A workflow using shape metrics plus classifier performance identifies downsampling configurations that preserve needle-EMG diagnostic information while reducing feature extraction time up to about 60-fold.
Effect of decimation on the classification rate of non-linear analysis methods ap- plied to uterine EMG signals.IRBM, 34(4):326–329, November 2013
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How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series
A workflow using shape metrics plus classifier performance identifies downsampling configurations that preserve needle-EMG diagnostic information while reducing feature extraction time up to about 60-fold.