventions in rehabilitation.

Purpose: Children who use manual wheelchairs encounter pain and injury risks to the upper body. Current literature does not describe how propulsion pattern and physiotherapeutic training methodologies impact response to treatment. Methods: This study assesses the effect of community-based intensive physical and occupational therapy on functional outcomes over a 7-week period in pediatric manual wheelchair users. Results: Key results include significant joint and musculotendon kinematic differences at the shoulder, improved speed and propulsion effectiveness, and changed propulsion pattern. Conclusions: Statistics also revealed that propulsion pattern was a predictor of response to therapy, as was weekly therapeutic duration, wheelchair-specific focus by the therapists, and stretching.

Given the unique challenges faced by manual wheelchair users, improving methods to accurately measure and enhance their participation in community life is critical. This study explores a comprehensive method to evaluate the real-world community mobility and participation of manual wheelchair users by combining GPS mobility tracking, heart rate, and activity journals. Collecting qualitative and quantitative measures such as the life space assessment, wheelchair user confidence scale, and physical performance tests alongside GPS mobility tracking from ten manual wheelchair users provided insight into the complex relationship between physical, psychological, and social factors that can impact their daily community mobility and participation. This study found significant, strong correlations between the recorded journal time outside of the home and the GPS mean daily heart rate (r = −0.750, p = 0.032) as well as between the upper limb strength assessments with cardiovascular assessments, physiological confidence, and GPS participation indicators (0.732 < r < 0.884, 0.002 < p < 0.039). This method of manual wheelchair user assessment reveals the complex relationships between different aspects of mobility and participation. It provides a means of enhancing the ability of rehabilitation specialists to focus rehabilitation programs toward the areas that will help manual wheelchair users improve their quality of life.

Pathologic movement patterns are characterized by abnormal kinematics that alter how muscles support the body during walking. Individual muscles are often the target of interventions with physical therapy and surgery alike, yet the tools to assess individual muscles clinically remain limited. The aim of this study is to assess OpenSim as a clinical tool for individualized rehabilitative evaluation of children using orthotics. This anatomic and kinematic modeling study was focused on pre- and post-treatment assessment of gait characteristics in fourteen children using orthotic devices. A range of four to twelve acceptable gait capture trials was collected for each child before therapy began and again after four weeks of treatment. The effects of therapy were significant in four of the lower extremity muscle analyses, three of the temporal parameters, and eighteen of the spatial parameters. All muscle lengths showed less deviation from normal values after physical therapy across all subjects. Results of this study support the further evaluation of OpenSim as a tool to improve quantitative assessment of musculoskeletal dynamics during the course of rehabilitative therapy in children using orthotics.