Design, modeling, and validation of a computer-vision-enabled 3D-printed soft robotic glove for stroke telerehabilitation
Abstract
Post-stroke rehabilitation for upper-limb mobility faces challenges such as limited availability, high costs, and insufficient insurance coverage. This work addresses these challenges by integrating soft robotics with computer vision. A lightweight soft robotic glove (159 g), featuring five three-dimensional (3D)-printed soft pneumatic actuators that function as fingers, is designed and optimized using finite element modeling (FEM) in terms of bending behavior and force output. The fingers demonstrated durability, bending deformation repeatability, force repeatability, and reliable holding force capability. The proof-of-concept system comprises a wearable robotic glove for the patient and a computer vision interface for the therapist. The therapist performs hand gestures captured by a camera to control the glove through the computer vision interface. The soft robotic glove and integrated computer vision interface were experimentally validated on healthy participants. This validation demonstrates the feasibility of controlling the glove using computer vision and its potential for future telerehabilitation applications.
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BibTeX
@article{tawk2026design,
title = {{Design, modeling, and validation of a computer-vision-enabled 3D-printed soft robotic glove for stroke telerehabilitation}},
author = {Charbel Tawk and George Saab and George Abdallah and Jason El Khoury and Reynald Aouad},
journal = {iScience},
year = {2026},
month = oct,
doi = {10.1016/j.isci.2026.118006},
url = {https://www.cell.com/iscience/fulltext/S2589-0042(26)03389-4},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Design, modeling, and validation of a computer-vision-enabled 3D-printed soft robotic glove for stroke telerehabilitation
AU - Charbel Tawk
AU - George Saab
AU - George Abdallah
AU - Jason El Khoury
AU - Reynald Aouad
PY - 2026
DA - 2026/10/26
JO - iScience
DO - 10.1016/j.isci.2026.118006
UR - https://www.cell.com/iscience/fulltext/S2589-0042(26)03389-4
AB - Post-stroke rehabilitation for upper-limb mobility faces challenges such as limited availability, high costs, and insufficient insurance coverage. This work addresses these challenges by integrating soft robotics with computer vision. A lightweight soft robotic glove (159 g), featuring five three-dimensional (3D)-printed soft pneumatic actuators that function as fingers, is designed and optimized using finite element modeling (FEM) in terms of bending behavior and force output. The fingers demonstrated durability, bending deformation repeatability, force repeatability, and reliable holding force capability. The proof-of-concept system comprises a wearable robotic glove for the patient and a computer vision interface for the therapist. The therapist performs hand gestures captured by a camera to control the glove through the computer vision interface. The soft robotic glove and integrated computer vision interface were experimentally validated on healthy participants. This validation demonstrates the feasibility of controlling the glove using computer vision and its potential for future telerehabilitation applications.
SN - 2589-0042
ER -