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UBC Theses and Dissertations
Automated decomposition of electromyographic signals recorded with surface electrode arrays Chen, Yunquan
This thesis presents results of various investigations which led to the development and validation of a new system for multi-channel surface electromyographic (EMG) recording for clinical examinations (McSERCE) and of a new method for multi-channel surface EMG decomposition (McSED). To obtain individual motor unit action potentials (MUAP5) non-invasively, we invented 1) a brush-tip pin (BTP) electrode made of a bundle of fine wires for contacting the skin without electrolytic jelly; 2) a miniature active surface electrode array consisting of the BTP electrodes and signal buffers built into the device for sampling the MUAPs distributed on the skin; and 3) a surface EMG recording method which makes use of the bipolar electrode configuration for spatial filtering and the Hilbert transform for correcting for the phase-frequency non-linearity of the bipolar electrode transfer function. Based on these novel electrodes and recording method, the McSERCE system can be used to obtain MUAPs with high selectivity, resolution and signal-to-noise ratios. To extract individual MUAPs from EMG signals recorded on the skin with the McSERCE system, McSED, an effective, efficient, and robust multi-channel surface EMG decomposition method, was developed. The McSED method incorporates the following new techniques: 1) the detection of MUAPs using a multi-pass scheme which locates and matches action potentials detected simultaneously at slightly different locations on the skin; 2) the representation of MUAPs with their spatial distribution and temporal propagation patterns and times of occurrences; 3) the measurement of dissimilarity between MUAPs in terms of these patterns and times of occurrences; 4) the classification of MUAPs using both the “chaining” and the “dissection” characteristics of the single and complete linkage clustering methods, respectively; and 5) the estimation of the firing parameters of an incomplete MUAP train using a maximum-likelihood estimator. Using McSERCE and McSED, a clinical study was conducted on the MU conduction velocities of the abductor pollicis brevis muscle. Results showed that 2% of the 894 MUs detected in the muscles of 32 control subjects were “slow MUs” (v < 2.5 m/sec), whereas 27.7% of the 141 MUs detected in the muscles of four patients with myopathic disorders were slow MUs.
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