Human Locomotion: Techniques for Processing and Analysis of EMG Data

Abstract

<p>Several techniques used by researchers in the area of human locomotion to process and analyse normal and pathological gait electromyographs (EMG) are discussed. Basic elements of neuromuscular organization are described.</p> <p>The thesis reports original work in several topic. The spectral analysis of dynamic EMG acquired during the locomotion of a normal subject was done to confirm the selected sampling frequency, and to determine a suitable low pass filter cutoff for smoothing EMG prior to data analysis.</p> <p>Results of using two filters for smoothing EMG, a second order Butterworth low pass filter, and a mid-point moving window average filter are compared.</p> <p>The cross correlation function is used in analysing EMG, since EMG signals are random. The results of cross correlation are compared with clinical observations in assessing the state of a patient following a stroke. Results for five normal and fourteen hemiplegic subjects are reported.</p> <p>The conclusion is that cross correlation analysis quantifies the state of the patient and assesses post stroke recovery according to the neurological picture of central nervous system control.</p>