A novel adaptive mixed reality system for stroke rehabilitation: Principles, proof of concept, and preliminary application in 2 patients

Topics in Stroke Rehabilitation

Volumn 18, Issue 3, 2011, Pages 212-230

  Chen, Yinpeng ^a   Duff, Margaret ^a,b   Lehrer, Nicole ^a   Liu, Sheng Min ^c   Blake, Paul ^c   Wolf, Steven L ^d   Sundaram, Hari ^a   Rikakis, Thanassis ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

^b Arizona State University   (United States)

^c Banner Baywood Medical Center   (United States)

^d EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

adaptive therapy; computational motion capture; kinematic analysis; mixed reality rehabilitation; multimedia feedback; reach and grasp; upper extremity

Indexed keywords

ADAPTIVE MIXED REALITY REHABILITATION SYSTEM; AGED; ARTICLE; AUDITORY FEEDBACK; BODY MOVEMENT; CASE REPORT; CLINICAL ASSESSMENT; CLINICAL STUDY; COMPUTER ASSISTED THERAPY; EVALUATION; GOAL ATTAINMENT; HEALTH CARE PERSONNEL; HUMAN; INTERMETHOD COMPARISON; KINEMATICS; KNOWLEDGE; MALE; MOTOR PERFORMANCE; OBSERVATIONAL METHOD; PRACTICE GUIDELINE; QUANTITATIVE ANALYSIS; REHABILITATION CARE; STROKE; STROKE PATIENT; TREATMENT DURATION; VISUAL FEEDBACK;

BIOFEEDBACK, PSYCHOLOGY; BIOMECHANICS; HUMANS; MALE; MOVEMENT; REALITY THERAPY; STROKE; UPPER EXTREMITY; USER-COMPUTER INTERFACE;

EID: 79958166668     PISSN: 10749357     EISSN: 19455119     Source Type: Journal    
DOI: 10.1310/tsr1803-212     Document Type: Article

References (24)

1. Schmidt RA. Motor learning principles for physical therapy. Contemporary Management of Motor Control Problems: Proceedings of the II STEP Conference. 1991:49-62.
2. Holden MK. Virtual environments for motor rehabilitation: review. Cyber Psychol Behav. 2005;8:187-211. (Pubitemid 40847797)
3. Sveistrup H. Motor rehabilitation using virtual reality. J Neuro Engineering Rehabil. 2004;1:10-17.
4. Subramanian S, Knaut LA, Beaudoin C, McFadyen BJ, Feldman AG, Levin MF. Virtual reality environments for post-stroke arm rehabilitation. J Neuroengineering Rehabil. 2007;4:20-24.
5. Jung Y, Yeh S, Stewart J. Tailoring virtual reality technology for stroke rehabilitation: a human factors design. Conference on Human Factors in Computing Systems. 2006;929-934.
6. Piron L, Tonin P, Piccione F, Iaia V, Trivello E, Dam M. Virtual environment training therapy for arm motor rehabilitation. Presence: Teleoperators Virtual Environ. 2005;14:732-740.
7. Cirstea MC, Levin MF. Improvement of arm movement patterns and endpoint control depends on type of feedback during practice in stroke survivors. Neurorehabil Neural Repair. 2007;21:398-411. (Pubitemid 47246436)
8. Jack D, Boian R, Merians AS, et al. Virtual realityenhanced stroke rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2001;9:308-318.
9. Wagner JM, Rhodes JA, Patten C. Reproducibility and minimal detectable change of threedimensional kinematic analysis of reaching tasks in people with hemiparesis after stroke. Phys Ther. 2008;88:652-663. (Pubitemid 351620016)
10. Pridmore T, Green J, Hilton D, Eastgate R, Cobb S. Mixed reality environments in stroke rehabilitation: interfaces across the real/virtual divide. In: Proceedings of the 5th International Conference on Disability, Virtual Reality & Associated Technology, Oxford, UK, 2004:1-17.
11. Lehrer N, Attygalle S, Wolf SL, Rikakis T. Exploring the bases for a mixed reality stroke rehabilitation system: part I. a unified approach for representing action, quantitative evaluation, and interactive feedback. Submitted for publication.
12. Cirstea MC, Levin MF. Compensatory strategies for reaching in stroke. Brain. 2000;123:940-953. (Pubitemid 30224190)
13. Roby-Brami A, Fuchs S, Mokhtari M, Bussel B. Reaching and grasping strategies in hemiparetic patients. Motor Function. 1997;1:72-91.
14. Levin MF, Kleim JA, Wolf SL. What do motor "recovery" and "compensation" mean in patients following stroke? Neurorehabil Neural Repair. 2009;23(4):313-319.
15. Chen Y, Duff M, Lehrer N, et al. A computational framework for quantitative evaluation of movement during rehabilitation. International Symposium on Computational Models for Life Sciences; October 2011; Japan.
16. Lehrer N, Attygalle S, Chen Y, Wolf SL, Rikakis T. Exploring the bases for a mixed reality stroke rehabilitation system: part II. Application of principles for the design of interactive feedback for upper limb rehabilitation. Submitted for publication.
17. Duff M, Chen Y, Attygalle S, et al. An adaptive mixed reality training system for stroke rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2010;18(5):531-541.
18. McPartland DD, Krebs DE, Wall C. Quantifying ataxia: ideal trajectory analysis - a technical note. J Rehabil Res Dev. 2000;37(4):445-454. (Pubitemid 32065907)
19. Xu W, Sundaram H. Information dense summaries for review of patient performance in biofeedback rehabilitation. Paper presented at: SIG ACM Multimedia; September 2007; Augsburg, Germany.
20. Uswatte G, Taub E, Morris D, Light K, Thompson PA. The Motor Activity Log-28: assessing daily use of the hemiparetic arm after stroke. Neurol Rep. 2006;67:1189-1194. (Pubitemid 44563826)
21. Duncan PW, Wallace D, Lai SM, Johnson D, Embretson S, Laster LJ. The Stroke Impact Scale version 2.0: evaluation of reliability, validity, and sensitivity. Stroke. 1999;30:2131-2140. (Pubitemid 29473260)
22. Wolf SL, Catlin PA, Ellis M, Archer AL, Morgan B, Piacentino A. Assessing Wolf Motor Function Test as outcome measure for research in patients after stroke. Stroke. 2001;32:1635-1639. (Pubitemid 32631916)
23. Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S. The poststroke hemiplegic patient: 1. a method for evaluation of physical performance. Scand J Rehab Med. 1975;7:13-31.
24. Krakauer JW. Motor learning: its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol. 2006;19:84-90. (Pubitemid 43172710)