ArticleJournal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology2012
Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes.
Article in Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
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- Analysis of Movement Variability During the Spike Jump Action in Young and High-Level Female Volleyball Players: Differences Between Categories and Playing Positions.Journal of functional morphology and kinesiology · 2025Article
- An adaptive segmentation scheme based on recurring action potentials for sEMG controlled movement decoding.Physical and engineering sciences in medicine · 2025Article
- An Onset Detection Method for Slowly Activated Muscle Based on Marginal Spectrum Entropy.Sensors (Basel, Switzerland) · 2025Article
- Estimating gait parameters from sEMG signals using machine learning techniques under different power capacity of muscle.Scientific reports · 2025Article
- Optimized strategies for developing high-speed muscle activity monitors utilizing multi-resolution energy operator.Frontiers in bioengineering and biotechnology · 2025Article
- Enhanced rehabilitation after total joint replacement using a wearable high-density surface electromyography system.Frontiers in rehabilitation sciences · 2025Article
- Tradeoffs of estimating reaction time with absolute and relative thresholds.Behavior research methods · 2024Article
- Pedaling Asymmetry Reflected by Bilateral EMG Complexity in Chronic Stroke.Entropy (Basel, Switzerland) · 2024Article
- Classification of hand and wrist movements via surface electromyogram using the random convolutional kernels transform.Scientific reports · 2024Article
- Comparison of sEMG Onset Detection Methods for Occupational Exoskeletons on Extensive Close-to-Application Data.Bioengineering (Basel, Switzerland) · 2024Article
- Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models.Sensors (Basel, Switzerland) · 2024Article
- Machine learning for hand pose classification from phasic and tonic EMG signals during bimanual activities in virtual reality.Frontiers in neuroscience · 2024Article
- Movement Diversity and Complexity Increase as Arm Impairment Decreases After Stroke: Quality of Movement Experience as a Possible Target for Wearable Feedback.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024Article
- Botulinum toxin treatment may improve myoelectric pattern recognition in robot-assisted stroke rehabilitation.Frontiers in neuroscience · 2024Article
- Review of electromyography onset detection methods for real-time control of robotic exoskeletons.Journal of neuroengineering and rehabilitation · 2023Review
- Effects of Law Enforcement Load Carriage Systems on Muscle Activity and Coordination during Walking: An Exploratory Study.Sensors (Basel, Switzerland) · 2023Article
- Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets.Entropy (Basel, Switzerland) · 2023Article
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Abstract
Voluntary surface electromyogram (EMG) signal is sometimes contaminated by spurious background spikes of both physiological and extrinsic or accidental origins. A novel method of muscle activity onset detection against such spurious spikes was proposed in this study based primarily on the sample entropy (SampEn) analysis of the surface EMG. The method takes advantage of the nonlinear properties of the SampEn analysis to distinguish voluntary surface EMG signals from spurious background spikes in the complexity domain. To facilitate muscle activity onset detection, the SampEn analysis of surface EMG was first performed to highlight voluntary EMG activity while suppressing spurious background spikes. Then, a SampEn threshold was optimized for muscle activity onset detection. The performance of the proposed method was examined using both semi-synthetic and experimental surface EMG signals. The SampEn based methods effectively reduced the detection error induced by spurious background spikes and achieved improved performance over the methods relying on conventional amplitude thresholding or its extended version in the Teager Kaiser Energy domain.
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