Comparison of analysis techniques for electromyographic data.

Abstract

Electromyography has been effectively employed to estimate the stress encountered by 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 performances 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 are employed to simultaneously process electromyographic data from the flexor muscles of the forearm. The methods of analysis include: 1) integrated EMG (three separate time constants), 2) root mean square voltage, 3) peak height discrimination (three level), and 4) turns counting (two methods). Mechanical stress input as applied to the arm of the subjects includes static load and vibration. The results of the study indicate the comparative sensitivity of each of the techniques to changes in EMG resulting from changes in static and dynamic load on the muscle.