Advertisement

Increasing Patient Engagement During Virtual Reality-Based Motor Rehabilitation

Published:March 11, 2013DOI:https://doi.org/10.1016/j.apmr.2013.01.029

      Abstract

      Objective

      To investigate the influence of different design characteristics of virtual reality exercises on engagement during lower extremity motor rehabilitation.

      Design

      Correlational study.

      Setting

      Spinal cord injury (SCI) rehabilitation center.

      Participants

      Subjects with SCI (n=12) and control subjects (n=10).

      Interventions

      Not applicable.

      Main Outcome Measures

      Heart rate and electromyographic activity from both legs at the tibialis anterior, the gastrocnemius medialis, the rectus femoris, and the biceps femoris were recorded.

      Results

      Interactivity (ie, functionally meaningful reactions to motor performance) was crucial for the engagement of subjects. No significant differences in engagement were found between exercises that differed in feedback frequency, explicit task goals, or aspects of competition.

      Conclusions

      Functional feedback is highly important for the active participation of patients during robotic-assisted rehabilitation. Further investigations on the design characteristics of virtual reality exercises are of great importance. Exercises should thoroughly be analyzed regarding their effectiveness, while user preferences and expectations should be considered when designing virtual reality exercises for everyday clinical motor rehabilitation.

      Keywords

      List of abbreviations:

      BDI II (Beck Depression Inventory II), EMG (electromyogram), LEMS (lower extremity motor score), RMS (root mean square), SCI (spinal cord injury), SCIM III (Spinal Cord Independence Measure III), VR (virtual reality), WISCI II (Walking Index for Spinal Cord Injury II)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Archives of Physical Medicine and Rehabilitation
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Israel J.F.
        • Campbell D.D.
        • Kahn J.H.
        • Hornby T.G.
        Metabolic costs and muscle activity patterns during robotic- and therapist-assisted treadmill walking in individuals with incomplete spinal cord injury.
        Phys Ther. 2006; 86: 1466-1478
        • Wolbrecht E.T.
        • Chan V.
        • Reinkensmeyer D.J.
        • Bobrow J.E.
        Optimizing compliant, model-based robotic assistance to promote neurorehabilitation.
        IEEE Trans Neural Syst Rehabil Eng. 2008; 16: 286-297
        • Secoli R.
        • Milot M.H.
        • Rosati G.
        • Reinkensmeyer D.J.
        Effect of visual distraction and auditory feedback on patient effort during robot-assisted movement training after stroke.
        J Neuroeng Rehabil. 2011; 8: 21
        • Holden M.K.
        Virtual environments for motor rehabilitation: review.
        Cyberpsychol Behav. 2005; 8: 187-211
        • Keshner E.A.
        Virtual reality and physical rehabilitation: a new toy or a new research and rehabilitation tool?.
        J Neuroeng Rehabil. 2004; 1: 8
      1. Flores E, Tobon G, Cavallaro E. Improving patient motivation in game development for motor deficit rehabilitation. In: Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology. December 3-5, 2008, Yokohama, Japan. New York: ACM; 2008;381-4.

      2. Malone TW. Heuristics for designing enjoyable user interfaces: lessons from computer games. In: Proceedings of the 1982 Conference on Human Factors in Computing. March 15-17, 1982, Gaithersburg, MD. New York: ACM; 1982;63-68.

        • Wood R.T.
        • Griffiths M.D.
        • Chappell D.
        • Davies M.N.
        The structural characteristics of video games: a psycho-structural analysis.
        Cyberpsychol Behav. 2004; 7: 1-10
        • King D.
        • Delfabbro P.
        • Griffiths M.D.
        Video game structural characteristics: a new psychological taxonomy.
        Int J Ment Health Addict. 2010; 8: 90-106
        • Bradley M.M.
        • Lang P.J.
        Affective reactions to acoustic stimuli.
        Psychophysiology. 2000; 37: 204-215
        • Weber R.
        • Tamborini R.
        • Westcott Baker A.
        • Kantor B.
        Theorizing flow and media enjoyment as cognitive synchronization of attentional and reward networks.
        Commun Theory. 2009; 19: 397-422
        • Csikszentmihalyi M.
        Flow: the psychology of optimal experience: steps toward enhancing the quality of life.
        Harper Collins, New York1990 (4)
      3. Csikszentmihalyi M. Beyond boredom and anxiety. San Francisco: Jossey-Bass Publishers; 1975.

      4. Csikszentmihalyi M. Optimal experience: psychological studies of flow in consciousness. Cambridge: Cambridge University Pr; 1992.

        • Sweetser P.
        • Wyeth P.
        GameFlow: a model for evaluating player enjoyment in games.
        Computers in Entertainment. 2005; 3: 1-24
      5. Kizony R, Katz N, Weiss PL. Virtual reality based intervention in rehabilitation: relationship between motor and cognitive abilities and performance within virtual environments for patients with stroke. In: Sharkey PM, Sik Lányi C, Standen PJ, editors. Proceedings of the 5th International Conference on Disability, Virtual Reality and Associated Technologies. September 20-22, 2004, ICDVRAT, Oxford, UK. Reading: The University of Reading; 2004;19-26.

        • Zimmerli L.
        • Krewer C.
        • Gassert R.
        • Muller F.
        • Riener R.
        • Lunenburger L.
        Validation of a mechanism to balance exercise difficulty in robot-assisted upper-extremity rehabilitation after stroke.
        J Neuroeng Rehabil. 2012; 9: 6
        • Lequerica A.H.
        • Kortte K.
        Therapeutic engagement: a proposed model of engagement in medical rehabilitation.
        Am J Phys Med Rehabil. 2010; 89: 415-422
      6. Dobkin BH. The clinical science of neurologic rehabilitation. 2nd ed. US: Oxford University Pr; 2003.

        • Sheehan D.P.
        • Katz L.
        The practical and theoretical implications of flow theory and intrinsic motivation in designing and implementing exergaming in the school environment. Loading.
        J Can Game Stud Assoc. 2012; 6: 53-68
        • Krakauer J.W.
        Motor learning: its relevance to stroke recovery and neurorehabilitation.
        Curr Opin Neurol. 2006; 19: 84-90
        • Ditunno J.F.J.
        • Ditunno P.L.
        • Graziani V.
        • et al.
        Walking Index for Spinal Cord Injury (WISCI): an international multicenter validity and reliability study.
        Spinal Cord. 2000; 38: 234-243
        • Itzkovich M.
        • Gelernter I.
        • Biering-Sorensen F.
        • et al.
        The Spinal Cord Independence Measure (SCIM) version III: reliability and validity in a multi-center international study.
        Disabil Rehabil. 2007; 29: 1926-1933
        • Burns A.S.
        • Delparte J.J.
        • Patrick M.
        • Marino R.J.
        • Ditunno J.F.
        The reproducibility and convergent validity of the Walking Index for Spinal Cord Injury (WISCI) in chronic spinal cord injury.
        Neurorehabil Neural Repair. 2011; 25: 149-157
        • Furlan J.C.
        • Fehlings M.G.
        • Tator C.H.
        • Davis A.M.
        Motor and sensory assessment of patients in clinical trials for pharmacological therapy of acute spinal cord injury: psychometric properties of the ASIA standards.
        J Neurotrauma. 2008; 25: 1273-1301
        • Marino R.J.
        • Graves D.E.
        Metric properties of the ASIA motor score: subscales improve correlation with functional activities.
        Arch Phys Med Rehabil. 2004; 85: 1804-1810
        • Maynard F.M.J.
        • Bracken M.B.
        • Creasey G.
        • et al.
        International Standards for Neurological and Functional Classification of Spinal Cord Injury. American Spinal Injury Association.
        Spinal Cord. 1997; 35: 266-274
        • Marino R.J.
        • Barros T.
        • Biering-Sorensen F.
        • et al.
        International Standards for Neurological Classification of Spinal Cord Injury.
        J Spinal Cord Med. 2003; 26: S50-S56
        • Krefetz D.G.
        • Steer R.A.
        • Gulab N.A.
        • Beck A.T.
        Convergent validity of the Beck Depression Inventory-II with the Reynolds Adolescent Depression Scale in psychiatric inpatients.
        J Pers Assess. 2002; 78: 451-460
        • Arnau R.C.
        • Meagher M.W.
        • Norris M.P.
        • Bramson R.
        Psychometric evaluation of the Beck Depression Inventory-II with primary care medical patients.
        Health Psychol. 2001; 20: 112-119
        • Colombo G.
        • Joerg M.
        • Schreier R.
        • Dietz V.
        Treadmill training of paraplegic patients using a robotic orthosis.
        J Rehabil Res Dev. 2000; 37: 693-700
        • Colombo G.
        • Wirz M.
        • Dietz V.
        Driven gait orthosis for improvement of locomotor training in paraplegic patients.
        Spinal Cord. 2001; 39: 252-255
        • Banz R.
        • Bolliger M.
        • Colombo G.
        • Dietz V.
        • Lünenburger L.
        Computerized visual feedback: an adjunct to robotic-assisted gait training.
        Phys Ther. 2008; 88: 1135-1145
        • De Luca C.J.
        The use of surface electromyography in biomechanics.
        J Appl Biomech. 1997; 13: 135-163
        • Disselhorst-Klug C.
        • Schmitz-Rode T.
        • Rau G.
        Surface electromyography and muscle force: limits in sEMG-force relationship and new approaches for applications.
        Clin Biomech (Bristol, Avon). 2009; 24: 225-235
        • Holm S.
        A simple sequentially rejective multiple test procedure.
        Scand J Stat. 1979; 6: 65-70
        • Lynskey J.V.
        • Belanger A.
        • Jung R.
        Activity-dependent plasticity in spinal cord injury.
        J Rehabil Res Dev. 2008; 45: 229-240
        • Bravo G.
        • Guizar-Sahagun G.
        • Ibarra A.
        • Centurion D.
        • Villalon C.M.
        Cardiovascular alterations after spinal cord injury: an overview.
        Curr Med Chem Cardiovasc Hematol Agents. 2004; 2: 133-148
        • Hidler J.M.
        • Wall A.E.
        Alterations in muscle activation patterns during robotic-assisted walking.
        Clin Biomech (Bristol, Avon). 2005; 20: 184-193
        • Brütsch K.
        • Schuler T.
        • König A.
        • et al.
        Influence of virtual reality soccer game on walking performance in robotic assisted gait training for children.
        J Neuroeng Rehabil. 2010; 7: 15
        • Schuler T.
        • Brütsch K.
        • Muller R.
        • van Hedel H.J.
        • Meyer-Heim A.
        Virtual realities as motivational tools for robotic assisted gait training in children: a surface electromyography study.
        NeuroRehabilitation. 2011; 28: 401-411
        • Borggraefe I.
        • Klaiber M.
        • Schuler T.
        • et al.
        Safety of robotic-assisted treadmill therapy in children and adolescents with gait impairment: a bi-centre survey.
        Dev Neurorehabil. 2010; 13: 114-119
        • Wender R.
        • Hoffman H.G.
        • Hunner H.H.
        • Seibel E.J.
        • Patterson D.R.
        • Sharar S.R.
        Interactivity influences the magnitude of virtual reality analgesia.
        J Cyber Ther Rehabil. 2009; 2: 27-33
        • Frenz H.
        • Lappe M.
        Absolute travel distance from optic flow.
        Vision Res. 2005; 45: 1679-1692
        • Banton T.
        • Stefanucci J.
        • Durgin F.
        • Fass A.
        • Proffitt D.
        The perception of walking speed in a virtual environment.
        Presence (Camb). 2005; 14: 394-406
        • Ryan R.M.
        • Deci E.L.
        Intrinsic and extrinsic motivations: classic definitions and new directions.
        Contemp Educ Psychol. 2000; 25: 54-67
        • Bandura A.
        Social cognitive theory of self-regulation.
        Organ Behav Hum Decis Process. 1991; 50: 248-287
        • Wressle E.
        • Eeg-Olofsson A.M.
        • Marcusson J.
        • Henriksson C.
        Improved client participation in the rehabilitation process using a client-centred goal formulation structure.
        J Rehabil Med. 2002; 34: 5-11
      7. König A, Brütsch K, Zimmerli L, et al. Virtual environments increase participation of children with cerebral palsy in robot-aided treadmill training. Virtual Rehabil, August 25-27, 2008. Vancouver: IEEE; 2008;121-6.

        • Westwood D.
        • Griffiths M.D.
        The role of structural characteristics in video-game play motivation: a Q-methodology study.
        Cyberpsychol Behav Soc Netw. 2010; 13: 581-585
        • Sherry J.L.
        Flow and media enjoyment.
        Commun Theory. 2004; 14: 328-347
      8. Lazzaro N. Why we play games: four keys to more emotion without story. In: Proceedings of the Game Developers Conference, San Francisco, CA, March 8, 2004.

        • Timmermans A.A.
        • Seelen H.A.
        • Willmann R.D.
        • Kingma H.
        Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design.
        J Neuroeng Rehabil. 2009; 6: 1