Investigating the feasibility and acceptability of real-time visual feedback in reducing compensatory motions during self-administered stroke rehabilitation exercises: A pilot study with chronic stroke survivors.

Graded Repetitive Arm Supplementary Program Stroke rehabilitation self-administered rehabilitation exercise upper limb exercises visual feedback

Journal

Journal of rehabilitation and assistive technologies engineering
ISSN: 2055-6683
Titre abrégé: J Rehabil Assist Technol Eng
Pays: England
ID NLM: 101671667

Informations de publication

Date de publication:
Historique:
received: 08 10 2018
accepted: 22 01 2019
entrez: 28 6 2019
pubmed: 28 6 2019
medline: 28 6 2019
Statut: epublish

Résumé

Homework-based rehabilitation programs can help stroke survivors restore upper extremity function. However, compensatory motions can develop without therapist supervision, leading to sub-optimal recovery. We developed a visual feedback system using a live video feed or an avatar reflecting users' movements so users are aware of compensations. This pilot study aimed to evaluate validity (how well the avatar characterizes different types of compensations) and acceptability of the system. Ten participants with chronic stroke performed upper-extremity exercises under three feedback conditions: none, video, and avatar. Validity was evaluated by comparing agreement on compensations annotated using video and avatar images. A usability survey was administered to participants after the experiment to obtain information on acceptability. There was substantial agreement between video and avatar images for shoulder elevation and hip extension (Cohen's κ: 0.6-0.8) and almost perfect agreement for trunk rotation and flexion (κ: 0.80-1). Acceptability was low due to lack of corrective prompts and occasional noise with the avatar display. Most participants suggested that an automatic compensation detection feature with visual and auditory cuing would improve the system. The avatar characterized four types of compensations well. Future work will involve increasing sensitivity for shoulder elevation and implementing a method to detect compensations.

Identifiants

pubmed: 31245031
doi: 10.1177/2055668319831631
pii: 10.1177_2055668319831631
pmc: PMC6582280
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2055668319831631

Déclaration de conflit d'intérêts

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Auteurs

Shayne Lin (S)

Division of Engineering Science, University of Toronto, Toronto, Canada.

Jotvarinder Mann (J)

Toronto Rehabilitation Institute, University Health Network, Toronto, Canada.
Department of Kinesiology, University of Waterloo, Waterloo, Canada.

Avril Mansfield (A)

Toronto Rehabilitation Institute, University Health Network, Toronto, Canada.
Department of Physical Therapy, University of Toronto, Toronto, Canada.
Evaluative Clinical Sciences, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada.

Rosalie H Wang (RH)

Toronto Rehabilitation Institute, University Health Network, Toronto, Canada.
Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Canada.

Jocelyn E Harris (JE)

School of Rehabilitation Sciences, McMaster University, Hamilton, Canada.

Babak Taati (B)

Toronto Rehabilitation Institute, University Health Network, Toronto, Canada.
Department of Computer Science, University of Toronto, Toronto, Canada.
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada.

Classifications MeSH