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Related Concept Videos

Electro-mechanical Systems01:19

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Electromechanical systems are intricate configurations that effectively combine electrical and mechanical elements to achieve a desired outcome. Central to many of these systems is the DC motor, a device that converts electrical energy into mechanical motion, enabling various applications ranging from simple fans to complex robotic mechanisms.
A key component of the DC motor is the armature, a rotating circuit positioned within a magnetic field. As an electric current passes through the...
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Related Experiment Video

Updated: Mar 12, 2026

Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
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EMG-Torque Relation in Chronic Stroke: A Novel EMG Complexity Representation With a Linear Electrode Array.

Xu Zhang, Dongqing Wang, Zaiyang Yu

    IEEE Journal of Biomedical and Health Informatics
    |November 16, 2016
    PubMed
    Summary

    Stroke survivors show altered electromyogram (EMG) complexity related to muscle torque. This study reveals reduced EMG complexity in affected limbs, offering new insights into post-stroke neuromuscular changes.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Rehabilitation Science

    Background:

    • Stroke often leads to impaired motor control and muscle weakness.
    • Understanding the electromyogram (EMG)-torque relationship is crucial for assessing neuromuscular function post-stroke.

    Purpose of the Study:

    • To investigate the EMG-torque relationship in chronic stroke survivors using a novel EMG complexity measure.
    • To compare EMG complexity between affected and unaffected limbs.

    Main Methods:

    • Ten chronic stroke survivors performed isometric elbow flexion tasks.
    • Surface EMG was recorded from biceps brachii using a 20-channel array.
    • Sample entropy (SampEn) was calculated to represent EMG complexity, and regression analysis was performed against torque.

    Main Results:

    • A linear relationship was observed between EMG SampEn and torque.
    • The regression slope was lower in the impaired limb compared to the non-impaired limb for 80% of subjects.
    • EMG signals over innervation zones showed lower complexity than those between zones and tendons.

    Conclusions:

    • EMG complexity offers a novel perspective on the EMG-torque relationship post-stroke.
    • Altered EMG complexity in stroke survivors reflects underlying neural and muscular changes.
    • Electrode placement significantly influences EMG analysis, particularly concerning innervation zones.