Ken Tomida1, Shigeru Sonoda2, Satoshi Hirano3, Akira Suzuki4, Genichi Tanino5, Kenji Kawakami4, Eiichi Saitoh3, Hitoshi Kagaya3. 1. Fujita Health University Nanakuri Memorial Hospital, Tsu, Mie, Japan. Electronic address: k-tomida@fujita-hu.ac.jp. 2. Fujita Health University Nanakuri Memorial Hospital, Tsu, Mie, Japan; Department of Rehabilitation Medicine II, School of Medicine, Fujita Health University, Tsu, Mie, Japan. 3. Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan. 4. Fujita Health University Nanakuri Memorial Hospital, Tsu, Mie, Japan. 5. Joint Research Support Promotion Facility, Center for Research Promotion and Support, Fujita Health University, Toyoake, Aichi, Japan.
Abstract
PURPOSE: This trial aimed to validate the effectiveness of using the Gait Exercise Assist Robot (GEAR) in patients with hemiplegia after primary stroke. METHODS: The study design was open-label randomized controlled trial. Twenty-six patients with hemiplegia after primary stroke admitted to the comprehensive inpatient rehabilitation wards were enrolled and randomized to a group using GEAR in gait training and a control group. The intervention period was 4 weeks. Evaluations were conducted at admission, during intervention period, 8 weeks from start of intervention, and at discharge. Primary outcome measure was improvement efficiency of Functional Independence Measure (FIM)-walk score (FIM-walk improvement efficiency) that was calculated at the time of achieving FIM-walk score 5 (supervision level) during the intervention period or as weekly gain in FIM-walk score during 4 weeks for those who did not achieve score 5. RESULTS:FIM-walk improvement efficiency was .7 ± .4 in GEAR group and .4 ± .3 in control group, and was significantly higher in GEAR group (P = .01). The FIM-walk score gain after 4 weeks was significantly higher in the GEAR group (P = .01), but there were no significant differences between 2 groups after 8 weeks and at discharge. CONCLUSIONS:Gait training using GEAR for 4 weeks improved walking ability of subacute stroke patients. GEAR contributes to early improvement of walking ability probably by the knee flexion assist during swing phase on the paralyzed side thereby increasing the volume of training, and by the finely adjustable stance/swing assist mechanism for the paralyzed limb which optimizes the training difficulty level.
RCT Entities:
PURPOSE: This trial aimed to validate the effectiveness of using the Gait Exercise Assist Robot (GEAR) in patients with hemiplegia after primary stroke. METHODS: The study design was open-label randomized controlled trial. Twenty-six patients with hemiplegia after primary stroke admitted to the comprehensive inpatient rehabilitation wards were enrolled and randomized to a group using GEAR in gait training and a control group. The intervention period was 4 weeks. Evaluations were conducted at admission, during intervention period, 8 weeks from start of intervention, and at discharge. Primary outcome measure was improvement efficiency of Functional Independence Measure (FIM)-walk score (FIM-walk improvement efficiency) that was calculated at the time of achieving FIM-walk score 5 (supervision level) during the intervention period or as weekly gain in FIM-walk score during 4 weeks for those who did not achieve score 5. RESULTS: FIM-walk improvement efficiency was .7 ± .4 in GEAR group and .4 ± .3 in control group, and was significantly higher in GEAR group (P = .01). The FIM-walk score gain after 4 weeks was significantly higher in the GEAR group (P = .01), but there were no significant differences between 2 groups after 8 weeks and at discharge. CONCLUSIONS: Gait training using GEAR for 4 weeks improved walking ability of subacute strokepatients. GEAR contributes to early improvement of walking ability probably by the knee flexion assist during swing phase on the paralyzed side thereby increasing the volume of training, and by the finely adjustable stance/swing assist mechanism for the paralyzed limb which optimizes the training difficulty level.
Authors: Lisa R Treviño; Peter Roberge; Michael E Auer; Angela Morales; Annelyn Torres-Reveron Journal: Front Neurorobot Date: 2021-06-10 Impact factor: 2.650