Comparative effects of passive and active mode robot-assisted gait training on brain and muscular activities in sub-acute and chronic stroke.

Journal: NeuroRehabilitation
PMID: 35311717

Abstract

BACKGROUND: Robot-assisted gait training (RAGT) was initially developed based on the passive controlled (PC) mode, where the target or ideal locomotor kinematic trajectory is predefined and a patient basically 'rides' the robot instead of actively participating in the actual locomotor relearning process. A new insightful contemporary neuroscience and mechatronic evidence suggest that robotic-based locomotor relearning can be best achieved through active interactive (AI) mode rather than PC mode.

Authors

  • Jiwon Shin
    Radiology Artificial Intelligence Lab (RAIL), Malone Center for Engineering in Healthcare, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA.
  • HongGi An
    Osstem Implant Co., Ltd, Seoul, South Korea.
  • Sejung Yang
    Medical Physics Division, Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, United States of America.
  • Chanhee Park
    Sports(Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea.
  • Yongseok Lee
    Myongji-Choonhey Rehabilitation Hospital, Seoul, Republic of Korea.
  • Sung Joshua H You
    Sports Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea.

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