Head Posture Analysis using sEMG Signal

被引:0
|
作者
Kushwah, Kavita [1 ]
Narvey, Rakesh [1 ]
Singhal, Ashish [2 ]
机构
[1] Madhav Inst Sci & Technol, Dept Elect Engn, Gwalior, India
[2] Sagar Inst Sci Technol & Engn, Dept Elect Engn, Bhopal, India
关键词
sEMG; left upper trapezius muscle; right upper trapezius muscle; head posture; RMS value;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The purpose of this study was to determine the muscle activity of upper trapezius muscle of different head posture at standing and sitting positions by using surface electromyography (sEMG) signals. This tool may be a non-invasive technique that enables the analysis of muscle activity. Human's head posture is significant part of human body and have a big role to analyze posture of human body. During this approach surface electrodes are employed to record surface electromyography (sEMG) signals of head posture at different angles. It is discovered that the muscle action of upper trapezius at both standing and sitting position is higher at 60 degree of head pose, whereas it's lower just in case of zero degree that may be a neutral posture of head. It was also found that the muscle activity at standing position is higher than that of sitting position and in the result right trapezius muscle is more activate in standing position than the sitting position. It was also investigated that the muscle activity in standing is higher than that of sitting position. It is suggested that the muscle activity of head posture is lower in neutral position of head.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Posture Recognition of Elbow Flexion and Extension Using sEMG Signal Based on Multi-Scale Entropy
    Wang, Zhenyu
    Guo, Shuxiang
    Gao, Baofeng
    Song, Xuan
    2014 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2014), 2014, : 1132 - 1136
  • [2] Analysis of sEMG signal for KOA classification
    李玉榕
    廖志伟
    杜民
    Journal of Harbin Institute of Technology(New series), 2011, (06) : 113 - 119
  • [3] Analysis of sEMG signal for KOA classification
    李玉榕
    廖志伟
    杜民
    Journal of Harbin Institute of Technology, 2011, 18 (06) : 113 - 119
  • [4] Analyzing an sEMG signal using wavelets
    Bastiaensen, Y.
    Schaeps, T.
    Baeyens, J. P.
    4TH EUROPEAN CONFERENCE OF THE INTERNATIONAL FEDERATION FOR MEDICAL AND BIOLOGICAL ENGINEERING, 2009, 22 (1-3): : 156 - 159
  • [5] Posture Characterization Based on Time and Frequency Domains Parameters for Erector Spine SEMG Signal
    Shobaki, Mohammed M.
    Malik, Noreha Abdul
    Khan, Sheroz
    Nordin, Anis Nurashikin
    Haider, Samnan
    Sidek, Khairul Azami
    2014 INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION ENGINEERING (ICCCE), 2014, : 1 - 4
  • [6] Analysis of Biceps Brachii sEMG signal using Multiscale Fuzzy Approximate Entropy
    Navaneethakrishna, M.
    Karthick, P. A.
    Ramakrishnan, S.
    2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2015, : 7881 - 7884
  • [7] Posture Changes, Perceived Strength and SEMG
    Peper, Erik
    Booiman, Annette
    Lin, I-Mei
    Harvey, Richard
    Del Dosso, Ashley
    APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK, 2015, 40 (02) : 128 - 128
  • [8] Posture Changes, Perceived Strength and SEMG
    Peper, Erik
    Booiman, Annette
    Lin, I-Mei
    Harvey, Richard
    Del Dossoa, Ashley
    APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK, 2015, 40 (04) : 373 - 373
  • [9] Voiceless Bangla vowel recognition using sEMG signal
    Mostafa, S. S.
    Awal, M. A.
    Ahmad, M.
    Rashid, M. A.
    SPRINGERPLUS, 2016, 5
  • [10] SEMG signal analysis at acupressure points for elbow movement
    Ryait, Hardeep S.
    Arora, A. S.
    Agarwal, Ravinder
    JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY, 2011, 21 (05) : 868 - 876