• DocumentCode
    1669974
  • Title

    Test-Retest Repeatability of Surface Electromyography Measurement for Hand Gesture

  • Author

    Chen Xiang ; Li Qiang ; Yang Ji-hai ; Lantz, Vuokko ; Wang Kong-qiao

  • Author_Institution
    Electron. Sci. & Technol. Dept., Univ. of Sci. & Technol. of China, Hefei
  • fYear
    2008
  • Firstpage
    1923
  • Lastpage
    1926
  • Abstract
    This study explores the test-retest repeatability of surface EMG measurements during hand gesture tasks across days and across subjects. Subjects took part in the data collection experiments on five separate days in a four-week time period. Surface EMG (sEMG) data was collected from the forearm. Intrasubject and intersubject test-retest repeatability of mean absolute values (MAV) and four-order AR model coefficients derived from 8-channel sEMG measurements were investigated using the coefficients of multiple correlation (CMCs) and coefficients of variation (CVs). Experimental results indicate moderate to high test-retest reliability for MAV and AR coefficients of sEMG measurements for nine of the ten studied hand gestures. The differences in test-retest repeatability among the hand gesture tasks also provide some insight into the effects of individual differences, electrode placement and gesture-specific characteristic of sEMG measurement.
  • Keywords
    biomechanics; biomedical electrodes; biomedical measurement; correlation methods; electromyography; data collection; electrode placement; gesture-specific characteristics; hand gesture; multiple correlation coefficients; surface EMG; surface electromyography measurement; test-retest repeatability; variation coefficients; Control systems; Electrodes; Electromyography; Electronic equipment testing; Fingers; Motion control; Muscles; Pattern recognition; System testing; Wrist;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.810
  • Filename
    4535690