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Design and validation of an intelligent wheelchair towards a clinically-functional outcome

Patrice Boucher, Amin Atrash, Sousso Kelouwani, Wormser Honoré, Hai Nguyen, Julien Villemure, François Routhier, Paul Cohen, Louise Demers, Robert Forget and Joelle Pineau

Article (2013)

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Terms of Use: Creative Commons Attribution.
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Cite this document: Boucher, P., Atrash, A., Kelouwani, S., Honoré, W., Nguyen, H., Villemure, J., ... Pineau, J. (2013). Design and validation of an intelligent wheelchair towards a clinically-functional outcome. Journal of NeuroEngineering and Rehabilitation, 10. doi:10.1186/1743-0003-10-58
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Background: Many people with mobility impairments, who require the use of powered wheelchairs, have difficulty completing basic maneuvering tasks during their activities of daily living (ADL). In order to provide assistance to this population, robotic and intelligent system technologies have been used to design an intelligent powered wheelchair (IPW). This paper provides a comprehensive overview of the design and validation of the IPW. Methods: The main contributions of this work are three-fold. First, we present a software architecture for robot navigation and control in constrained spaces. Second, we describe a decision-theoretic approach for achieving robust speech-based control of the intelligent wheelchair. Third, we present an evaluation protocol motivated by a meaningful clinical outcome, in the form of the Robotic Wheelchair Skills Test (RWST). This allows us to perform a thorough characterization of the performance and safety of the system, involving 17 test subjects (8 non-PW users, 9 regular PW users), 32 complete RWST sessions, 25 total hours of testing, and 9 kilometers of total running distance. Results: User tests with the RWST show that the navigation architecture reduced collisions by more than 60% compared to other recent intelligent wheelchair platforms. On the tasks of the RWST, we measured an average decrease of 4% in performance score and 3% in safety score (not statistically significant), compared to the scores obtained with conventional driving model. This analysis was performed with regular users that had over 6 years of wheelchair driving experience, compared to approximately one half-hour of training with the autonomous mode.Conclusions: The platform tested in these experiments is among the most experimentally validated robotic wheelchairs in realistic contexts. The results establish that proficient powered wheelchair users can achieve the same level of performance with the intelligent command mode, as with the conventional command mode.

Uncontrolled Keywords

Adult; Aged; Aged, 80 and over; Artificial Intelligence; Disabled Persons; Equipment Design; Female; Humans; Male; Middle Aged; Robotics; Software; Treatment Outcome; User-Computer Interface; Wheelchairs; Assistive robotics; Intelligent powered wheelchairs; wheelchair skill test

Open Access document in PolyPublie
Subjects: 2500 Génie électrique et électronique > 2500 Génie électrique et électronique
Department: Département de génie électrique
Research Center: Non applicable
Funders: Canadian Foundation for Innovation (CFI), CRSNG / NSERC, Canadian Institutes for Health Research (via CanWheel Team), Fonds québécois de a recherche sur la nature et les technologies (via REPARTI et INTER), Fondation du Centre de réadaptation Lucie Bruneau, Fondation Constante Lethbridge, Robovic
Date Deposited: 15 Jan 2019 12:40
Last Modified: 16 Jan 2019 01:20
PolyPublie URL: https://publications.polymtl.ca/3439/
Document issued by the official publisher
Journal Title: Journal of NeuroEngineering and Rehabilitation (vol. 10)
Publisher: BioMed Central Ltd
Official URL: https://doi.org/10.1186/1743-0003-10-58


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