FRACTAL-BASED CLASSIFICATION OF ELECTROMYOGRAPHY (EMG) SIGNAL BETWEEN FINGERS AND HAND’S BASIC MOVEMENTS, FUNCTIONAL MOVEMENTS, AND FORCE PATTERNS

Abstract

Analysis of human ability to move the body (hand, feet, etc.) is one of the major issues in rehabilitation science. For this purpose, scientists analyze different signals govern from human body. Electromyography (EMG) signal is the main indicator of human movement that can be analyzed using different techniques in order to classify different movements. In this paper, we analyze the complex non-linear structure of EMG signal from subjects while they underwent three exercises that include basic movements of the fingers and of the wrist, grasping and functional movements, and force patterns. For this purpose, we employ fractal dimension as indicator of complexity. The result of our analysis showed that the EMG signal experiences the greatest complexity when subjects think to press combinations of fingers with an increasing force (force pattern). The method of analysis employed in this research can be widely applied to analyze and classify different types of human movements.