User-Centric Design of Contactless Smart Wheelchair System for Elderly People

Using hand gesture recognition to improve mobility and independence, the study offers a user-centric design of a contactless wheelchair navigation system suited for senior citizens. The system utilizes the MediaPipe method to extract hand gesture data, allowing navigation based on five predefined gesture categories. By minimizing the necessity for physical contact and hence lowering strain and potential harm, this technique guaranteed users a smooth and intuitive control experience. The wheelchair's control system has been engineered to maneuver efficiently and avoid obstacles (using the SLAM + <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A$</tex> * algorithm), improving user safety and dependability. The proposed navigation system proved helpful in real-world circumstances, with an overall accuracy of 90.23 ± 1.13 %. Furthermore, the hand gesture recognition model demonstrated strong performance in understanding user commands with an accuracy of 91.55 ± 1.55 %. For older adults who require wheelchair navigation that is safe, effective, and user-friendly, this novel approach presented a possible answer.

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Published
2024-12-12
DOI
https://doi.org/10.1109/icac64487.2024.10850958
Primary Topic
Advanced Technologies in Various Fields
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article
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article

User-Centric Design of Contactless Smart Wheelchair System for Elderly People

Udesh Oruthota, S.L.P. Yasakethu, H.M.K.K.M.B. Herath, A.C. Chamalsha et al.
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Advanced Technologies in Various Fields
article

User-Centric Design of Contactless Smart Wheelchair System for Elderly People

Udesh Oruthota, S.L.P. Yasakethu, H.M.K.K.M.B. Herath, A.C. Chamalsha, R.A.K. Nadeeshan
article en

Abstract

Using hand gesture recognition to improve mobility and independence, the study offers a user-centric design of a contactless wheelchair navigation system suited for senior citizens. The system utilizes the MediaPipe method to extract hand gesture data, allowing navigation based on five predefined gesture categories. By minimizing the necessity for physical contact and hence lowering strain and potential harm, this technique guaranteed users a smooth and intuitive control experience. The wheelchair's control system has been engineered to maneuver efficiently and avoid obstacles (using the SLAM + <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A$</tex> * algorithm), improving user safety and dependability. The proposed navigation system proved helpful in real-world circumstances, with an overall accuracy of 90.23 ± 1.13 %. Furthermore, the hand gesture recognition model demonstrated strong performance in understanding user commands with an accuracy of 91.55 ± 1.55 %. For older adults who require wheelchair navigation that is safe, effective, and user-friendly, this novel approach presented a possible answer.

Sri Lanka Institute of Information Technology (LK)
Openalex Percentile: Top 76%
Advanced Technologies in Various Fields
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