Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios

Electromyography (EMG) onsets determined by computerized detection methods have been compared against the onsets selected by experts through visual inspection. However, with this type of approach, the true onset remains unknown, making it impossible to determine if computerized detection methods are...

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Main Authors: Erik Kowalski, Danilo S. Catelli, Mario Lamontagne
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Journal of Functional Morphology and Kinesiology
Subjects:
Online Access:https://www.mdpi.com/2411-5142/6/3/70
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spelling doaj-a631410ae5454aebb3ebd080cb68af9b2021-09-26T00:29:27ZengMDPI AGJournal of Functional Morphology and Kinesiology2411-51422021-08-016707010.3390/jfmk6030070Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise RatiosErik Kowalski0Danilo S. Catelli1Mario Lamontagne2Human Movement Biomechanics Laboratory, School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, CanadaHuman Movement Biomechanics Laboratory, School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, CanadaHuman Movement Biomechanics Laboratory, School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, CanadaElectromyography (EMG) onsets determined by computerized detection methods have been compared against the onsets selected by experts through visual inspection. However, with this type of approach, the true onset remains unknown, making it impossible to determine if computerized detection methods are better than visual detection (VD) as they can only be as good as what the experts select. The use of simulated signals allows for all aspects of the signal to be precisely controlled, including the onset and the signal-to-noise ratio (SNR). This study compared three onset detection methods: approximated generalized likelihood ratio, double threshold (DT), and VD determined by eight trained individuals. The selected onset was compared against the true onset in simulated signals which varied in the SNR from 5 to 40 dB. For signals with 5 dB SNR, the VD method was significantly better, but for SNRs of 20 dB or greater, no differences existed between the VD and DT methods. The DT method is recommended as it can improve objectivity and reduce time of analysis when determining EMG onsets. Even for the best-quality signals (SNR of 40 dB), all the detection methods were off by 15–30 ms from the true onset and became progressively more inaccurate as the SNR decreased. Therefore, although all the detection methods provided similar results, they can be off by 50–80 ms from the true onset as the SNR decreases to 10 dB. Caution must be used when interpreting EMG onsets, especially on signals where the SNR is low or not reported at all.https://www.mdpi.com/2411-5142/6/3/70approximated generalized likelihood ratiodouble thresholdvisual detectionmuscle activitysurface EMG onset
collection DOAJ
language English
format Article
sources DOAJ
author Erik Kowalski
Danilo S. Catelli
Mario Lamontagne
spellingShingle Erik Kowalski
Danilo S. Catelli
Mario Lamontagne
Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios
Journal of Functional Morphology and Kinesiology
approximated generalized likelihood ratio
double threshold
visual detection
muscle activity
surface EMG onset
author_facet Erik Kowalski
Danilo S. Catelli
Mario Lamontagne
author_sort Erik Kowalski
title Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios
title_short Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios
title_full Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios
title_fullStr Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios
title_full_unstemmed Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios
title_sort comparing the accuracy of visual and computerized onset detection methods on simulated electromyography signals with varying signal-to-noise ratios
publisher MDPI AG
series Journal of Functional Morphology and Kinesiology
issn 2411-5142
publishDate 2021-08-01
description Electromyography (EMG) onsets determined by computerized detection methods have been compared against the onsets selected by experts through visual inspection. However, with this type of approach, the true onset remains unknown, making it impossible to determine if computerized detection methods are better than visual detection (VD) as they can only be as good as what the experts select. The use of simulated signals allows for all aspects of the signal to be precisely controlled, including the onset and the signal-to-noise ratio (SNR). This study compared three onset detection methods: approximated generalized likelihood ratio, double threshold (DT), and VD determined by eight trained individuals. The selected onset was compared against the true onset in simulated signals which varied in the SNR from 5 to 40 dB. For signals with 5 dB SNR, the VD method was significantly better, but for SNRs of 20 dB or greater, no differences existed between the VD and DT methods. The DT method is recommended as it can improve objectivity and reduce time of analysis when determining EMG onsets. Even for the best-quality signals (SNR of 40 dB), all the detection methods were off by 15–30 ms from the true onset and became progressively more inaccurate as the SNR decreased. Therefore, although all the detection methods provided similar results, they can be off by 50–80 ms from the true onset as the SNR decreases to 10 dB. Caution must be used when interpreting EMG onsets, especially on signals where the SNR is low or not reported at all.
topic approximated generalized likelihood ratio
double threshold
visual detection
muscle activity
surface EMG onset
url https://www.mdpi.com/2411-5142/6/3/70
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