Research on Pattern Classification of SVM-based Gait Signal

被引：0
|
作者：
Yin, Jing [1 ]
机构：
[1] Shanghai Jianqiao Univ, Dept Informat Technol, Shanghai 201319, Peoples R China
来源：
ADVANCES IN APPLIED SCIENCE AND INDUSTRIAL TECHNOLOGY, PTS 1 AND 2 | 2013年 / 798-799卷
关键词：
Parkinson; gait signal; characteristic parameter;
D O I：
10.4028/www.scientific.net/AMR.798-799.526
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Research on Parkinson-based gait is a hotspot nowadays. However, few researches on the gait characteristics of PD patients start from the plantar pressure signal. In this paper, characteristic parameters are extracted from the gaits of PD patients and healthy people, and two-sided T inspection is performed to find significantly different parameters as input for the model classifier. The SVM classifier designed can achieve good result in discriminating the gaits of patients and normal people.
引用
收藏
页码：526 / 529
页数：4
相关论文
共 50 条
  • [1] Research of SVM-based document classification
    Zhang, ZhenNan
    Xu, Qian
    Cui, Junbo
    Pu, Duan
    [J]. Information, Management and Algorithms, Vol II, 2007, : 260 - 263
  • [2] SVM-based Partial Discharge Pattern Classification for GIS
    Ling, Yin
    Bai, Demeng
    Wang, Menglin
    Gong, Xiaojin
    Gu, Chao
    [J]. 2017 2ND INTERNATIONAL CONFERENCE ON COMMUNICATION, IMAGE AND SIGNAL PROCESSING (CCISP 2017), 2018, 960
  • [3] SVM-Based Gait Analysis and Classification for Patients with Parkinson's Disease
    Zheng, Yuncheng
    Weng, Yanhong
    Yang, Xiaoli
    Cai, Guofa
    Cai, Guoen
    Song, Yang
    [J]. 2021 15TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION AND COMMUNICATION TECHNOLOGY (ISMICT), 2021, : 53 - 58
  • [4] Research on SVM-Based Automatic Classification of Chinese Web Page
    Song, Jie
    Liu, Yanque
    Li, Nana
    Gu, Junhua
    [J]. PROGRESS IN INTELLIGENCE COMPUTATION AND APPLICATIONS, 2008, : 160 - 164
  • [5] Implementation of SVM-Based Low Power EEG Signal Classification Chip
    Su, Yongqian
    Shi, Weiwei
    Hu, Lizhi
    Zhuang, Suixing
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2022, 69 (10) : 4048 - 4052
  • [6] SVM-Based Classification of Moving Objects
    Li, Zhanchuang
    Jiang, Jianmin
    Xiao, Guoqiang
    [J]. MULTIMEDIA, COMPUTER GRAPHICS AND BROADCASTING, PROCEEDINGS, 2009, 60 : 37 - 45
  • [7] SVM-based audio scene classification
    Jiang, HC
    Bai, JM
    Zhang, SW
    Xu, B
    [J]. PROCEEDINGS OF THE 2005 IEEE INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND KNOWLEDGE ENGINEERING (IEEE NLP-KE'05), 2005, : 131 - 136
  • [8] An optimal svm-based text classification algorithm
    Wang, Zi-Qiang
    Sun, Xia
    Zhang, De-Xian
    Li, Xin
    [J]. PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 1378 - +
  • [9] Multiresolution histograms for SVM-based texture classification
    Andra, S
    Wu, YJ
    [J]. IMAGE ANALYSIS AND RECOGNITION, 2005, 3656 : 754 - 761
  • [10] SVM-Based DOA estimation with classification optimization
    Faye, A.
    Ndaw, J. D.
    Sene, M.
    [J]. 2018 26TH TELECOMMUNICATIONS FORUM (TELFOR), 2018, : 168 - 171
12345