Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Multichannel Optimization Strategy for Functional Electrical Stimulation in Grasp Gesture Restoration: A Pilot Study. |
| Συγγραφείς: |
Cheng KH, Sun J, Leng Y, Lin C, Fu C |
| Πηγή: |
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] 2026; Vol. 34, pp. 3096-3107. |
| Τύπος έκδοσης: |
Journal Article |
| Γλώσσα: |
English |
| Στοιχεία περιοδικού: |
Publisher: IEEE Country of Publication: United States NLM ID: 101097023 Publication Model: Print Cited Medium: Internet ISSN: 1558-0210 (Electronic) Linking ISSN: 15344320 NLM ISO Abbreviation: IEEE Trans Neural Syst Rehabil Eng Subsets: MEDLINE |
| Imprint Name(s): |
Original Publication: Piscataway, NJ : IEEE, c2001- |
| Ιατρικοί όροι (MeSH): |
Hand Strength*/physiology , Electric Stimulation Therapy*/methods , Gestures*, Muscle, Skeletal/physiology ; Electric Stimulation/methods ; Hand/physiology ; Humans ; Pilot Projects ; Female ; Male ; Algorithms ; Adult ; Electromyography ; Stroke Rehabilitation ; Reproducibility of Results |
| Περίληψη: |
Grasping difficulties profoundly diminish the quality of life in individuals affected by stroke or spinal cord injury. Multi-channel functional electrical stimulation (FES) enables precise, targeted muscle activation through selectively activated electrodes, offering a promising approach for motor restoration in neurorehabilitation. However, the requirement for gesture-specific calibration limits the scalability of the system to the diverse and highly coordinated hand functions essential for daily living. We present a biophysically informed modeling approach that selects optimal multichannel stimulation patterns, enabling an extensive repertoire of predictable grasping gestures. Individual-specific muscle characteristics are integrated into a bioelectric field model, which quantifies spatial interference and informs the selection of optimal stimulation patterns. The system was evaluated across a range of grasping gestures involving coordinated movements of the wrist and finger joints. Experimental evaluation confirmed that the proposed modeling approach effectively distinguishes functional stimulation patterns, yielding a mean grasp accuracy of 0.97 for optimized configurations across all tested gesture categories. These results demonstrate that the proposed approach enables effective and adaptable neuromuscular control across a variety of functional grasping tasks. This approach has shown strong generalizability by adapting to individual physiological characteristics, thereby offering valuable guidance for clinical implementation. |
| Entry Date(s): |
Date Created: 20260618 Date Completed: 20260703 Latest Revision: 20260929 |
| Update Code: |
20260930 |
| DOI: |
10.1109/TNSRE.2026.3704919 |
| PMID: |
42313580 |
| Βάση Δεδομένων: |
MEDLINE |