Sliding window averaging in normal and pathological motor unit action potential trains

Publication date: June 2018
Source:Clinical Neurophysiology, Volume 129, Issue 6
Author(s): Armando Malanda-Trigueros, Javier Navallas, Javier Rodriguez-Falces, Ignacio Rodriguez-Carreño, Sonia Porta, Miguel Fernández-Martínez, Luis Gila
ObjectiveTo evaluate the performance of a recently proposed motor unit action potential (MUAP) averaging method based on a sliding window, and compare it with relevant published methods in normal and pathological muscles.MethodsThree versions of the method (with different window lengths) were compared to three relevant published methods in terms of signal analysis-based merit figures and MUAP waveform parameters used in the clinical practice. 218 MUAP trains recorded from normal, myopathic, subacute neurogenic and chronic neurogenic muscles were analysed. Percentage scores of the cases in which the methods obtained the best performance or a performance not significantly worse than the best were computed.ResultsFor signal processing figures of merit, the three versions of the new method performed better (with scores of 100, 86.6 and 66.7%) than the other three methods (66.7, 25 and 0%, respectively). In terms of MUAP waveform parameters, the new method also performed better (100, 95.8 and 91.7%) than the other methods (83.3, 37.5 and 25%).ConclusionsFor the types of normal and pathological muscle studied, the sliding window approach extracted more accurate and reliable MUAP curves than other existing methods.SignificanceThe new method can be of service in quantitative EMG.



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