An Implementation of Neuro-Fuzzy System for Gait Analysis in a Smart Insole of Exoskeleton

被引：0
|
作者：
Do Xuan Phu [1 ]
Ta Duc Huy [1 ]
Tran Hoang Ha [1 ]
机构：
[1] Vietnamese German Univ, MediRobot Lab, Binh Duong, Vietnam
来源：
PROCEEDINGS OF 2018 4TH INTERNATIONAL CONFERENCE ON GREEN TECHNOLOGY AND SUSTAINABLE DEVELOPMENT (GTSD) | 2018年
关键词：
exoskeleton; gait pattern; gait analysis; lower limb analysis; neuro-fuzzy system; prosthesis design; smart insole; smart exoskeleton;
D O I：
暂无
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
This study presents an implementation of neuro-fuzzy model in a smart insole for exoskeleton to extract features using for control The features are found based on the walking state of the human. The model of fuzzy C means is applied based on the interval type 2 fuzzy. The gait phases of the smart insole are analyzed within a gait cycle of human motion. Due to the boundaries among the gait phases, fuzzy inference is used for finding these variations. In addition, the neural network structure uses as the training role for both the fuzzy membership function parameters and its weights. The results show that states of human motions can be filtered by the neuro-fuzzy model at 98.14%.
引用
收藏
页码：611 / 614
页数：4
相关论文
共 50 条
  • [1] Design and Implementation of a Lightweight Smart Insole for Gait Analysis
    Cho, Hyuntae
    [J]. 2017 16TH IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS / 11TH IEEE INTERNATIONAL CONFERENCE ON BIG DATA SCIENCE AND ENGINEERING / 14TH IEEE INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS, 2017, : 792 - 797
  • [2] A novel gait analysis system based on adaptive neuro-fuzzy inference system
    Su, Xu
    Xu, Zhou
    Yi-Ning, Sun
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (02) : 1265 - 1269
  • [3] Towards Neuro-Fuzzy Compensated PID Control of Lower Extremity Exoskeleton System for Passive Gait Rehabilitation
    Narayan, Jyotindra
    Dwivedy, Santosha Kumar
    [J]. IETE JOURNAL OF RESEARCH, 2023, 69 (02) : 778 - 795
  • [4] Fuzzy Vs. Neuro-fuzzy: Implementation on the Reconfigurable FPGA System
    Mondal, Saikat
    Chattapadhyay, Paramita
    [J]. 2015 INTERNATIONAL CONFERENCE ON ENERGY, POWER AND ENVIRONMENT: TOWARDS SUSTAINABLE GROWTH (ICEPE), 2015,
  • [5] Neuro-fuzzy control of a robotic exoskeleton with EMG signals
    Kiguchi, K
    Tanaka, T
    Fukuda, T
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2004, 12 (04) : 481 - 490
  • [6] Digital Implementation of Neuro-Fuzzy System for Image Processing Functions
    Elloumi, Manel
    Krid, Mohamed
    Masmoudi, Dorra Sellami
    [J]. JOURNAL OF TESTING AND EVALUATION, 2016, 44 (03) : 1161 - 1174
  • [7] Efficient hardware/software implementation of an adaptive neuro-fuzzy system
    del Campo, Ines
    Echanobe, Javier
    Bosque, Guillermo
    Manuel Tarela, Jose
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2008, 16 (03) : 761 - 778
  • [8] An implementation of the neuro-fuzzy inference circuit
    Fujimoto, Kuniaki
    Sasaki, Hirofumi
    Masaoka, Yoichiro
    Yang, Ren-Qi
    Mizumoto, Masaharu
    [J]. INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2007, 3 (04): : 1043 - 1052
  • [9] An implementation of the neuro-fuzzy inference circuit
    Fujimoto, Kuniaki
    Sasaki, Hirofumi
    Masaoka, Yoichiro
    Yang, Ren-Qi
    Mizumoto, Masaharu
    [J]. ICICIC 2006: FIRST INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING, INFORMATION AND CONTROL, VOL 2, PROCEEDINGS, 2006, : 301 - +
  • [10] FPGA implementation of neuro-fuzzy system with improved PSO learning
    Karakuzu, Cihan
    Karakaya, Fuat
    Cavuslu, Mehmet Ali
    [J]. NEURAL NETWORKS, 2016, 79 : 128 - 140
12345