Development of a Mobile Gait Trainer Using Pose Estimation


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Date

2025

Publication Type

Conference Paper

ETH Bibliography

yes

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Abstract

Patients with neurological disorders often have gait impairments. This work aimed to develop a computer-vision-based mobile gait trainer which supports users during free overground walking. The mobile gait trainer consists of three submodules: a Mecanum-wheel-driven frame with a body-weight-support (BWS) mechanism, a pose estimation module and a motor control system. Secured by the BWS, the user walked overground at preferred speeds. The webcam on the top frame estimated the shoulder movement based on the MMPose algorithms. Kinematic analysis yielded the target speeds for the trainer to follow the user. The motor control algorithms enabled the BWS to relieve the target load and the trainer to move. Preliminary test showed that the BWS mechanism produced a mean force control error of 2.03% for free walking, and 4.57% during obstacle climbing. The trainer followed the user with a speed error of 0.17 m/s. It was concluded that the trainer managed to support free overground walking.

Publication status

published

Book title

Converging Clinical and Engineering Research on Neurorehabilitation V. ICNR 2024

Volume

31

Pages / Article No.

541 - 545

Publisher

Springer

Event

6th International Conference on NeuroRehabilitation (ICNR 2024)

Edition / version

First Edition

Methods

Software

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Organisational unit

03654 - Riener, Robert / Riener, Robert check_circle

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