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Bilateral Tactile Feedback-Enabled Training for Stroke Survivors Using Microsoft KinectTM
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0001-6525-7665
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Department of Rehabilitation, Fujita Health University, Nanakuri Memorial Hospital, Tsu, Japan.ORCID iD: 0000-0001-9858-5809
Schools of Mechatronics Systems Engineering and Engineering Science, Simon Fraser University, Surrey, Canada.
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2019 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 16, article id 3474Article in journal (Refereed) Published
Abstract [en]

Rehabilitation and mobility training of post-stroke patients is crucial for their functional recovery. While traditional methods can still help patients, new rehabilitation and mobility training methods are necessary to facilitate better recovery at lower costs. In this work, our objective was to design and develop a rehabilitation training system targeting the functional recovery ofpost-stroke users with high efficiency. To accomplish this goal, we applied a bilateral training method, which proved to be effective in enhancing motor recovery using tactile feedback for the training. One participant with hemiparesis underwent six weeks of training. Two protocols, “contralater alarm matching” and “both arms moving together”, were carried out by the participant. Each ofthe protocols consisted of “shoulder abduction” and “shoulder flexion” at angles close to 30 and 60 degrees. The participant carried out 15 repetitions at each angle for each task. For example, in the“contralateral arm matching” protocol, the unaffected arm of the participant was set to an angle close to 30 degrees. He was then requested to keep the unaffected arm at the specified angle while trying to match the position with the affected arm. Whenever the two arms matched, a vibration was given on both brachialis muscles. For the “both arms moving together” protocol, the two arms were first set approximately to an angle of either 30 or 60 degrees. The participant was asked to return both arms to a relaxed position before moving both arms back to the remembered specified angle.The arm that was slower in moving to the specified angle received a vibration. We performed clinical assessments before, midway through, and after the training period using a Fugl-Meyer assessment (FMA), a Wolf motor function test (WMFT), and a proprioceptive assessment. For the assessments, two ipsilateral and contralateral arm matching tasks, each consisting of three movements (shoulder abduction, shoulder flexion, and elbow flexion), were used. Movements were performed at two angles, 30 and 60 degrees. For both tasks, the same procedure was used. For example, in the case of the ipsilateral arm matching task, an experimenter positioned the affected arm of the participant at 30 degrees of shoulder abduction. The participant was requested to keep the arm in that positionfor ~5 s before returning to a relaxed initial position. Then, after another ~5-s delay, the participant moved the affected arm back to the remembered position. An experimenter measured this shoulder abduction angle manually using a goniometer. The same procedure was repeated for the 60 degree angle and for the other two movements. We applied a low-cost Kinect to extract the participant’s body joint position data. Tactile feedback was given based on the arm position detected by the Kinect sensor. By using a Kinect sensor, we demonstrated the feasibility of the system for the training ofa post-stroke user. The proposed system can further be employed for self-training of patients at home. The results of the FMA, WMFT, and goniometer angle measurements showed improvements in several tasks, suggesting a positive effect of the training system and its feasibility for further application for stroke survivors’ rehabilitation. © 2019 by the authors.

Place, publisher, year, edition, pages
Basel: MDPI, 2019. Vol. 19, no 16, article id 3474
Keywords [en]
Kinect, stroke rehabilitation, bilateral training, tactile feedback
National Category
Physiotherapy
Identifiers
URN: urn:nbn:se:hh:diva-41229DOI: 10.3390/s19163474ISI: 000484407200031PubMedID: 31398957Scopus ID: 2-s2.0-85071280266OAI: oai:DiVA.org:hh-41229DiVA, id: diva2:1377330
Note

Funder: Canadian Institutes of Health Research (CIHR), (Grant Number: 353444)

Available from: 2019-12-11 Created: 2019-12-11 Last updated: 2020-01-21Bibliographically approved

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Orand, AbbasErdal Aksoy, ErenMiyasaka, HiroyukiMenon, Carlo
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