{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T16:17:07Z","timestamp":1780589827143,"version":"3.54.1"},"reference-count":78,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T00:00:00Z","timestamp":1612310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NASA Space Technology Research Fellowship","award":["NNX15AQ32H"],"award-info":[{"award-number":["NNX15AQ32H"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Current methods for evaluating fatigue separately assess intramuscular changes in individual muscles from corresponding alterations in movement output. The purpose of this study is to investigate if a system-based monitoring paradigm, which quantifies how the dynamic relationship between the activity from multiple muscles and force changes over time, produces a viable metric for assessing fatigue. Improvements made to the paradigm to facilitate online fatigue assessment are also discussed. Eight participants performed a static elbow extension task until exhaustion, while surface electromyography (sEMG) and force data were recorded. A dynamic time-series model mapped instantaneous features extracted from sEMG signals of multiple synergistic muscles to extension force. A metric, called the Freshness Similarity Index (FSI), was calculated using statistical analysis of modeling errors to reveal time-dependent changes in the dynamic model indicative of performance degradation. The FSI revealed strong, significant within-individual associations with two well-accepted measures of fatigue, maximum voluntary contraction (MVC) force (rrm=\u22120.86) and ratings of perceived exertion (RPE) (rrm=0.87), substantiating the viability of a system-based monitoring paradigm for assessing fatigue. These findings provide the first direct and quantitative link between a system-based performance degradation metric and traditional measures of fatigue.<\/jats:p>","DOI":"10.3390\/s21041024","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T20:31:51Z","timestamp":1612384311000},"page":"1024","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Using a System-Based Monitoring Paradigm to Assess Fatigue during Submaximal Static Exercise of the Elbow Extensor Muscles"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5652-7392","authenticated-orcid":false,"given":"Kaci E.","family":"Madden","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9080-818X","authenticated-orcid":false,"given":"Dragan","family":"Djurdjanovic","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4152-5933","authenticated-orcid":false,"given":"Ashish D.","family":"Deshpande","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1152\/physrev.2001.81.4.1725","article-title":"Spinal and supraspinal factors in human muscle fatigue","volume":"81","author":"Gandevia","year":"2001","journal-title":"Physiol. 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