Pai-Chuan Huang1, Yu-Wei Hsieh2, Chin-Man Wang3, Ching-Yi Wu4, Shu-Chun Huang5, Keh-Chung Lin6. 1. Pai-Chuan Huang, ScD, OTR/L, is Postdoctoral Fellow, Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan, and Healthy Aging Research Center at Chang Gung University, Taoyuan, Taiwan. 2. Yu-Wei Hsieh, PhD, is Assistant Professor, Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan, and Healthy Aging Research Center at Chang Gung University, Taoyuan, Taiwan. 3. Chin-Man Wang, MD, is Attending Physician, Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou, Taiwan. 4. Ching-Yi Wu, ScD, OTR/L, is Professor and Chair, Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan, and Healthy Aging Research Center at Chang Gung University, Taoyuan, Taiwan. 5. Shu-Chun Huang, MD, is Attending Physician, Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou, Taiwan. 6. Keh-Chung Lin, ScD, OTR/L, is Professor, School of Occupational Therapy, College of Medicine, National Taiwan University and Division of Occupational Therapy, Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, 17, F4, Xu Zhou Road, Taipei, Taiwan; kehchunglin@ntu.edu.tw.
Abstract
OBJECTIVE: A subgroup of patients benefiting most from robot-assisted therapy (RT) has not yet been described. We examined the predictors of improved outcomes after RT. METHOD: Sixty-six patients with stroke receiving RT were analyzed. The outcome measures were the Fugl-Meyer Assessment (FMA), Wolf Motor Function Test (WMFT), Motor Activity Log (MAL), and Stroke Impact Scale (SIS). The potential predictors were age, side of lesion, time since onset, Modified Ashworth Scale (MAS) scores, accelerometer data, Box and Block Test (BBT) scores, and kinematic parameters. RESULTS: BBT scores were predictive of FMA (29%) and MAL (9%-15%) improvements. Reduced shoulder flexion synergy, as measured by less shoulder abduction during forward reach, and MAS-distal were predictive of WMFT-function improvements. MAS-distal was predictive of SIS-physical improvements. Demographic variables did not predict outcomes. CONCLUSION: Manual dexterity was a valuable predictor of motor impairment and daily function after RT. Outcomes at different levels may have different predictors.
OBJECTIVE: A subgroup of patients benefiting most from robot-assisted therapy (RT) has not yet been described. We examined the predictors of improved outcomes after RT. METHOD: Sixty-six patients with stroke receiving RT were analyzed. The outcome measures were the Fugl-Meyer Assessment (FMA), Wolf Motor Function Test (WMFT), Motor Activity Log (MAL), and Stroke Impact Scale (SIS). The potential predictors were age, side of lesion, time since onset, Modified Ashworth Scale (MAS) scores, accelerometer data, Box and Block Test (BBT) scores, and kinematic parameters. RESULTS: BBT scores were predictive of FMA (29%) and MAL (9%-15%) improvements. Reduced shoulder flexion synergy, as measured by less shoulder abduction during forward reach, and MAS-distal were predictive of WMFT-function improvements. MAS-distal was predictive of SIS-physical improvements. Demographic variables did not predict outcomes. CONCLUSION: Manual dexterity was a valuable predictor of motor impairment and daily function after RT. Outcomes at different levels may have different predictors.