{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T13:48:27Z","timestamp":1770644907633,"version":"3.49.0"},"reference-count":24,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:sec>\n               <jats:title>Background<\/jats:title>\n               <jats:p>This study presents and validates a methodology for assessing upper limb motor control using quantitative metrics derived from biomechanics and surface electromyography (sEMG). By combining kinematic and neurophysiological measurements, the study establishes normative benchmarks in healthy adults, which can offer a foundation for future clinical applications in populations with neuromotor impairments, which are commonly characterized by spasticity, involuntary coactivation, and restricted range of motion (ROM). A combination of clinical functional scales with the quantitative metrics presented here is expected to enable better evaluation of motor control.<\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title>Materials and Methods<\/jats:title>\n               <jats:p>Twenty healthy adults performed elbow flexion-extension (FE) movements at three controlled speeds (42, 60, and 78 beats per minute (bpm)). The protocol involved recording sEMG signals of the biceps brachii and triceps brachii, with an inertial measurement unit (IMU) sensor, to compute four metrics: the range of motion (ROM), a derived angular velocity, the coactivation coefficient (CC), and muscle synergy. Movements were segmented into acceleration and deceleration phases to enable a phase-specific analysis, with a focus on both agonist and antagonist muscle activity during flexion and extension.<\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title>Results<\/jats:title>\n               <jats:p>The results established normative values for each metric, showing alignment with previous results in the literature for healthy motor patterns. ROM values were consistent with the expected ranges for healthy adults ranging between normative values, with the angular velocity increasing proportionally to the speed of movement but showing greater variability at higher speeds. The CC analysis demonstrated distinct phase-dependent activation patterns, with higher values during flexion deceleration due to antagonist muscle stabilization requirements. The muscle synergy metric highlighted a balanced activation of the biceps and triceps, with minor secondary activation of the triceps during flexion to counteract gravitational forces.<\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title>Discussion<\/jats:title>\n               <jats:p>The results validate the feasibility of this approach for quantifying motor control based on the quantitative metrics presented here. Normative values and the ability to detect changes in ROM, CC, and muscle synergy enhance the diagnostic potential of this approach in terms of identifying spasticity, coordination deficits, or abnormal neuromuscular patterns in clinical populations. This study establishes a comprehensive methodology for evaluating upper limb motor control, based on a combination of kinematic and neurophysiological data. These findings offer a solid foundation for developing advanced diagnostic tools and personalized rehabilitation strategies, with potential applications to conditions such as stroke, cerebral palsy, and other neuromotor impairments.<\/jats:p>\n            <\/jats:sec>","DOI":"10.7717\/peerj.19859","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T08:36:25Z","timestamp":1755851785000},"page":"e19859","source":"Crossref","is-referenced-by-count":3,"title":["Assessment of upper limb motor control: establishing normative benchmarks for clinical applications"],"prefix":"10.7717","volume":"13","author":[{"given":"Pablo","family":"Mart\u00edn-Sierra","sequence":"first","affiliation":[{"name":"Information Technologies Department, Universidad de San Pablo CEU, Boadilla del Monte, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristina","family":"Sanchez","sequence":"additional","affiliation":[{"name":"Information Technologies Department, Universidad de San Pablo CEU, Boadilla del Monte, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eloy","family":"Urendes","sequence":"additional","affiliation":[{"name":"Information Technologies Department, Universidad de San Pablo CEU, Boadilla del Monte, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafael","family":"Raya","sequence":"additional","affiliation":[{"name":"Information Technologies Department, Universidad de San Pablo CEU, Boadilla del Monte, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"4443","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"10.7717\/peerj.19859\/ref-1","doi-asserted-by":"publisher","first-page":"3412","DOI":"10.3390\/S20123412","article-title":"Reliability and validity of a novel wearable device for measuring elbow strength","volume":"20","author":"Brookshaw","year":"2020","journal-title":"Sensors"},{"key":"10.7717\/peerj.19859\/ref-2","doi-asserted-by":"publisher","first-page":"231","DOI":"10.4324\/9781003525288-95","article-title":"Modified Ashworth scale","volume-title":"Occupational therapy assessments for older adults: 100 instruments for measuring occupational performance","author":"Brotnick","year":"2023"},{"key":"10.7717\/peerj.19859\/ref-3","doi-asserted-by":"publisher","first-page":"e0310192","DOI":"10.1371\/JOURNAL.PONE.0310192","article-title":"The effect of gravity on hand spatio-temporal kinematic features during functional movements","volume":"19","author":"Bucchieri","year":"2024","journal-title":"PLOS ONE"},{"key":"10.7717\/peerj.19859\/ref-4","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1016\/J.JELEKIN.2010.07.004","article-title":"How should we normalize electromyograms obtained from healthy participants? 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