ArticleJournal of neuroengineering and rehabilitation2024
Detecting muscle fatigue among community-dwelling senior adults with shape features of the probability density function of sEMG.
Article in Journal of neuroengineering and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effectiveness of Digital Health Interventions in Older Adults With Frailty and Sarcopenia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.Journal of medical Internet research · 2026Pooled it
- A Systematic Review of Surface Electromyography in Sarcopenia: Muscles Involved, Signal Processing Techniques, Significant Features, and Artificial Intelligence Approaches.Sensors (Basel, Switzerland) · 2025Pooled it
- Systematic Evaluation of sEMG Processing Pipelines for Gesture Recognition.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial Intelligence Applications to Support Physical Activity, Mobility, and Fatigue Management in People with Multiple Sclerosis: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- EEG-based dynamic emotion recognition using multi-scale wavelet transform with a Spatio-Temporal neural network.Scientific reports · 2026Article
- Effective real-time self-rehabilitation exercise monitoring and correctness system for low back pain management.Scientific reports · 2026Article
- Machine-learning methods for epilepsy diagnosis and therapeutic prevention: advances, setbacks, and opportunities.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- KAN-DeScoD: Kolmogorov-Arnold Network Enhanced Deep Score-Based Diffusion Model for ECG Denoising.Sensors (Basel, Switzerland) · 2026Article
- An age-related computational framework for predicting tibial fracture healing under walking rehabilitation: a comparison between younger and older adults.Medical & biological engineering & computing · 2026Article
- An IoT-enabled CRNN framework for secure wearable sensor-based activity recognition in physical education.Scientific reports · 2026Article
- Research on aging-friendly design risk assessment model based on non-parametric estimation.Scientific reports · 2026Article
- Functional Analysis of miR-148a: A Differentially Expressed microRNA in Hemifacial Microsomia.Current molecular medicine · 2026Article
- Modeling multiscale neural dynamics for EEG-based emotion recognition using an attentive wavelet-transformer framework.Frontiers in computational neuroscience · 2026Article
- Explainable Cluster-Based Predictive Framework for Early Diagnosis of Autism Spectrum Disorder Using Behavioral Biomarkers.Diagnostics (Basel, Switzerland) · 2025Article
- Rectus Femoris and Gastrocnemius EMG Driven Cheonjiin Speller for Korean Text Input.Sensors (Basel, Switzerland) · 2025Article
- Comparing the Effects of AI-Assisted and Traditional Exercise on Physical Health Outcomes in Older Adults: A Systematic Review and Meta-Analysis.Healthcare (Basel, Switzerland) · 2025Review
- Motion Intention Prediction for Lumbar Exoskeletons Based on Attention-Enhanced sEMG Inference.Biomimetics (Basel, Switzerland) · 2025Article
- DGHNN: a deep graph and hypergraph neural network for pan-cancer related gene prediction.Bioinformatics (Oxford, England) · 2025Article
- A deep learning approach to stress recognition through multimodal physiological signal image transformation.Scientific reports · 2025Article
- Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundPhysical exercise is an important method for both the physical and mental health of the senior population. However, excessive exertion can lead to increased risks of falls, severe injuries, and diminished quality of life. Therefore, simple and effective methods for fatigue monitoring during exercise are highly desirable, particularly in community settings. The purpose of this study was to explore the possibility of real-time detection of exercise-induced fatigue using surface Electromyogram (sEMG) features, including the kurtosis and skewness of the Probability Density Function (PDF) in the community settings to solve the issues of low sensitivity and high computational complexity of commonly used sEMG features.
methodssEMG signals from six forearm muscles were recorded during hand grip tasks at 20% maximal voluntary contraction (MVC) task-to-failure contractions from 30 healthy community-dwelling elders at their respective community centers. PDF shape features of the sEMG, namely kurtosis and skewness, were computed from 25 s of non-fatigue stable phase and 25 s of fatigue data for comparison. Statistical tests were conducted to compare and test for the significance of these features. We further proposed a novel fatigue indicator, Temporal-Mean-Kurtosis (TMK) of channel-averaged kurtosis, to detect fatigue with relatively low computational complexity and adequate sensitivity in community settings. ANOVA and post-hoc analyses were performed to examine the performance of TMK.
resultsStatistically significant differences were found between the non-fatigue period and the fatigue period for both kurtosis and skewness, with increasing values when approaching fatigue. TMK was shown to be sensitive in detecting fatigue with respect to time with lower computational complexity than the Sample Entropy.
conclusionThis study investigated PDF shape features of sEMG signals during a handgrip exercise to identify muscle fatigue in older adults in community experiments. Results revealed significant changes in kurtosis upon fatigue, indicating that PDF shape features were suitable convenient detectors of muscle fatigue in community experiments. The proposed indicator, TMK, showed potential sensitivity in tracking muscle fatigue over time in community-based settings with limited computational complexity, highlighting the promise of sEMG's PDF features in detecting muscle fatigue among the elderly.
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