First Advisor

Susan Masta

Date of Award

Spring 5-2022

Document Type


Degree Name

Bachelor of Science (B.S.) in Biology and University Honors






Robotic exoskeletons -- Research, Cerebrovascular disease -- Patients -- Rehabilitation, Cerebrovascular disease -- Physical therapy -- Technological innovations, Gait disorders, Hemiplegics, Robotics in medicine




Robotic-assisted gait training has been cited as a potential rehabilitation intervention for the recovery of ambulation in hemiplegic stroke patients. Previous reviews on robotic gait training have elicited a need for more randomized, clinical studies on robotic gait training for the development of evidence-based intervention protocols and elimination of research bias. The purpose of this scoping review was to provide an updated examination of the clinical research on robotic assisted gait training and address any research gaps to be considered for future research. This review included randomized, clinical trials on stroke patients with a robotic-assisted treatment (RAGT) and conventional gait training (CGT) group. This review included studies observing the following outcome measures: Functional Ambulatory Category, Gait Speed, 6-minute Walking Test, Berg Balance Scale, Fugl-Meyer Assessment, and Modified Ashworth Scale. Screening on Web of Science and PubMed revealed 11 studies for review from an initial pool of 231 unique titles. Studies focused on subacute stroke patients, non-ambulatory subjects, and longer intervention protocols were more likely to observe clinically meaningful improvements in outcome. RAGT groups were more likely to observe greater improvements in outcome than CGT groups. However, individual studies observed relatively few significant differences between treatment groups. Clinical trials on robotic-assisted gait training for stroke patients were at different stages in research, based on the assistive device in question. Future clinical trials should focus on cost-effectiveness of RAGT, proper intervention dosage, and personalization of RAGT based on stroke subject characteristics.


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