The development of an adaptive upper-limb stroke rehabilitation robotic system

Kan Patricia, Huq Rajibul, Hoey Jesse, Goetschalckx Robby, Mihailidis, Mihailidis Alex

Description

Stroke is the primary cause of adult disability. To support this large population in recovery, robotic technologies are being developed to assist in the delivery of rehabilitation. This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The system uses a decision theoretic model (a partially observable Markov decision process, or POMDP) as its primary engine for decision making. The POMDP allows the system to automatically modify exercise parameters to account for the specific needs and abilities of different individuals, and to use these parameters to take appropriate decisions about stroke rehabilitation exercises. Methods The performance of the system was evaluated by comparing the decisions made by the system with those of a human therapist. A single patient participant was paired up with a therapist participant for the duration of the study, for a total of six sessions. Each session was an hour long and occurred three times a week for two weeks. During each session, three steps were followed: (A) after the system made a decision, the therapist either agreed or disagreed with the decision made; (B) the researcher had the device execute the decision made by the therapist; (C) the patient then performed the reaching exercise. These parts were repeated in the order of A-B-C until the end of the session. Qualitative and quantitative question were asked at the end of each session and at the completion of the study for both participants. Results Overall, the therapist agreed with the system decisions approximately 65% of the time. In general, the therapist thought the system decisions were believable and could envision this system being used in both a clinical and home setting. The patient was satisfied with the system and would use this system as his/her primary method of rehabilitation. Conclusions The data collected in this study can only be used to provide insight into the performance of the system since the sample size was limited. The next stage for this project is to test the system with a larger sample size to obtain significant results.

Informations

• Publié par: biomed
• Publié le: 01 janvier 2011
• Nombre de lectures: 2
• Langue: English
• Poids de l'ouvrage: 2 Mo

Extrait

Kanet al.Journal of NeuroEngineering and Rehabilitation2011,8:33 http://www.jneuroengrehab.com/content/8/1/33

JOURNAL OF NEUROENGINEERING J N E R AND REHABILITATION

R E S E A R C HOpen Access The development of an adaptive upperlimb stroke rehabilitation robotic system 1 12 21,3,4* Patricia Kan , Rajibul Huq , Jesse Hoey , Robby Goetschalckxand Alex Mihailidis

Abstract Background:Stroke is the primary cause of adult disability. To support this large population in recovery, robotic technologies are being developed to assist in the delivery of rehabilitation. This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upperlimb reaching task. The system uses a decision theoretic model (a partially observable Markov decision process, or POMDP) as its primary engine for decision making. The POMDP allows the system to automatically modify exercise parameters to account for the specific needs and abilities of different individuals, and to use these parameters to take appropriate decisions about stroke rehabilitation exercises. Methods:The performance of the system was evaluated by comparing the decisions made by the system with those of a human therapist. A single patient participant was paired up with a therapist participant for the duration of the study, for a total of six sessions. Each session was an hour long and occurred three times a week for two weeks. During each session, three steps were followed: (A) after the system made a decision, the therapist either agreed or disagreed with the decision made; (B) the researcher had the device execute the decision made by the therapist; (C) the patient then performed the reaching exercise. These parts were repeated in the order of ABC until the end of the session. Qualitative and quantitative question were asked at the end of each session and at the completion of the study for both participants. Results:Overall, the therapist agreed with the system decisions approximately 65% of the time. In general, the therapist thought the system decisions were believable and could envision this system being used in both a clinical and home setting. The patient was satisfied with the system and would use this system as his/her primary method of rehabilitation. Conclusions:The data collected in this study can only be used to provide insight into the performance of the system since the sample size was limited. The next stage for this project is to test the system with a larger sample size to obtain significant results.

Background Stroke is the leading cause of physical disability and third leading cause of death in most countries around the world, including Canada [1] and the United States [2]. The consequences of stroke are devastating with approximately 75% of stroke sufferers being left with a permanent disability [3]. Research has shown that stroke rehabilitation can reduce the impairments and disabilities that are caused

* Correspondence: [e-mail] 1 Institute of Biomaterials and Biomedical Engineering, Rosebrugh Building, 164 College Street, Room 407, University of Toronto, Toronto, M5T 1P7, Canada Full list of author information is available at the end of the article

by stroke, and improve motor function, allowing stroke patients to regain much of their independence and qual ity of life. It is generally agreed that intensive, repetitive, and goaldirected rehabilitation improves motor func tion and cortical reorganization in stroke patients with both acute and longterm (chronic) impairments [4]. However, this recovery process is typically slow and laborintensive, usually involving extensive interaction between one or more therapists and one patient. One of the main motivations for developing rehabilitation robotic devices is to automate interventions that are normally repetitive and physically demanding. These robots can provide stroke patients with intensive and reproducible movement training in timeunlimited

© 2011 Kan et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.