ArticleJournal of medical signals and sensors
Assessing Muscle Fatigue in Multiple Sclerosis using the Sample Entropy of Electromyographic Signals: A Proof of Concept.
Article in Journal of medical signals and sensors. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Static Baropodometric Assessment for Musculoskeletal Rehabilitation: Plantar Pressure and Postural Load Distribution in Young Adults.Life (Basel, Switzerland) · 2025Article
- Isfahan Artificial Intelligence Event 2023: Lesion Segmentation and Localization in Magnetic Resonance Images of Patients with Multiple Sclerosis.Journal of medical signals and sensors · 2025Article
- Sample Entropy Improves Assessment of Postural Control in Early-Stage Multiple Sclerosis.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Multiple sclerosis (MS) is a progressive and neurodegenerative disease of the central nervous system. Its symptoms vary greatly, which makes its diagnosis complex, expensive, and time-consuming. One of its most prevalent symptoms is muscle fatigue. It occurs in about 92% of patients with MS (PwMS) and is defined as a decrease in maximal strength or energy production in response to contractile activity. This article aims to compare the behavior of a healthy control (HC) with that of a patient with MS before and after muscle fatigue. Methods: For this purpose, a static baropodometric test and a dynamic electromyographic analysis are performed to calculate the area of the stabilometric ellipse, the remitting MS (RMS) value, and the sample entropy (SampEn) of the signals, as a proof of concept to explore the feasibility of this test in the muscle fatigue quantitative analysis; in addition, the statistical analysis was realized to verify the results. Results: According to the results, the ellipse area increased in the presence of muscle fatigue, indicating a decrease in postural stability. Likewise, the RMS value increased in the MS patient and decreased in the HC subject and the opposite behavior in the SampEn was observed in the presence of muscle fatigue. Conclusion: Thus, this study demonstrates that SampEn is a viable parameter to estimate muscle fatigue in PwMS and other neuromuscular diseases.
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Registered trials
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