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Closed-Loop Force Control by Biorealistic Hand Prosthesis With Visual and Tactile Sensory Feedback.
- Source :
-
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society [IEEE Trans Neural Syst Rehabil Eng] 2024; Vol. 32, pp. 2939-2949. Date of Electronic Publication: 2024 Aug 16. - Publication Year :
- 2024
-
Abstract
- The ability of a novel biorealistic hand prosthesis for grasp force control reveals improved neural compatibility between the human-prosthetic interaction. The primary purpose here was to validate a virtual training platform for amputee subjects and evaluate the respective roles of visual and tactile information in fundamental force control tasks. We developed a digital twin of tendon-driven prosthetic hand in the MuJoCo environment. Biorealistic controllers emulated a pair of antagonistic muscles controlling the index finger of the virtual hand by surface electromyographic (sEMG) signals from amputees' residual forearm muscles. Grasp force information was transmitted to amputees through evoked tactile sensation (ETS) feedback. Six forearm amputees participated in force tracking and holding tasks under different feedback conditions or using their intact hands. Test results showed that visual feedback played a predominant role than ETS feedback in force tracking and holding tasks. However, in the absence of visual feedback during the force holding task, ETS feedback significantly enhanced motor performance compared to feedforward control alone. Thus, ETS feedback still supplied reliable sensory information to facilitate amputee's ability of stable grasp force control. The effects of tactile and visual feedback on force control were subject-specific when both types of feedback were provided simultaneously. Amputees were able to integrate visual and tactile information to the biorealistic controllers and achieve a good sensorimotor performance in grasp force regulation. The virtual platform may provide a training paradigm for amputees to adapt the biorealistic hand controller and ETS feedback optimally.
- Subjects :
- Humans
Male
Adult
Female
Middle Aged
Touch physiology
Muscle, Skeletal physiology
Psychomotor Performance physiology
Forearm physiology
Biomechanical Phenomena
Tendons physiology
Feedback, Sensory physiology
Hand Strength physiology
Hand physiology
Amputees
Artificial Limbs
Electromyography
Prosthesis Design
Subjects
Details
- Language :
- English
- ISSN :
- 1558-0210
- Volume :
- 32
- Database :
- MEDLINE
- Journal :
- IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
- Publication Type :
- Academic Journal
- Accession number :
- 39110556
- Full Text :
- https://doi.org/10.1109/TNSRE.2024.3439722