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Article type: Research Article
Authors: Shin, Jiwona; b | An, HongGic | Yang, Sejungd | Park, Chanheea; b | Lee, Yongseoke | You, Sung (Joshua) H.a; b; *
Affiliations: [a] Sports Movement Artificial-Intelligence Robotics Technology (SMART) Institute, Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea | [b] Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea | [c] Osstem Implant Co., Ltd, Seoul, South Korea | [d] Department of Biomedical Engineering, Yonsei University, Wonju, Republic of Korea | [e] Myongji-Choonhey Rehabilitation Hospital, Seoul, Republic of Korea
Correspondence: [*] Address for correspondence: Sung (Joshua) H. You, PT, PhD, 1 Yonseidae-gil, Wonju, Gangwon-do 26493, Republic of Korea. Tel.: +82 33 760 2476; Fax: +82 33 760 2496; E-mail: [email protected].
Note: [1] This article received a correction notice (Erratum) post publication with DOI 10.3233/NRE-230004, available at http://doi.org/10.3233/NRE-230004.
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. OBJECTIVE:The purpose of this study was to compare the pattern of gait-related cortical activity, specifically gait event-related spectral perturbations (ERSPs), and muscle activity from the tibialis anterior (TA) and clinical functional tests in subacute and chronic stroke patients during robot-assisted gait training (RAGT) in passive controlled (PC) and active interactive (AI) modes. METHODS:The present study involves a two-group pretest-posttest design in which two groups (i.e., PC-RAGT group and AI-RAGT group) of 14 stroke subjects were measured to assess changes in ERSPs, the muscle activation of TA, and the clinical functional tests, following 15– 18 sessions of intervention according to the protocol of each group. RESULTS:Our preliminary results demonstrated that the power in the μ band (8– 12 Hz) was increased in the leg area of sensorimotor cortex (SMC) and supplementary motor area (SMA) at post-intervention as compared to pre-intervention in both groups. Such cortical neuroplasticity change was associated with TA muscle activity during gait and functional independence in functional ambulation category (FAC) and motor coordination in Fugl– Meyer Assessment for lower extremity (FMA-LE) test as well as spasticity in the modified Ashworth scale (MAS) measures. CONCLUSIONS:We have first developed a novel neuroimaging experimental paradigm which distinguished gait event related cortical involvement between pre- and post-intervention with PC-RAGT and AI-RAGT in individuals with subacute and chronic hemiparetic stroke.
Keywords: Walkbot, Robotic assisted gait training, gait event-related spectral perturbations, electroencephalography
DOI: 10.3233/NRE-210304
Journal: NeuroRehabilitation, vol. 51, no. 1, pp. 51-63, 2022
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