| Summary: | 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. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
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