Monitoring electromyography signals (EMG) leads to a greater understanding of muscle properties hives insight into how muscles work together to coordinate tasks, and yields information about neuromuscular disorders. In this project we developed a PC based EMG data acquisition and analysis system to record and analysis EMG signals. We tested this system by recording EMG signals from the biceps brachii of a single normal subject. The acquired data was analyzed in both time and frequency domains to determine the behavior of the EMG signal during different experiment conditions. Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT) were applied during digital signal processing. The FFT only provides the information in frequency domain. STFT is a modification of the Fourier transform in an attempt to retain both time and frequency information during signal analysis. The STFT produces a two dimensional function with time and frequency as variables. Thus the STFT gives information about when in time a given frequency component occurs. The extracted features of EMG are RMS value, mean absolute value, mean power frequency, and median power frequency. The raw EMG signal is collected for 10 seconds. The sampling rate is set to 1000 Hz. The emphases of this project were software development, data collection, and simple signal analysis. / Thesis / Master of Engineering (ME)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/23202 |
| Date | 01 1900 |
| Creators | Zhenkun, Wu |
| Contributors | de Bruin, H., Electrical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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