TY - GEN
T1 - Application of Gesture Recognition in Finger Rehabilitation Training
AU - Jinyu, Liu
AU - Jie, Li
AU - Yifan, Xia
AU - Yufeng, Zhang
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The hand is one of the essential organs of human beings. For people's daily life, hand injuries will bring much trouble. The traditional finger rehabilitation training method relying on the assistance of medical personnel needs a lot of time and manpower. Therefore, starting from hand target detection, this paper selects a suitable deep learning algorithm to recognize gestures, designs a finger rehabilitation training system platform, and displays sample gesture images and gestures captured by the camera on the operation interface through reasonable layout of the user interface, so that patients can compare their own gestures with correct gestures. The system is faster, more convenient and more labor-saving. It has wide application prospect and practical application value.
AB - The hand is one of the essential organs of human beings. For people's daily life, hand injuries will bring much trouble. The traditional finger rehabilitation training method relying on the assistance of medical personnel needs a lot of time and manpower. Therefore, starting from hand target detection, this paper selects a suitable deep learning algorithm to recognize gestures, designs a finger rehabilitation training system platform, and displays sample gesture images and gestures captured by the camera on the operation interface through reasonable layout of the user interface, so that patients can compare their own gestures with correct gestures. The system is faster, more convenient and more labor-saving. It has wide application prospect and practical application value.
KW - Artificial intelligence
KW - Convolutional neural network
KW - Gesture recognition
KW - Interface design
KW - YOLOv5
UR - https://www.scopus.com/pages/publications/105007285201
U2 - 10.1109/AISOMT64170.2024.10992127
DO - 10.1109/AISOMT64170.2024.10992127
M3 - 会议稿件
AN - SCOPUS:105007285201
T3 - 2024 IEEE Academic International Symposium on Optoelectronics and Microelectronics Technology, AISOMT 2024
SP - 444
EP - 448
BT - 2024 IEEE Academic International Symposium on Optoelectronics and Microelectronics Technology, AISOMT 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE Academic International Symposium on Optoelectronics and Microelectronics Technology, AISOMT 2024
Y2 - 21 November 2024 through 22 November 2024
ER -