Autoregressive and cepstral analyses of motor unit action potentials
AuthorPattichis, Constantinos S.
Elia, Andreas G.
SourceMedical Engineering and Physics
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Quantitative electromyographic signal analysis in the time domain for motor unit action potential (MUAP) classification and disease identification has been well documented over recent years. Considerable work has also been carried out in the frequency domain using classical power spectrum analysis techniques. Although MUAP autoregressive (AR) spectral analysis has been suggested as a diagnostic tool by a number of studies, it has not been thoroughly investigated yet. This work investigates the application of AR modeling and cepstral analysis for the diagnostic assessment of MUAPs recorded from normal (NOR) subjects and subjects suffering with motor neuron disease (MND) and myopathy (MYO). The following feature sets were extracted from the MUAP signal: (i) time domain measures, (ii) AR spectral measures, (iii) AR coefficients, and (iv) cepstral coefficients. Discriminative analysis of the individual features was carried out using the univariate and multiple covariance analysis methods. Both methods showed that: (i) the duration measure is the best discriminative feature among the time domain parameters, and (ii) the median frequency is the best discriminative feature among the AR spectral measures. Furthermore, the classification performance of the above four feature sets was investigated for three classes (NOR, MND and MYO) using artificial neural networks. Results showed that the highest diagnostic yield was obtained with the time domain measures followed by the cepstral coefficients, the AR spectral parameters, and the AR coefficients. In conclusion, MUAP autoregressive and cepstral analyses combined with time domain analysis provide useful information in the assessment of myopathology. Copyright (C) 1999 IPEM.
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Pattichis, Constantinos S.; Pattichis, Marios S. (1999)Quantitative analysis in clinical electromyography (EMG) is very desirable because it allows a more standardized, sensitive and specific evaluation of the neurophysiological findings, especially for the assessment of ...
Pattichis, Constantinos S.; Schofield, I. S.; Fawcett, P. (1999)The technique of macro EMG is used to investigate the motor unit architecture in a number of pathological conditions. Amplitude and area are the most commonly used criteria, but these parameters alone are not sufficient ...
Pattichis, Constantinos S.; Pattichis, Marios S.; Schizas, Christos N. (IEEE, 1996)In this study the usefulness of the wavelet transforms (WT) Daubechies with 4 and 20 coefficients, Chui, and Battle-Lemarie in analyzing MUAPs recorded from normal subjects and subjects suffering with motor neuron disease ...