Observational studyAnnals of biomedical engineering2025
The Relation Between Hemiparetic Gait Patterns and Walking Function After Stroke, as Measured with Wearable Sensors.
Observational study in Annals of biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The trial behind it
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Who cites it
2 citing papers in PubMed.
- Smart Sensor-Driven Gait Rehabilitation Walker Using Machine Learning for Predictive Home-Based Therapy.Sensors (Basel, Switzerland) · 2026Article
- Design, Modeling, and Testing-A Compact Variable-Stiffness Actuator for Knee Joint Dimensions.Micromachines · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
purposeAfter stroke, walking is characterized by hemiparetic patterns, quantified with force sensitive walkways and motion capture systems. Some joint-level kinematic patterns of walking also can be obtained with wearable sensors. The purpose of this project was to measure joint-level kinematic patterns during walking with wearable sensors and determine the association with walking speed and endurance in individuals with chronic stroke.
methodsIn this cross-sectional observational study, participants donned APDM Opal wearable sensors during walking tests (10-meter walk test or 6-min walk test). We extracted joint-level kinematic variables of elevation at midswing, circumduction, foot strike angle, and toe-off angle. Associations of each variable with walking speed and endurance were tested, and significantly associated variables were entered into a regression model.
results68 individuals with chronic stroke were included. We found that the less affected foot strike angle, less affected toe-off angle, and more affected toe-off angle were significant predictors of walking speed (R
conclusionWe found consistent evidence that greater toe-off angle (may reflect greater push-off) and lesser foot strike angle (may reflect lesser foot drop) were important predictors of greater walking speed and endurance. Our results suggest that wearable sensors can provide important information about joint-level kinematic patterns that are important for walking function. This information could help therapists target interventions toward specific deficits or compensatory patterns to improve walking.
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