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The Role of Serious Games in Robot Exoskeleton-Assisted Rehabilitation of Stroke Patients

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Serious Games Analytics

Part of the book series: Advances in Game-Based Learning ((AGBL))

Abstract

This chapter describes how serious games can be used to improve the rehabilitation of stroke patients. Determining ideal training conditions for rehabilitation is difficult, as no objective measures exist and the psychological state of patients during therapy is often neglected. What is missing is a way to vary the difficulty of the tasks during a therapy session in response to the patient needs, in order to adapt the training specifically to the individual. In this chapter, we describe such a method. A serious game is used to present challenges to the patient, including motor and cognitive tasks. The psychological state of the patient is inferred from measures computed from heart rate variability (HRV) as well as breathing frequency, skin conductance response, and skin temperature. Once the psychological state of the patient can be determined from these measures, it is possible to vary the tasks in real time by adjusting parameters of the game. The serious game aspect of the training allows the virtual environment to become adaptive in real time, leading to improved matching of the activity to the needs of the patient. This is likely to lead to improved training outcomes and has the potential to lead to faster and more complete recovery, as it enables training that is challenging yet does not overstress the patient.

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References

  • Adamovich, S. V., Fluet, G. G., Tunik, E., & Merians, A. S. (2009). Sensorimotor training in virtual reality: A review. NeuroRehabilitation, 25(1), 29–44.

    Google Scholar 

  • Aisen, M. L., Krebs, H. I., Hogan, N., McDowell, F., & Volpe, B. T. (1997). The effect of robot-assisted therapy and rehabilitative training on motor recovery following stroke. Archives of Neurology, 54, 443–446.

    Article  Google Scholar 

  • Amano, M., Oida, E., & Moritani, T. (2005). Age-associated alteration of sympatho-vagal balance in a female population assessed through the tone-entropy analysis. European Journal of Applied Physiology, 94, 602–610.

    Article  Google Scholar 

  • Andreassi, J. L. (2007). Psychophysiology: Human behavior and physiological response 5th ed. Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Arazpour, M., Mehrpour, S. R., Bani, M. A., Hutchins, S. W., Bahramizadeh, M., & Rahgozar, M. (2014). Comparison of gait between healthy participants and persons with spinal cord injury when using a powered gait orthosis—A pilot study. Spinal Cord, 52(1), 44–48.

    Article  Google Scholar 

  • Banz, R., Bolliger, M., Colombo, G., Dietz, V., & Lunenburger, L. (2008). Computerized visual feedback: An adjunct to robotic-assisted gait training. Physical Therapy, 88, 1135–1145.

    Article  Google Scholar 

  • Berntson, G. G., Bigger, J. T., Jr., Eckberg, D. L., Grossman, P., Kaufmann, P. G., Malik, M., et al. (1997). Heart rate variability: Origins, methods, and interpretive caveats. Psychophysiology, 34(6), 623–648.

    Article  Google Scholar 

  • Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49–59.

    Article  Google Scholar 

  • Brennan, M., Palaniswami, M., & Kamen, P. (2001). New insights into the relationship between Poincare plot geometry and linear measures of heart rate variability. In Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Vol. 1, pp. 526–529).

    Google Scholar 

  • Brown, R., & Macefield, V. G. (2014). Skin sympathetic nerve activity in humans during exposure to emotionally-charged images: Sex differences. Frontiers in Physiology, 5, 111.

    Article  Google Scholar 

  • Burke, J. W., McNeill, M. D. J., Charles, D. K., Morrow, P. J., Crosbie, J. H., & McDonough, S. M. (2009). Optimising engagement for stroke rehabilitation using serious games. The Visual Computer, 25(12), 1085–1099.

    Google Scholar 

  • Carroll, D., Turner, J. R., & Prasad, R. (1986). The effects of level of difficulty of mental arithmetic challenge on heart rate and oxygen-consumption. International Journal of Psychophysiology, 4, 167–173.

    Article  Google Scholar 

  • Christov, I. (2004). Real time electrocardiogram QRS detection using combined adaptive threshold. Biomedical Engineering Online, 3, 8.

    Article  Google Scholar 

  • Colombo, G., Joerg, M., Schreier, R., & Dietz, V. (2000). Treadmill training of paraplegic patients using a robotic orthosis. Journal of Rehabilitation Research and Development, 37, 693–700.

    Google Scholar 

  • Dawson, M. E., Schell, A. M., & Filion, D. L. (2008). Handbook of psychophysiology (3rd ed.). New York: Cambridge University Press.

    Google Scholar 

  • de la Cruz Torres, B., Lopez, C. L., & Orellana, J. N. (2008). Analysis of heart rate variability at rest and during aerobic exercise: A study in healthy people and cardiac patients. British Journal of Sports Medicine, 42(9), 715–720.

    Article  Google Scholar 

  • Delaney, J. P. A., & Brodie, D. A. (2000). Effects of short-term psychological stress on the time and frequency domains of heart-rate variability. Perceptual and Motor Skills, 91, 515–524.

    Article  Google Scholar 

  • Dietterich, T. G., & Bakiri, G. (1995). Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research, 2, 263–286.

    Google Scholar 

  • Dietz, V., & Duysens, J. (2000). Significance of load receptor input during locomotion: A review. Gait & Posture, 11(2), 102–110.

    Article  Google Scholar 

  • Doberenz, S., Roth, W. T., Wollburg, E., Maslowski, N. I., & Kim, S. (2011). Methodological considerations in ambulatory skin conductance monitoring. International Journal of Psychophysiology, 80(2), 87–95.

    Article  Google Scholar 

  • Duda, R. O., Hart, P. E., & Stork, D. G. (2012). Pattern classification and scene analysis. London: Wiley.

    Google Scholar 

  • Guadagnoli, M. A., & Lee, T. D. (2004). Challenge point: A framework for conceptualizing the effects of various practice conditions in motor learning. Journal of Motor Behavior, 36, 212–224.

    Article  Google Scholar 

  • Gunther, A., Witte, O. W., & Hoyer, D. (2010). Autonomic dysfunction and risk stratification assessed from heart rate pattern. Open Neurology Journal, 4, 39–49.

    Google Scholar 

  • Hamilton, P. S., & Tompkins, W. J. (1986). Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Transactions on Biomedical Engineering, BME-33, 1157–1165.

    Article  Google Scholar 

  • Harro, C. C., Shoemaker, M. J., Frey, O., Gamble, A. C., Harring, K. B., Karl, K. L., et al. (2014). The effects of speed-dependent treadmill training and rhythmic auditory-cued overground walking on balance function, fall incidence, and quality of life in individuals with idiopathic Parkinson's disease: A randomized controlled trial. NeuroRehabilitation, 34(3), 541–556.

    Google Scholar 

  • Hirshfield, L. M., Bobko, P., Barelka, A., Hirshfield, S. H., Farrington, M. T, Gulbronson, S., et al. (2014). Using noninvasive brain measurement to explore the psychological effects of computer malfunctions on users during human–computer interactions. Advances in Human-Computer Interaction. doi: 10.1155/2014/101038.

  • Holden, M. K. (2005). Virtual environments for motor rehabilitation: Review. CyberPsychology & Behavior, 8, 187–211.

    Article  Google Scholar 

  • Houtsma, J. A., & Van Houten, F. J. (2006). Virtual reality and a haptic master-slave set-up in post-stroke upper-limb rehabilitation. Proceedings of the Institute of Mechanical Engineers H, 220, 715–718.

    Article  Google Scholar 

  • Jelinek, H. F., August, K. G., Imam, Md. H., Khandoker, A. H., Khalaf, K., Koenig, A., et al. (2014). Influence of stroke location on heart rate variability in robot-assistive neurorehabilitation. In Proceedings of the 2nd Middle East Conference on Biomedical Engineering (pp. 253–256). ISBN: 978-1-4799-4799-7/14.

    Google Scholar 

  • Jelinek, H. F., August, K., Khandoker, A., Issam, H. M., Koenig, A., & Riener, R. (2011). Heart rate asymmetry and emotional response to robot-assist task challenges in post-stroke patients. In Proceedings of the Computers in Cardiology Conference (Vol. 38, pp. 521–524).

    Google Scholar 

  • Karmakar, C. K., Khandoker, A. H., Gubbi, J., & Palaniswami, M. (2011). Defining asymmetry in heart rate variability signals using a Poincaré plot. Physiological Measurement, 30, 1227–1240.

    Article  Google Scholar 

  • Karmakar, C. K., Khandoker, A. H., Jelinek, H. F., & Palaniswami, M. (2013). Risk stratification of cardiac autonomic neuropathy based on multi-scale tone-entropy. Medical and Biological Engineering and Computing, 51(5), 537–546. doi:10.1007/s11517-012-1022-5.

    Article  Google Scholar 

  • Karmakar, C. K., Khandoker, A. H., Voss, A., & Palaniswami, M. (2011). Sensitivity of temporal heart rate variability in Poincaré plot to changes in parasympathetic nervous system activity. Biomedical Engineering Online, 10, 17.

    Article  Google Scholar 

  • Khandoker, A. H., Jelinek, H. F., Moritani, T., & Palaniswami, M. (2010). Association of cardiac autonomic neuropathy with alteration of sympatho-vagal balance through heart rate variability analysis. Medical Engineering and Physics, 32, 61–67.

    Article  Google Scholar 

  • Koenig, A., Omlin, X., Zimmerli, L., Sapa, M., Krewer, C., Bolliger, M., et al. (2011). Psychological state estimation from physiological recordings during robot-assisted gait rehabilitation. Journal of Rehabilitation Research and Development, 48(4), 367–385.

    Article  Google Scholar 

  • Lakusic, N., Mahovic, D., Babic, T., & Sporis, D. (2003). Changes in autonomic control of heart rate after ischemic cerebral stroke. Acta Medica Croatica, 57(4), 269–273.

    Google Scholar 

  • Lotze, M., Braun, C., Birbaumer, N., Anders, S., & Cohen, L. G. (2003). Motor learning elicited by voluntary drive. Brain, 126, 866–872.

    Article  Google Scholar 

  • Mackersie, C. L., & Cones, H. (2011). Subjective and psychophysiological indexes of listening effort in a competing-talker task. Journal of the American Academy of Audiology, 22(2), 113–122.

    Article  Google Scholar 

  • Maclean, N., Pound, P., Wolfe, C., & Rudd, A. (2002). The concept of patient motivation. Stroke, 33(2), 444–448.

    Article  Google Scholar 

  • Malik, M., & Camm, A. J. (Eds.). (1995). Heart rate variability. Armonk, NY: Futura.

    Google Scholar 

  • Mancuso, D. L, Knight, K. L. (1992). Effects of prior physical activity on skin surface temperature response of the ankle during and after a 30-minute ice pack application. Journal of Athletic Training, 27(3), 242, 244, 246, 248-249.

    Google Scholar 

  • McAuley, E., Duncan, T., & Tammen, V. V. (1989). Psychometric properties of the intrinsic motivation inventory in a competitive sports setting—A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60, 48–58.

    Article  Google Scholar 

  • Meyer, T., Peters, J., Zander, T., Scholkopf, B., & Grosse-Wentrup, M. (2014). Predicting motor learning performance from electroencephalographic data. Journal of NeuroEngineering and Rehabilitation, 11(1), 24.

    Article  Google Scholar 

  • Moré, J. J. (1977). The Levenberg-Marquardt algorithm: implementation and theory. In G. A. Watson (Ed.), Numerical analysis (Lecture notes in mathematics, Vol. 630, pp. 105–116). New York: Springer.

    Chapter  Google Scholar 

  • Morris, J. D. (1995). Observations: SAM—The Self Assessment Mannequin: An efficient cross-cultural measurement of emotional response. Journal of Advertising Research, 35(6), 63–70.

    Google Scholar 

  • Nef, T., Guidali, M., & Riener, R. (2009). ARMin III—Arm therapy exoskeleton with an ergonomic shoulder actuation. Applied Bionics and Biomechanics, 6, 16.

    Article  Google Scholar 

  • Nef, T., Mihelj, M., & Riener, R. (2007). ARMin: A robot for patient-cooperative arm therapy. Medical and Biological Engineering and Computing, 45, 887–900.

    Article  Google Scholar 

  • Nguyen, D., & Widrow, B. (1990). Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights. In Proceedings of the IJCNN International Joint Conference on Neural Networks (Vol. 3, pp. 21–26).

    Google Scholar 

  • Ohsuga, M., Shimono, F., & Genno, H. (2001). Assessment of phasic work stress using autonomic indices. International Journal of Psychophysiology, 40, 211–220.

    Article  Google Scholar 

  • Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine Series 6, 2(11), 559–572.

    Article  Google Scholar 

  • Porta, A., Casali, K. R., Casali, A. G., Gnecchi-Ruscone, T., Tovaldini, E., Montano, N., et al. (2008). Temporal asymmetries of short-term heart period variability are linked to autonomic regulation. American Journal of Physiology—Regulatory, Integrative and Comparative Physiology, 295, R550557.

    Article  Google Scholar 

  • Rego, P., Moreira, P. M., & Reis, L. P. (2011). Serious games for rehabilitation: A survey and a classification towards a taxonomy. In: 2010 5th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1–6).

    Google Scholar 

  • Rosenblueth, A., & Simeone, A. (1984). The interrelations of vagal and accelerator effects on the cardiac rate. American Journal of Physiology, 110, 42–55.

    Google Scholar 

  • Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161–1178.

    Article  Google Scholar 

  • Saposnik, G., Teasell, R., Mamdani, M., Hall, J., McIlroy, W., Cheung, D., et al. (2010). Effectiveness of virtual reality using Wii gaming technology in stroke rehabilitation: A pilot randomized clinical trial and proof of principle. Stroke, 41(7), 1477–1484.

    Article  Google Scholar 

  • Stauffer, Y., Allemand, Y., Bouri, M., Fournier, J., Clavel, R., Metrailler, P., et al. (2009). The WalkTrainer—A new generation of walking reeducation device combining orthoses and muscle stimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17, 38–45.

    Article  Google Scholar 

  • Suess, W. M., Alexander, A. B., Smith, D. D., Sweeney, H. W., & Marion, R. J. (1980). The effects of psychological stress on respiration—A preliminary-study of anxiety and hyperventilation. Psychophysiology, 17, 535–540.

    Article  Google Scholar 

  • Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation and health. Annals of Behavioral Medicine, 37, 141–153.

    Google Scholar 

  • Veneman, J. F., Kruidhof, R., Hekman, E. E., Ekkelenkamp, R., Van Asseldonk, E. H., & van der Kooij, H. (2007). Design and evaluation of the LOPES exoskeleton robot for interactive gait rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 15, 379–386.

    Article  Google Scholar 

  • Vichitvanichphong, S., Talaei-Khoei, A., Kerr, D., & Ghapanchi, A. H. (2014). Adoption of assistive technologies for aged care: A realist review of recent studies. In: 2014 47th Hawaii International Conference on System Sciences (HICSS) (pp. 2706–2715). doi:10.1109/HICSS.2014.341.

  • Winchester, P., & Querry, R. (2006). Robotic orthoses for body weight-supported treadmill training. Physical Medicine and Rehabilitation Clinics of North America, 17, 159–172.

    Article  Google Scholar 

  • Wiemeyer, J., & Kliem, A. (2012). Serious games in prevention and rehabilitation—A new panacea for elderly people? European Review of Aging and Physical Activity, 9(1), 41–50. doi:10.1007/s11556-011-0093-x.

  • Zimmerli, L., Duschau-Wicke, A., Mayr, A., Riener, R., & Lunenburger, L. (2009). Virtual reality and gait rehabilitation: Augmented feedback for the Lokomat. In Proceedings of the IEEE Virtual Rehabilitation International Conference (pp. 150–153).

    Google Scholar 

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Authors and Affiliations

  1. University of Newcastle, Australia, University Drive, ICT3.12, Callaghan, NSW, 2308, Australia

    David J. Cornforth

  2. ETH Zurich, Tannenstrasse 1, E4, Zurich, 8092, Switzerland

    Alexander Koenig, Robert Riener & Katherine August

  3. The University of Melbourne, Electrical Engineering Building, Level 4, Parkville, VIC, 3010, Australia

    Ahsan H. Khandoker & Chandan Karmakar

  4. The University of Melbourne, Level 5, 161 Barry Street, Parkville, VIC, 3010, Australia

    Marimuthu Palaniswami

  5. Charles Sturt University, Building 673, Room 419, Albury, NSW, Australia

    Herbert F. Jelinek

Authors
  1. David J. Cornforth
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  2. Alexander Koenig
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  3. Robert Riener
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  4. Katherine August
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  5. Ahsan H. Khandoker
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  6. Chandan Karmakar
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  7. Marimuthu Palaniswami
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  8. Herbert F. Jelinek
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Correspondence to David J. Cornforth .

Editor information

Editors and Affiliations

  1. Virtual Environment Lab (V-Lab), Southern Illinois University, Carbondale, Illinois, USA

    Christian Sebastian Loh

  2. Department of Counseling, Quantitative Methods, and Special Education, Southern Illinois University, Carbondale, Illinois, USA

    Yanyan Sheng

  3. University of Mannheim, Mannheim, Germany

    Dirk Ifenthaler

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Cornforth, D.J. et al. (2015). The Role of Serious Games in Robot Exoskeleton-Assisted Rehabilitation of Stroke Patients. In: Loh, C., Sheng, Y., Ifenthaler, D. (eds) Serious Games Analytics. Advances in Game-Based Learning. Springer, Cham. https://doi.org/10.1007/978-3-319-05834-4_10

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