IEEE Transactions on Biomedical Engineering · 1985 · 208 citations · 25 references
EngineeringBioengineeringBiomedical EngineeringBiomedical Signal ProcessingElectrophysiologyMovement AnalysisBiopotential MeasurementElectromyogram AnalysisMovement Pattern AnalysisMuscle PhysiologyMuscle Signal ProcessingDigital FilteringElectromyography Signal FilteringElectromyography Signal PreprocessingFilteringMotor Unit Action Potential AnalysisMuscle Activation AnalysisSpike TrainsTemplate-based Matching
We describe a new, automatic signal-processing method (ADEMG) for extracting motor-unit action potentials (MUAP's) from the electromyographic interference pattern for clinical diagnostic purposes. The method employs digital filtering to select the spike components of the MUAP's from the background activity, identifies the spikes by template matching, averages the MUAP waveforms from the raw signal using the identified spikes as triggers, and measures their amplitudes, durations, rise rates, numbers of phases, and firing rates. Efficient new algorithms are used to align and compare spikes and to eliminate interference from the MUAP averages. In a typical 10-s signal recorded from the biceps brachii muscle using a needle electrode during a 20 percent-maximal isometric contraction, the method identifies 8-15 simultaneously active MUAP's and detects 30-70 percent of their occurrences. The analysis time is 90 s on a PDP-11/34A.
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