Conference item
A soft robotic glove providing proprioceptive feedback for grip force regulation training
- Abstract:
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Inadequate regulation of grip force during tennis strokes may contribute to wrist and elbow overuse injuries. Although force transducer technologies such as strain gauge and piezoelectric sensors can quantify grip force, training feedback has largely been limited to visual feedback. The potential benefit of proprioceptive haptic feedback in grip force regulation training remains unclear.This study presents a soft robotic training system integrating a strain gauge embedded in a tennis racket for grip force sensing and an pneumatic actuator that provides proprioceptive haptic feedback. A pilot study was conducted in one novice tennis player to evaluate system feasibility and demonstrate its functionality. A passive force regulation experiment first verified the actuator’s ability to deliver physical haptic guidance. Then, during the active force regulation training, differences in learning curve and retention were observed between visual and haptic feedback conditions. Learning improvement, quantified as error reduction from pre- to post-training, reached 39% of the target force under visual feedback and 37% under haptic feedback. In retention trials, the root mean square error (RMSE) was 23.6% following visual feedback training and 20.0% following haptic feedback training. These preliminary findings suggest potential differences in training efficiency between feedback modalities. Further studies with larger samples are required to determine the generalizability of these observations and to further evaluate the effectiveness of the proposed soft robotic training system.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
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(Preview, Accepted manuscript, pdf, 2.8MB, Terms of use)
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- Publisher copy:
- 10.1109/RoboSoft67810.2026.11522873
Authors
- Publisher:
- IEEE
- Host title:
- 2026 IEEE 9th International Conference on Soft Robotics (RoboSoft)
- Pages:
- 635-641
- Publication date:
- 2026-05-22
- Acceptance date:
- 2026-01-30
- Event title:
- IEEE Robosoft 2026 Conference
- Event location:
- Kanazawa, Japan
- Event website:
- https://www.robosoft2026.org/
- Event start date:
- 2026-04-07
- Event end date:
- 2026-04-11
- DOI:
- EISSN:
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2769-4534
- ISSN:
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2769-4526
- EISBN:
- 9798331582159
- ISBN:
- 9798331582166
- Language:
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English
- Keywords:
- Pubs id:
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2391398
- Local pid:
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pubs:2391398
- Deposit date:
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2026-03-18
- ARK identifier:
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2026
- Rights statement:
- Copyright © 2026, IEEE
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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