Real-Time Hand Motion Recognition Using sEMG Patterns Classification

被引：0
|
作者：
Crepin, Roxane [1 ]
Fall, Cheikh Latyr [1 ]
Mascret, Quentin [1 ]
Gosselin, Clement [2 ]
Campeau-Lecours, Alexandre [2 ]
Gosselin, Benoit [1 ]
机构：
[1] Univ Laval, Dept Comp & Elect Engn, Quebec City, PQ G1V 0A6, Canada
[2] Univ Laval, Dept Mech Engn, Quebec City, PQ G1V 0A6, Canada
来源：
2018 40TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2018年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Myoelectric prostheses; sEMG signals; Analog Front-End; Classifier; Linear Discriminant Analysis; Real-Time;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Increasing performance while decreasing the cost of sEMG prostheses is an important milestone in rehabilitation engineering. The different types of prosthetic hands that are currently available to patients worldwide can benefit from more effective and intuitive control. This paper presents a real-time approach to classify finger motions based on surface electromyography (sEMG) signals. A multichannel signal acquisition platform implemented using components off the shelf is used to record forearm sEMG signals from 7 channels. sEMG pattern classification is performed in real time, using a Linear Discriminant Analysis approach. Thirteen hand motions can be successfully identified with an accuracy of up to 95.8% and of 92.7% on average for 8 participants, with an updated prediction every 192 ms.
引用
收藏
页码：2655 / 2658
页数：4
相关论文
共 50 条
  • [21] Feasibility of Wrist-Worn, Real-Time Hand, and Surface Gesture Recognition via sEMG and IMU Sensing
    Jiang, Shuo
    Lv, Bo
    Guo, Weichao
    Zhang, Chao
    Wang, Haitao
    Sheng, Xinjun
    Shull, Peter B.
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (08) : 3376 - 3385
  • [22] Real-time Hand Finger Motion Capturing using Regression Forest
    Hsieh, Pei-Chi
    Hsu, Shih-Chung
    Huang, Chung-Lin
    2016 INTERNATIONAL COMPUTER SYMPOSIUM (ICS), 2016, : 419 - 424
  • [23] Real-time hand posture recognition using hand geometric features and Fisher Vector'
    Fang, Linpu
    Liang, Ningxin
    Kang, Wenxiong
    Wang, Zhiyong
    Feng, David Dagan
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2020, 82
  • [24] REAL-TIME HAND POSTURE RECOGNITION BASED ON HAND DOMINANT LINE USING KINECT
    Wang, Yue
    Yang, Ruoyu
    ELECTRONIC PROCEEDINGS OF THE 2013 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 2013,
  • [25] Real-Time Hand Gesture Recognition for Robot Hand Interface
    Lv, Xiaomeng
    Xu, Yulin
    Wang, Ming
    LIFE SYSTEM MODELING AND SIMULATION, 2014, 461 : 209 - 214
  • [26] Real-time hand gesture recognition for robot hand interface
    Lv, Xiaomeng
    Xu, Yulin
    Wang, Ming
    Communications in Computer and Information Science, 2014, 461 : 209 - 214
  • [27] Real-Time Robotic Hand Control Using Human Gesture Recognition
    Egipko, V
    Voronin, V.
    Gapon, N.
    Zhdanova, M.
    Semenishchev, E.
    Zelensky, A.
    REAL-TIME IMAGE PROCESSING AND DEEP LEARNING 2023, 2023, 12528
  • [28] Extraction and classification of visual motion patterns for hand gesture recognition
    Yang, MH
    Ahuja, N
    1998 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1998, : 892 - 897
  • [29] Real-Time Hand Gesture Recognition With EMG Using Machine Learning
    Jaramillo, Andres G.
    Benalcazar, Marco E.
    2017 IEEE SECOND ECUADOR TECHNICAL CHAPTERS MEETING (ETCM), 2017,
  • [30] A Real-time Hand Gesture Recognition Approach Based on Motion Features of Feature Points
    She, Yingying
    Wang, Qian
    Jia, Yunzhe
    Gu, Ting
    He, Qun
    Yang, Baorong
    2014 IEEE 17TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE), 2014, : 1096 - 1102
12345