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Background: 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.
Materials And Methods: 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.
Results: 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.
Discussion: 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.
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http://dx.doi.org/10.7717/peerj.19859 | DOI Listing |
Comput Methods Biomech Biomed Engin
September 2025
Institute of Radio Physics and Electronics, University of Calcutta, Kolkata, India.
Parkinson's disease (PD) is a neurodegenerative condition that impairs motor functions. Accurate and early diagnosis is essential for enhancing well-being and ensuring effective treatment. This study proposes a deep learning-based approach for PD detection using EEG signals.
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August 2025
School of Physical Education, Zhejiang Guangsha Vocational and Technical University of Construction, Dongyang, China.
Introduction: This study examined the impacts of different negative pressure cupping therapies (PCT) on pain relief, functional recovery, and inflammatory regulation in delayed onset muscle soreness (DOMS) after high-intensity exercise, with the aim of clarifying the dose-effect relationship.
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Neuropsychiatr Dis Treat
September 2025
Department of Radiology, No. 926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, Yunnan, 661699, People's Republic of China.
Parkinson's disease (PD) represents a progressive neurodegenerative disorder with escalating global burden, with mechanistic studies revealing α-synuclein propagation through gut-brain axis, mitochondrial defects, and neuroinflammatory cascades driven by genetic-environmental interplay. Recent advancements in diagnostic paradigms have successfully combined α-synuclein seed amplification assays with multimodal neuroimaging techniques, achieving an impressive diagnostic accuracy of 92% during the prodromal stages of disease. Phase II trials highlight disease-modifying potential of α-synuclein-targeting immunotherapies (40% reduction in motor decline) and LRRK2 kinase inhibitors showing blood-brain barrier penetration.
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September 2025
23andMe, Inc., Sunnyvale, California, USA.
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September 2025
Neurodevelopmental Laboratory on Addictions and Mental Health, McLean Hospital, Belmont, Massachusetts, USA.
Background: Examining youth before engagement in risky behaviors may help identify neurobiological signatures that prospectively predict susceptibility to initiating and escalating alcohol and other substance use. Given that frontal and medial temporal (e.g.
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