Comparison of Analysis Techniques for Electromyographic Data,

Abstract

Electromyography has been effectively employed to estimate the stress encountered by the forearm flexor muscles in performing a variety of functions in the static environment. Such analysis provides the basis for modification of a man-machine system in order to optimize the performance of individual tasks by reducing muscle stress. Myriad analysis methods have been proposed and employed to convert raw electromyographic data into numerical indices of stress and, more specifically, muscle work. However, the type of analysis technique applied to the data can significantly affect the outcome of the experiment. In this study four methods of analysis were used to simultaneously process electromyographic data. The following conclusions were drawn from this study: (1) Integrated and root mean square voltage parameters provided the smoothest and most linear indicators of muscle activity; (2) Peak counting techniques were more sensitive to change in muscle activity induced by vibration than integrated and RMS techniques; (3) Single threshold turns counting provided no useful information in this experiment; however, the turns amplitude histogram provided information similar to that of multi-threshold peak counting technique; and (4) Changing the integration time constant did not alter the linearity of the relationship between EMG output and arm load.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1977
Accession Number
ADA050032

Entities

People

  • John C. Johnson

Organizations

  • United States Army Aeromedical Research Lab

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Acquisition
  • Biomedical Research
  • Central Nervous System
  • Computers
  • Data Acquisition
  • Data Analysis
  • Discrimination
  • Dynamic Loads
  • Dynamic Range
  • Electrodes
  • Histograms
  • Human-Machine Systems
  • Hybrid Computers
  • Instrumentation
  • Static Loads
  • Test And Evaluation
  • Waves

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