Enhancing Post-Stroke Gait Rehabilitation with Robot-Assisted Therapy: A Focus on Step Repetitions and Neuroplasticity

Background: Stroke is a leading cause of disability worldwide, with gait impairments significantly affecting patients' independence and quality of life. Gait recovery relies heavily on neuroplasticity, which requires highrepetition, task-specific training. Conventional rehabilitation often fails to provide enough repetitions, and the shortage of therapists further highlights the need for alternative solutions. Objective: This study explores the role of robot-assisted gait training (RAGT) in post-stroke patients, focusing on the number of repetitions achieved during the therapy. Material and methods: Data from 264 therapies conducted on 132 poststroke patients who underwent treatment with the RAGT end-effector system, collected from five different facilities, were analysed. Results: Data analysis revealed that during therapy using an end-effectorbased RAGT system, patients achieved an average of 1098 ± 325 steps in the first session and 1529 ± 298 steps in the final session, representing a 39% increase in step count throughout the entire treatment program. Conclusion: The end-effector-based RAGT system addresses core neuroplasticity principles with an emphasis on high repetition rates, enabling patients to achieve up to three times the number of repetitions compared to conventional therapy. Given the increasing number of stroke survivors and the shortage of qualified personnel, the RAGT system presents a promising solution for the future of post-stroke gait rehabilitation.

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Publication Details

Journal
Archives of Clinical and Biomedical Research
Published
2025-01-01
DOI
https://doi.org/10.26502/acbr.50170453
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
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article

Enhancing Post-Stroke Gait Rehabilitation with Robot-Assisted Therapy: A Focus on Step Repetitions and Neuroplasticity

Andrew W. Pichardo, Martin Malovec
Archives of Clinical and Biomedical Research
Stroke Rehabilitation and Recovery
article

Enhancing Post-Stroke Gait Rehabilitation with Robot-Assisted Therapy: A Focus on Step Repetitions and Neuroplasticity

Andrew W. Pichardo, Martin Malovec
article en

Abstract

Background: Stroke is a leading cause of disability worldwide, with gait impairments significantly affecting patients' independence and quality of life. Gait recovery relies heavily on neuroplasticity, which requires highrepetition, task-specific training. Conventional rehabilitation often fails to provide enough repetitions, and the shortage of therapists further highlights the need for alternative solutions. Objective: This study explores the role of robot-assisted gait training (RAGT) in post-stroke patients, focusing on the number of repetitions achieved during the therapy. Material and methods: Data from 264 therapies conducted on 132 poststroke patients who underwent treatment with the RAGT end-effector system, collected from five different facilities, were analysed. Results: Data analysis revealed that during therapy using an end-effectorbased RAGT system, patients achieved an average of 1098 ± 325 steps in the first session and 1529 ± 298 steps in the final session, representing a 39% increase in step count throughout the entire treatment program. Conclusion: The end-effector-based RAGT system addresses core neuroplasticity principles with an emphasis on high repetition rates, enabling patients to achieve up to three times the number of repetitions compared to conventional therapy. Given the increasing number of stroke survivors and the shortage of qualified personnel, the RAGT system presents a promising solution for the future of post-stroke gait rehabilitation.

Archives of Clinical and Biomedical ResearchVol. 9(3)
Openalex Percentile: Top 84%
Stroke Rehabilitation and Recovery
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Enhancing Post-Stroke Gait Rehabilitation with Robot-Assisted Therapy: A Focus on Step Repetitions and Neuroplasticity — Andrew W. Pichardo, Martin Malovec · Archives of Clinical and Biomedical Research (2025) | TGRS Research Map | TGRS