![]() 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. 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). 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. ![]() Considerable work has also been carried out in the frequency domain using classical power spectrum analysis techniques. ![]() 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. ![]()
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