Kinematic Analysis of Dynamic Coactivation During Arm Swing at the Shoulder and Elbow Joints

This study aimed to investigate the influence of different walking speeds on shoulder and elbow joint kinematics, specifically focusing on range of motion, angular velocity, and angular acceleration during arm swing. The natural rhythm of human gait was studied to develop an effective mechanical interface, particularly with respect to joint impedance and force controllability. The independent variable in this study was walking speed, operationalized at four levels—3.6 km/h (slow), 4.2 km/h (preferred walking speed, PWS), 5.4 km/h (normal), and 7.2 km/h (fast)—and defined as a within-subject factor. The dependent variables consisted of quantitative kinematic parameters, including joint range of motion (ROM, in degrees), peak and minimum joint angular velocity (deg/s), and peak and minimum joint angular acceleration (deg/s2). For each subject, data from twenty gait cycles were extracted for analysis. The kinematic variables of the shoulder and elbow were analyzed, showing increasing trends as the walking speed increased. As walking speed increases, adequate arm swing contributes to gait stability and energy efficiency. Notably, the ROM of shoulder was slightly reduced at the PWS compared to the slowest speed (3.6 km/h), which may reflect more natural and coordinated limb movements at the PWS. Dynamic covariation of torque patterns in the shoulder and elbow joints was observed, reflecting a synergistic coordination between these joints in response to human body movement.

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Publication Details

Journal
Applied Sciences
Published
2025-06-11
DOI
https://doi.org/10.3390/app15126593
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Kinematic Analysis of Dynamic Coactivation During Arm Swing at the Shoulder and Elbow Joints

Jaejin Hwang, Myung‐Chul Jung, Seung-Min Mo, Jae Ho Kim
Applied Sciences
Muscle activation and electromyography studies
article

Kinematic Analysis of Dynamic Coactivation During Arm Swing at the Shoulder and Elbow Joints

Jaejin Hwang, Myung‐Chul Jung, Seung-Min Mo, Jae Ho Kim
article en

Abstract

This study aimed to investigate the influence of different walking speeds on shoulder and elbow joint kinematics, specifically focusing on range of motion, angular velocity, and angular acceleration during arm swing. The natural rhythm of human gait was studied to develop an effective mechanical interface, particularly with respect to joint impedance and force controllability. The independent variable in this study was walking speed, operationalized at four levels—3.6 km/h (slow), 4.2 km/h (preferred walking speed, PWS), 5.4 km/h (normal), and 7.2 km/h (fast)—and defined as a within-subject factor. The dependent variables consisted of quantitative kinematic parameters, including joint range of motion (ROM, in degrees), peak and minimum joint angular velocity (deg/s), and peak and minimum joint angular acceleration (deg/s2). For each subject, data from twenty gait cycles were extracted for analysis. The kinematic variables of the shoulder and elbow were analyzed, showing increasing trends as the walking speed increased. As walking speed increases, adequate arm swing contributes to gait stability and energy efficiency. Notably, the ROM of shoulder was slightly reduced at the PWS compared to the slowest speed (3.6 km/h), which may reflect more natural and coordinated limb movements at the PWS. Dynamic covariation of torque patterns in the shoulder and elbow joints was observed, reflecting a synergistic coordination between these joints in response to human body movement.

Applied SciencesVol. 15(12)
Northern Illinois University (US), Suncheon Jeil College (KR), Osan University (KR), Ajou University (KR)
Rural Development Administration
Openalex Percentile: Top 87%
Muscle activation and electromyography studies
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Kinematic Analysis of Dynamic Coactivation During Arm Swing at the Shoulder and Elbow Joints — Jaejin Hwang, Myung‐Chul Jung, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS