Dynamic electromyography. II. Normal patterns during gait

Abstract

Human gait is a complex phenomenon. Many descriptors are needed to completely describe gait in terms of the biomechanics involved. The descriptors, when expressed as a function of the gait cycle, are complex waveforms. For each of these variables, a single “normal” pattern with bands of deviation has generally been accepted as a reference in clinical/research use to explain the abnormalities in a patient's walking pattern. In fact, one observes many “normal” patterns, and a body of research has been devoted to explaining the differences between these patterns in terms of walking speed, age, cadence, sex, etc. It would be simpler in one sense to start with the fact that different people walk with different patterns, not one pattern with bands of deviation. Numerical representation of the waveforms simplifies the analysis and interpretation of waveform data and facilitates comparison between subjects or groups of subjects. When combined with pattern recognition techniques, it also is useful for identifying subpatterns within a group. In this article, the numerical representation of electromyographic data by Karhunen-Loeve expansion are combined with cluster analysis to obtain patterns of dynamic phasic activity of 10 muscles of the lower extremity. From the 35 normal subjects walking at self-selected speed, two to four patterns are developed for each of the muscles and the physiological significance of the patterns are discussed.