EMG Signal Decoded Based Virtual Artificial Intelligence Hand Control System

被引:0
|
作者
Yu, Long [1 ]
Gen, Yanjuan [1 ]
Tao, Dandan [1 ]
Zhou, Guodong [1 ]
Chen, Liang [1 ]
Li, Guanglin [1 ]
Wu, Lushen [2 ]
机构
[1] Univ Town Shenzhen, 1068 Xueyuan Blvd, Shenzhen 518055, Peoples R China
[2] Univ Nanchang, Sch Mechatron Engn, Nanchang, Jiangxi, Peoples R China
来源
关键词
Electromyography; virtual reality technology; multifunctional prosthesis control; Artificial intelligence;
D O I
10.4028/www.scientific.net/AMR.268-270.422
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An electromyography (EMG) decoded based virtual artificial intelligence control system has been developed to quantify the performance of real-time control of a multifunctional myoelectric prosthesis. To develop this platform system, a three-dimensional upper limb was simulated by using Solidworks and then implemented into an integrated scene of virtual artificial limb,which was programmed in virtual reality modeling language (VRML) and performed through Simulink toolbox of the MATLAB. By decoding surface electromyography (sEMG) signals collected from arm muscle surface, the platform system can identify thesix classes of different arm and hand movements and control the virtual artificial limb and/or the physical arms simultaneously. The VR-based platform also provides a relaxant and enjoyable training environment for prosthesis-users in clinic.
引用
收藏
页码:422 / +
页数:2
相关论文
共 50 条
  • [31] Multi run ICA and surface EMG based signal processing system for recognising hand gestures
    Naik, Ganesh R.
    Kumar, Dinesh K.
    Palaniswami, Marimuthu
    2008 IEEE 8TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, VOLS 1 AND 2, 2008, : 700 - +
  • [32] EMG Signal based Control of an Intelligent Wheelchair
    Mahendran, Rampriya
    2014 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), 2014,
  • [33] Artificial Intelligence-Based Control Design for Reliable Virtual Synchronous Generators
    Xu, Qianwen
    Dragicevic, Tomislav
    Xie, Lihua
    Blaabjerg, Frede
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2021, 36 (08) : 9453 - 9464
  • [34] Review on System Identification, Control, and Optimization Based on Artificial Intelligence
    Yu, Pan
    Wan, Hui
    Zhang, Bozhi
    Wu, Qiang
    Zhao, Bohao
    Xu, Chen
    Yang, Shangbin
    MATHEMATICS, 2025, 13 (06)
  • [35] Synthesis of Induction Brazing System Control Based on Artificial Intelligence
    Grozdanov, Dragomir
    Gilev, Bogdan
    Hinov, Nikolay
    ELECTRONICS, 2021, 10 (10)
  • [36] EMG Based Control of Individual Fingers of Robotic Hand
    Naseer, Noman
    Ali, Faizan
    Ahmed, Sameer
    Iftikhar, Saad
    Khan, Rayyan Azam
    Nazeer, Hammad
    PROCEEDINGS OF 2018 3RD INTERNATIONAL CONFERENCE ON SUSTAINABLE INFORMATION ENGINEERING AND TECHNOLOGY (SIET 2018), 2018, : 6 - 9
  • [37] Design and Development of Real Time Bionic Hand Control Using EMG Signal
    Praveen, L. S.
    Nagananda, S. N.
    Shankapal, Preetham
    2018 IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTING AND COMMUNICATION TECHNOLOGIES (CONECCT), 2018,
  • [38] Robust Control of Hand Prostheses from Surface EMG Signal for Transradial Amputees
    Nastarin, Anika
    Akter, Ashrina
    Awal, Md Abdul
    2019 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE), 2019, : 143 - 148
  • [39] Implementation of EMG Signal Measurement for the Control of the 3D Hand Prototype
    Nawrocka, Agata
    Nawrocki, Marcin
    Kot, Andrzej
    2021 22ND INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC), 2021, : 155 - 158
  • [40] EMG Sliding Mode Finger Joint Synergy Control of a Dexterous Artificial Hand
    Kent, Benjamin A.
    Karnati, Nareen
    Engeberg, Erik D.
    2012 4TH IEEE RAS & EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL ROBOTICS AND BIOMECHATRONICS (BIOROB), 2012, : 87 - 92