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Journal of NeuroEngineering and Rehabilitation
Published in: Journal of NeuroEngineering and Rehabilitation 1/2010

Open Access 01-12-2010 | Research

Neurorehabilitation using the virtual reality based Rehabilitation Gaming System: methodology, design, psychometrics, usability and validation

Authors: Mónica S Cameirão, Sergi Bermúdez i Badia, Esther Duarte Oller, Paul FMJ Verschure

Published in: Journal of NeuroEngineering and Rehabilitation | Issue 1/2010

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Abstract

Background

Stroke is a frequent cause of adult disability that can lead to enduring impairments. However, given the life-long plasticity of the brain one could assume that recovery could be facilitated by the harnessing of mechanisms underlying neuronal reorganization. Currently it is not clear how this reorganization can be mobilized. Novel technology based neurorehabilitation techniques hold promise to address this issue. Here we describe a Virtual Reality (VR) based system, the Rehabilitation Gaming System (RGS) that is based on a number of hypotheses on the neuronal mechanisms underlying recovery, the structure of training and the role of individualization. We investigate the psychometrics of the RGS in stroke patients and healthy controls.

Methods

We describe the key components of the RGS and the psychometrics of one rehabilitation scenario called Spheroids. We performed trials with 21 acute/subacute stroke patients and 20 healthy controls to study the effect of the training parameters on task performance. This allowed us to develop a Personalized Training Module (PTM) for online adjustment of task difficulty. In addition, we studied task transfer between physical and virtual environments. Finally, we assessed the usability and acceptance of the RGS as a rehabilitation tool.

Results

We show that the PTM implemented in RGS allows us to effectively adjust the difficulty and the parameters of the task to the user by capturing specific features of the movements of the arms. The results reported here also show a consistent transfer of movement kinematics between physical and virtual tasks. Moreover, our usability assessment shows that the RGS is highly accepted by stroke patients as a rehabilitation tool.

Conclusions

We introduce a novel VR based paradigm for neurorehabilitation, RGS, which combines specific rehabilitative principles with a psychometric evaluation to provide a personalized and automated training. Our results show that the RGS effectively adjusts to the individual features of the user, allowing for an unsupervised deployment of individualized rehabilitation protocols.
Appendix
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Literature
1.
Hendricks HT, van Limbeek J, Geurts AC, Zwarts MJ: Motor recovery after stroke: a systematic review of the literature. Arch Phys Med Rehabil 2002, 83: 1629-1637. 10.1053/apmr.2002.35473CrossRefPubMed
2.
3.
Strong K, Mathers C, Bonita R: Preventing stroke: saving lives around the world. Lancet Neurol 2007, 6: 182-187. 10.1016/S1474-4422(07)70031-5CrossRefPubMed
4.
WHO: The global burden of disease: 2004 update. In Book The global burden of disease: 2004 update (Editor ed.^eds.). City: World Health Organization; 2008.
5.
Nudo RJ: Postinfarct cortical plasticity and behavioral recovery. Stroke 2007, 38: 840-845. 10.1161/01.STR.0000247943.12887.d2CrossRefPubMed
6.
Seitz RJ, Butefisch CM, Kleiser R, Homberg V: Reorganisation of cerebral circuits in human ischemic brain disease. Restor Neurol Neurosci 2004, 22: 207-229.PubMed
7.
Murphy TH, Corbett D: Plasticity during stroke recovery: from synapse to behaviour. Nat Rev Neurosci 2009, 10: 861-872. 10.1038/nrn2735CrossRefPubMed
8.
Altschuler EL, Wisdom SB, Stone L, Foster C, Galasko D, Llewellyn DME, Ramachandran VS: Rehabilitation of hemiparesis after stroke with a mirror. The Lancet 1999, 353: 2035-2036. 10.1016/S0140-6736(99)00920-4CrossRef
9.
Bhatt E, Nagpal A, Greer KH, Grunewald TK, Steele JL, Wiemiller JW, Lewis SM, Carey JR: Effect of finger tracking combined with electrical stimulation on brain reorganization and hand function in subjects with stroke. Exp Brain Res 2007, 182: 435-447. 10.1007/s00221-007-1001-5CrossRefPubMed
10.
Blanton S, Wilsey H, Wolf SL: Constraint-induced movement therapy in stroke rehabilitation: perspectives on future clinical applications. NeuroRehabilitation 2008, 23: 15-28.PubMed
11.
Butler AJ, Page SJ: Mental practice with motor imagery: evidence for motor recovery and cortical reorganization after stroke. Arch Phys Med Rehabil 2006, 87: S2-11. 10.1016/j.apmr.2006.08.326PubMedCentralCrossRefPubMed
12.
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. 10.1177/1545968306298414CrossRefPubMed
13.
Ertelt D, Small S, Solodkin A, Dettmers C, McNamara A, Binkofski F, Buccino G: Action observation has a positive impact on rehabilitation of motor deficits after stroke. Neuroimage 2007,36(Suppl 2):T164-173. 10.1016/j.neuroimage.2007.03.043CrossRefPubMed
14.
Karni A, Meyer G, Jezzard P, Adams MM, Turner R, Ungerleider LG: Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature 1995, 377: 155-158. 10.1038/377155a0CrossRefPubMed
15.
Kwakkel G, van Peppen R, Wagenaar RC, Wood Dauphinee S, Richards C, Ashburn A, Miller K, Lincoln N, Partridge C, Wellwood I, Langhorne P: Effects of augmented exercise therapy time after stroke: a meta-analysis. Stroke 2004, 35: 2529-2539. 10.1161/01.STR.0000143153.76460.7dCrossRefPubMed
16.
Cameirao MS, Bermudez i Badia S, Verschure PFMJ: Virtual Reality Based Upper Extremity Rehabilitation following Stroke: a Review. Journal of CyberTherapy & Rehabilitation 2008, 1: 63-74.
17.
Holden MK: Virtual environments for motor rehabilitation: review. Cyberpsychol Behav 2005, 8: 187-211. discussion 212-189 10.1089/cpb.2005.8.187CrossRefPubMed
18.
Lucca LF: Virtual reality and motor rehabilitation of the upper limb after stroke: a generation of progress? J Rehabil Med 2009, 41: 1003-1100. 10.2340/16501977-0405CrossRefPubMed
19.
Prabhakaran S, Zarahn E, Riley C, Speizer A, Chong JY, Lazar RM, Marshall RS, Krakauer JW: Inter-individual variability in the capacity for motor recovery after ischemic stroke. Neurorehabil Neural Repair 2008, 22: 64-71.CrossRefPubMed
20.
Cameirão MS, Bermúdez i Badia S, Zimmerli L, Duarte Oller E, Verschure PFMJ: The Rehabilitation Gaming System: a Virtual Reality Based System for the Evaluation and Rehabilitation of Motor Deficits. Virtual Rehabilitation 2007; Sep; Lido, Venice, Italy 2007, 29-33. full_textCrossRef
21.
Cameirao MS, Bermudez IBS, Duarte Oller E, Verschure PF: The rehabilitation gaming system: a review. Stud Health Technol Inform 2009, 145: 65-83.PubMed
22.
Gallese V, Fadiga L, Fogassi L, Rizzolatti G: Action recognition in the premotor cortex. Brain 1996,119(Pt 2):593-609. 10.1093/brain/119.2.593CrossRefPubMed
23.
Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ: Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study. Eur J Neurosci 2001, 13: 400-404.PubMed
24.
Rizzolatti G, Craighero L: The mirror-neuron system. Annu Rev Neurosci 2004, 27: 169-192. 10.1146/annurev.neuro.27.070203.144230CrossRefPubMed
25.
Iacoboni M, Dapretto M: The mirror neuron system and the consequences of its dysfunction. Nat Rev Neurosci 2006, 7: 942-951. 10.1038/nrn2024CrossRefPubMed
26.
Mukamel R, Ekstrom AD, Kaplan J, Iacoboni M, Fried I: Single-Neuron Responses in Humans during Execution and Observation of Actions. Curr Biol 2010, in press.
27.
Wyss R, Konig P, Verschure PF: A model of the ventral visual system based on temporal stability and local memory. PLoS Biol 2006, 4: e120. 10.1371/journal.pbio.0040120PubMedCentralCrossRefPubMed
28.
Verschure PF, Voegtlin T, Douglas RJ: Environmentally mediated synergy between perception and behaviour in mobile robots. Nature 2003, 425: 620-624. 10.1038/nature02024CrossRefPubMed
29.
Kilner JM, Friston KJ, Frith CD: The mirror-neuron system: a Bayesian perspective. Neuroreport 2007, 18: 619-623. 10.1097/WNR.0b013e3281139ed0CrossRefPubMed
30.
August K, Lewis JA, Chandar G, Merians A, Biswal B, Adamovich S: FMRI analysis of neural mechanisms underlying rehabilitation in virtual reality: activating secondary motor areas. Conf Proc IEEE Eng Med Biol Soc 2006, 1: 3692-3695. full_textCrossRefPubMed
31.
Maeda F, Kleiner-Fisman G, Pascual-Leone A: Motor facilitation while observing hand actions: specificity of the effect and role of observer's orientation. J Neurophysiol 2002, 87: 1329-1335.PubMed
32.
Strafella AP, Paus T: Modulation of cortical excitability during action observation: a transcranial magnetic stimulation study. Neuroreport 2000, 11: 2289-2292. 10.1097/00001756-200007140-00044CrossRefPubMed
33.
Yerkes RM, Dodson JD: The relation of strength of stimulus to rapidity of habit formation. Journal of Comparative Neurology 1908, 18: 459-482. 10.1002/cne.920180503CrossRef
34.
Calabrese EJ: Converging concepts: adaptive response, preconditioning, and the Yerkes-Dodson Law are manifestations of hormesis. Ageing Res Rev 2008, 7: 8-20. 10.1016/j.arr.2007.07.001CrossRefPubMed
35.
Csikszentmihalyi M: Flow: The Classic Work on How to Achieve Happiness. London: Rider & Co; 2002.
36.
Folstein MF, Folstein SE, McHugh PR: "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975, 12: 189-198. 10.1016/0022-3956(75)90026-6CrossRefPubMed
37.
Mathews Z, Bermúdez i Badia S, Verschure PFMJ: A Novel Brain-Based Approach for Multi-Modal Multi-Target Tracking in a Mixed Reality Space. INTUITION - International Conference and Workshop on Virtual Reality 2007; Sep; Athens, Greece 2007.
38.
Cohen J, Cohen P, Werst SG, Aiken LS: Applied multiple regression/correlation analysis for the behavioral sciences. Psychology Press; 2002.
39.
Krakauer JW: Motor learning: its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol 2006, 19: 84-90. 10.1097/01.wco.0000200544.29915.ccCrossRefPubMed
40.
Krakauer JW, Ghilardi MF, Ghez C: Independent learning of internal models for kinematic and dynamic control of reaching. Nat Neurosci 1999, 2: 1026-1031. 10.1038/14826CrossRefPubMed
41.
Todorov E, Shadmehr R, Bizzi E: Augmented Feedback Presented in a Virtual Environment Accelerates Learning of a Difficult Motor Task. J Mot Behav 1997, 29: 147-158. 10.1080/00222899709600829CrossRefPubMed
42.
Molina-Luna K, Hertler B, Buitrago MM, Luft AR: Motor learning transiently changes cortical somatotopy. Neuroimage 2008, 40: 1748-1754. 10.1016/j.neuroimage.2007.11.018CrossRefPubMed
43.
Nudo RJ: Adaptive plasticity in motor cortex: implications for rehabilitation after brain injury. J Rehabil Med 2003, 7-10. 10.1080/16501960310010070
44.
Holden MK, Dyar T: Virtual environment training: a new tool for neurorehabilitation. Neurol Rep 2002, 26: 62-71.CrossRef
45.
Piron L, Tonin P, Piccione F, Laia V, Trivello E, Dam M: Virtual Environment Training Therapy for Arm Motor Rehabilitation. Presence 2005, 14: 732-740. 10.1162/105474605775196580CrossRef
46.
Broeren J, Rydmark M, Bjorkdahl A, Sunnerhagen KS: Assessment and training in a 3-dimensional virtual environment with haptics: a report on 5 cases of motor rehabilitation in the chronic stage after stroke. Neurorehabil Neural Repair 2007, 21: 180-189. 10.1177/1545968306290774CrossRefPubMed
47.
Merians AS, Tunik E, Fluet GG, Qiu Q, Adamovich SV: Innovative approaches to the rehabilitation of upper extremity hemiparesis using virtual environments. Eur J Phys Rehabil Med 2009, 45: 123-133.PubMed
48.
Rand D, Katz N, Weiss PL: Intervention using the VMall for improving motor and functional ability of the upper extremity in post stroke participants. Eur J Phys Rehabil Med 2009, 45: 113-121.PubMed
49.
Gaggioli A, Meneghini A, Morganti F, Alcaniz M, Riva G: A strategy for computer-assisted mental practice in stroke rehabilitation. Neurorehabil Neural Repair 2006, 20: 503-507. 10.1177/1545968306290224CrossRefPubMed
50.
Yarosh CA, Hoffman DS, Strick PL: Deficits in movements of the wrist ipsilateral to a stroke in hemiparetic subjects. J Neurophysiol 2004, 92: 3276-3285. 10.1152/jn.00549.2004CrossRefPubMed
51.
Horstman AM, Gerrits KH, Beltman MJ, Koppe PA, Janssen TW, de Haan A: Intrinsic properties of the knee extensor muscles after subacute stroke. Arch Phys Med Rehabil 2010, 91: 123-128. 10.1016/j.apmr.2009.09.008CrossRefPubMed
52.
Levin MF, Knaut LA, Magdalon EC, Subramanian S: Virtual reality environments to enhance upper limb functional recovery in patients with hemiparesis. Stud Health Technol Inform 2009, 145: 94-108.PubMed
53.
Cameirão MS, Bermúdez i Badia S, Duarte Oller E, Verschure PFMJ: Using a Multi-Task Adaptive VR System for Upper Limb Rehabilitation in the Acute Phase of Stroke. Virtual Rehabilitation 2008; Aug; Vancouver, Canada 2008.
54.
Granger CV, Albrecht GL, Hamilton BB: Outcome of comprehensive medical rehabilitation: measurement by PULSES profile and the Barthel Index. Arch Phys Med Rehabil 1979, 60: 145-154.PubMed
55.
Brunnstrom S: Recovery stages and evaluation procedures. In Movement Therapy in Hemiplegia: A Neurophysiological Approach. New York: Harper & Row; 1970:34-55.
Metadata
Title
Neurorehabilitation using the virtual reality based Rehabilitation Gaming System: methodology, design, psychometrics, usability and validation
Authors
Mónica S Cameirão
Sergi Bermúdez i Badia
Esther Duarte Oller
Paul FMJ Verschure
Publication date
01-12-2010
Publisher
BioMed Central
Published in
Journal of NeuroEngineering and Rehabilitation / Issue 1/2010
Electronic ISSN: 1743-0003
DOI
https://doi.org/10.1186/1743-0003-7-48

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