TY - GEN
T1 - Interactive Gait Rehabilitation Through Gamified Real-Time Biofeedback and Adaptive Hip Exoskeleton Assistance
T2 - 2025 International Conference on Rehabilitation Robotics, ICORR 2025
AU - Tohfafarosh, Mariya
AU - Ratnakumar, Neethan
AU - Zurzolo, Lorenzo
AU - Adamovich, Sergei
AU - Zhou, Xianlian
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper presents the design and functional evaluation of an interactive rehabilitation system that integrates a hip exoskeleton with a game-based environment for targeted gait rehabilitation. The system offers real-time visualization of full-body motion tracking and biofeedback, including electromyography (EMG) based muscle activation feedback. Users control an anatomical avatar within a task-based gameplay interface, where the avatar mirrors their motion and displays muscle activation through dynamic, red-shaded overlays corresponding to real-time EMG signals. To assess the system's functionality, a healthy subject participated in a study involving treadmill walking at 0.25 ms slower than their selfselected speed. The subject navigated a forest environment to collect virtual apples while using two stiffness-based hip control modes: an in-phase assistive mode and an out-of-phase resistive mode. The assistive mode reduced muscle activation, while the resistive mode increased muscle activation for strength training. Additionally, the system supports post-processing of collected data for further analysis, enabling visualization of kinematics, exoskeleton torques, and EMG patterns. Users can customize rehabilitation parameters to tailor the experience to their needs. The results demonstrate the system's potential as an interactive, feedback-driven rehabilitation platform, showcasing its biofeedback capabilities and adaptability.
AB - This paper presents the design and functional evaluation of an interactive rehabilitation system that integrates a hip exoskeleton with a game-based environment for targeted gait rehabilitation. The system offers real-time visualization of full-body motion tracking and biofeedback, including electromyography (EMG) based muscle activation feedback. Users control an anatomical avatar within a task-based gameplay interface, where the avatar mirrors their motion and displays muscle activation through dynamic, red-shaded overlays corresponding to real-time EMG signals. To assess the system's functionality, a healthy subject participated in a study involving treadmill walking at 0.25 ms slower than their selfselected speed. The subject navigated a forest environment to collect virtual apples while using two stiffness-based hip control modes: an in-phase assistive mode and an out-of-phase resistive mode. The assistive mode reduced muscle activation, while the resistive mode increased muscle activation for strength training. Additionally, the system supports post-processing of collected data for further analysis, enabling visualization of kinematics, exoskeleton torques, and EMG patterns. Users can customize rehabilitation parameters to tailor the experience to their needs. The results demonstrate the system's potential as an interactive, feedback-driven rehabilitation platform, showcasing its biofeedback capabilities and adaptability.
KW - assistive technology
KW - biomechanical feedback
KW - gamified rehabilitation
KW - myofeedback
UR - https://www.scopus.com/pages/publications/105011138328
UR - https://www.scopus.com/pages/publications/105011138328#tab=citedBy
U2 - 10.1109/ICORR66766.2025.11063083
DO - 10.1109/ICORR66766.2025.11063083
M3 - Conference contribution
C2 - 40644080
AN - SCOPUS:105011138328
T3 - IEEE International Conference on Rehabilitation Robotics
SP - 1799
EP - 1804
BT - 2025 International Conference on Rehabilitation Robotics, ICORR 2025
PB - IEEE Computer Society
Y2 - 12 May 2025 through 16 May 2025
ER -