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 + $A$ * 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.