Quasi-passive shoulder exoskeleton with enhanced assistance variability to adapt to frequent load changes

To develop an effective quasi-passive (QP) exoskeleton, maximizing its range of variable assistive torques while minimizing the energy required for this variation is crucial. However, achieving this goal has proven challenging so far owing to the common trade-off between the range of variable assistive torques and the energy required for torque variation. Additionally, the shoulder’s standby posture complicates the search for viable solutions. To tackle this issue, we derived design principles based on elastic potential energy field. Utilizing these principles, we developed a QP shoulder exoskeleton called adjustable shoulder exoskeleton (AD Exo), which successfully achieved a wide range of variable assistive torques with significantly reduced required energy for variation. Benchtop tests demonstrated a remarkable enhancement in variability, with a range of assistance spanning 6.37 Nm achieved with a variation energy of 0.9 J. In human trials, AD Exo significantly minimized the average percentage of maximum voluntary contraction in shoulder muscles. Compared to the condition without the exoskeleton (NE), the average muscle activation was reduced by 25% at the adjusted assistance (ADJ), 7.5% at the low assistance (LOW), and 6.7% at the high assistance (HIGH), respectively. Considering repetitive and long-term tasks, this reduction in muscle activity can accumulate, making AD Exo highly effective for alleviating shoulder muscle burden and fatigue. Furthermore, kinematic motions of wearers and actual assistive torque delivered to wearers were examined to analyze the underlying the assistive effect of the exoskeleton.

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Publication Details

Journal
The International Journal of Robotics Research
Published
2025-04-24
DOI
https://doi.org/10.1177/02783649251323282
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
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article

Quasi-passive shoulder exoskeleton with enhanced assistance variability to adapt to frequent load changes

Jehyeok Kim, Sumin Kim, Junyoung Moon, Sang-Eui Lee et al.
The International Journal of Robotics Research
Prosthetics and Rehabilitation Robotics
article

Quasi-passive shoulder exoskeleton with enhanced assistance variability to adapt to frequent load changes

Jehyeok Kim, Sumin Kim, Junyoung Moon, Sang-Eui Lee, Jihwan Yoon, Giuk Lee
article en

Abstract

To develop an effective quasi-passive (QP) exoskeleton, maximizing its range of variable assistive torques while minimizing the energy required for this variation is crucial. However, achieving this goal has proven challenging so far owing to the common trade-off between the range of variable assistive torques and the energy required for torque variation. Additionally, the shoulder’s standby posture complicates the search for viable solutions. To tackle this issue, we derived design principles based on elastic potential energy field. Utilizing these principles, we developed a QP shoulder exoskeleton called adjustable shoulder exoskeleton (AD Exo), which successfully achieved a wide range of variable assistive torques with significantly reduced required energy for variation. Benchtop tests demonstrated a remarkable enhancement in variability, with a range of assistance spanning 6.37 Nm achieved with a variation energy of 0.9 J. In human trials, AD Exo significantly minimized the average percentage of maximum voluntary contraction in shoulder muscles. Compared to the condition without the exoskeleton (NE), the average muscle activation was reduced by 25% at the adjusted assistance (ADJ), 7.5% at the low assistance (LOW), and 6.7% at the high assistance (HIGH), respectively. Considering repetitive and long-term tasks, this reduction in muscle activity can accumulate, making AD Exo highly effective for alleviating shoulder muscle burden and fatigue. Furthermore, kinematic motions of wearers and actual assistive torque delivered to wearers were examined to analyze the underlying the assistive effect of the exoskeleton.

The International Journal of Robotics ResearchVol. 44(12)
Université Laval (CA), Chung-Ang University (KR)
Openalex Percentile: Top 92%
Prosthetics and Rehabilitation Robotics
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