EventsThe 6th International Electronic Conference on Applied Sciences
Published
This submission belongs to the session S1. Applied Biosciences and Bioengineering of the event The 6th International Electronic Conference on Applied Sciences
Published date
03 Dec, 2025
Academic Editor
author-avatarRoger Narayan
Citation
King-Pong YU, Chi-Chau Chan, Kwok-Keung Chan, Fai Poon, Ka-Leung Chan, Wai-Ling Ma, Evaluating the Effectiveness of a Boundary Detection System (BDS) for Indoor Wheelchair Training, in Proceedings of The 6th International Electronic Conference on Applied Sciences, 9 December–11 December 2025, MDPI: Basel, Switzerland
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Evaluating the Effectiveness of a Boundary Detection System (BDS) for Indoor Wheelchair Training

Chi-Chau Chan 1
Kwok-Keung Chan 1
Fai Poon 1
Ka-Leung Chan 1
Wai-Ling Ma 1
1. Community Rehabilitation Service Support Center (CRSSC), Hospital Authority, Hong Kong, 999077, China, Hong Kong
Abstract

Powered wheelchair maneuvering skill is essential for independence and safety in people with mobility impairment. However, real-time monitoring of maneuver compliance under training or assessment is challenging for therapists, affecting intervention effectiveness and assessment objectiveness. To overcome this and digitalize users' performance, rehabilitation engineers at the Hospital Authority Community Rehabilitation Service Support Centre (CRSSC) created a Boundary Detection System (BDS); this study assesses the effectiveness of the BDS, comparing system and manual counting.

BDS utilized wheelchair-clamped webcams recording real-time video of wheels and boundaries. Through computer vision algorithms, wheels (grey) and boundaries (yellow) were separated through color filtering, with contours identified using binary masking. Boundary violations were registered when wheel contours intersected a dilated boundary contour during indoor training within a training area. Subjects were asked to complete clockwise and counterclockwise circles for three laps without cues. Human ethics approval was acquired from the Central Institutional Review Board (Ref. No. KC/KE-23-0216/ER-1).

In total, 13 male and 13 female (mean age=67.3±10.2) wheelchair users were recruited. The system-detected boundary violations (8.74 ± 7.25) differ significantly (p < 0.001) from the manual counting method (7.22 ± 6.86), representing the high sensitivity of the proposed system. Overall, an average of 2.64 ± 2.48 boundary violations that lasted less than 0.5 seconds wascaptured by the system and validated by video inspection, which shows the system’s ability to eliminate human error.

This pilot study illustrates the viability of the BDS as a computer vision-based, scalable solution for objective wheelchair training monitoring. Future research will advance algorithmic accuracy and investigate integrations with clinical rehabilitation practice to modernize intervention effectiveness and objectiveness.

Keywords
rehabilitation
wheelchair training
computer vision
biomedical engineering
BDS
Poster
BDS Conference Poster.pdf
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