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Ung Hee Lee

Showing results (1-10 of 4) with videos related to

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IEEE ... International Conference on Rehabilitation Robotics : [Proceedings]|July 11, 2025
Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed SimulationYi-Hung Chiu, Ung Hee Lee, Changseob Song, et al.
Science Robotics|October 18, 2023
User preference optimization for control of ankle exoskeletons using sample efficient active learningUng Hee Lee, Varun S Shetty, Patrick W Franks, et al.
Journal of Neuroengineering and Rehabilitation|October 13, 2017
Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-conceptJunkai Xu, Tian Bao, Ung Hee Lee, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|March 9, 2017
Detecting voluntary gait intention of chronic stroke patients towards top-down gait rehabilitation using EEGJunhyuk Choi, Hyolim Kang, Sang Hun Chung, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
IEEE ... International Conference on Rehabilitation Robotics : [Proceedings]|July 11, 2025
Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed SimulationYi-Hung Chiu, Ung Hee Lee, Changseob Song, et al.
Science Robotics|October 18, 2023
User preference optimization for control of ankle exoskeletons using sample efficient active learningUng Hee Lee, Varun S Shetty, Patrick W Franks, et al.
Journal of Neuroengineering and Rehabilitation|October 13, 2017
Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-conceptJunkai Xu, Tian Bao, Ung Hee Lee, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|March 9, 2017
Detecting voluntary gait intention of chronic stroke patients towards top-down gait rehabilitation using EEGJunhyuk Choi, Hyolim Kang, Sang Hun Chung, et al.
Pageof 1