Self-paced regulation of treadmill speed using model predictive control
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Date
2025-06
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University of New Brunswick
Abstract
A self-paced treadmill is a powerful tool enabling users, especially those with gait abnormalities, to perform clinical gait analysis at their own comfortable speed, unlike a fixed-speed treadmill. It comprises two components: position estimation and controller design. Position estimation determines the participant's real-time location, while the controller adjusts the speed based on location data. This study utilized a model predictive controller to forecast the user's walking state and employed two position estimation methods: marker-based (requiring the participant to wear markers) and markerless (embedded in CAREN system belts). To evaluate the designed self-paced treadmill, healthy adult participants walked on it in a simulated New York City environment, completing three trials and filling out a questionnaire afterward. Results indicated that participants felt more comfortable with the marker-based method, although the markerless method scored closely.