Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/6023
Title: | Human Locomotion: Techniques for Processing and Analysis of EMG Data |
Authors: | Marsh, Amanda Eva Mary |
Advisor: | Bruin, H. de Kitai, R. |
Department: | Electrical Engineering |
Keywords: | Electrical and Electronics;Electrical and Electronics |
Publication Date: | Sep-1981 |
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> |
URI: | http://hdl.handle.net/11375/6023 |
Identifier: | opendissertations/136 1478 913080 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 3.14 MB | Adobe PDF | View/Open |
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