Abstract
The virtual reality serious game in the field of physical rehabilitation are mentioned as complementary tools to assure highly motivated training for patients that are following a physical rehabilitation plan. Different virtual reality (VR) serious game framework is reported and different interface that provide information dynamic and kinematic parameters associated with the user body motion during training are reported in literature. Physical training affect not only the patient motor condition but is also reflected on the level of cardiac and respiratory activity. Taking into account the necessity to monitor the health status of patient during the training, reflected on the level of autonomous nervous system, the paper provides information about relevant works presented in the literature that sought to explore the effects of virtual reality exergaming on autonomic nervous responses based on wearable sensor data. The contributions of serious exergames on physical performance, and on rehabilitation processes has also been addressed. Particular contributions focus on heart rate variability (HRV) changes in younger adults while experiencing VR serious gaming of different time durations and exercise intensity. Moreover, the application of artificial intelligence algorithms to classify the VR serious game intensity levels is also presented.
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Munoz Cardona, J.E., Cameirao, M.S., Paulino, T., Bermudez i Badia, S., Rubio, E.: Modulation of physiological responses and activity levels during exergame experiences. In: 2016 8th International Conference on Games and Virtual Worlds for Serious Applications (VS-GAMES), pp. 1–8, Barcelona, Spain, September 2016. https://doi.org/10.1109/VS-GAMES.2016.7590353
Benzing, V., Heinks, T., Eggenberger, N., Schmidt, M.: Acute cognitively engaging exergame-based physical activity enhances executive functions in adolescents. PLoS ONE11(12), e0167501 (2016). https://doi.org/10.1371/journal.pone.0167501
Polechoński, J., Dębska, M., Dębski, P.G.: Exergaming can be a health-related aerobic physical activity. Biomed. Res. Int. 2019, 1–7 (2019). https://doi.org/10.1155/2019/1890527
Wittmann, F., et al.: Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system. J. NeuroEng. Rehabil. 13(1), 75 (2016). https://doi.org/10.1186/s12984-016-0182-1
Standen, P., et al.: A low cost virtual reality system for home based rehabilitation of the arm following stroke: a randomised controlled feasibility trial. Clin. Rehabil. 31(3), 340–350 (2017). https://doi.org/10.1177/0269215516640320
Charoensook, T., Barlow, M., Lakshika, E.: Heart rate and breathing variability for virtual reality game Play. In: 2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH), pp. 1–7, Kyoto, Japan, August 2019. https://doi.org/10.1109/SeGAH.2019.8882434
Kafri, M., Myslinski, M.J., Gade, V.K., Deutsch, J.E.: Energy expenditure and exercise intensity of interactive video gaming in individuals poststroke. Neurorehabil. Neural Repair 28(1), 56–65 (2014). https://doi.org/10.1177/1545968313497100
Cho, G.H., Hwangbo, G., Shin, H.S.: The effects of virtual reality-based balance training on balance of the elderly. J. Phys. Ther. Sci. 26(4), 615–617 (2014). https://doi.org/10.1589/jpts.26.615
Donath, L., Rössler, R., Faude, O.: Effects of virtual reality training (exergaming) compared to alternative exercise training and passive control on standing balance and functional mobility in healthy community-dwelling seniors: a meta-analytical review. Sports Med. 46(9), 1293–1309 (2016). https://doi.org/10.1007/s40279-016-0485-1
de Amorim, J.S.C., Leite, R.C., Brizola, R., Yonamine, C.Y.: Virtual reality therapy for rehabilitation of balance in the elderly: a systematic review and META-analysis. Adv. Rheumatol. 58(1), 18 (2018). https://doi.org/10.1186/s42358-018-0013-0
Lei, C., et al.: Effects of virtual reality rehabilitation training on gait and balance in patients with Parkinson’s disease: a systematic review. PLoS ONE14(11), e0224819 (2019). https://doi.org/10.1371/journal.pone.0224819
Fang, Q., et al.: Effects of exergaming on balance of healthy older adults: a systematic review and meta-analysis of randomized controlled trials. Games Health J. 9(1), 11–23 (2020). https://doi.org/10.1089/g4h.2019.0016
Wiley, E., Khattab, S., Tang, A.: Examining the effect of virtual reality therapy on cognition post-stroke: a systematic review and meta-analysis. Disabil. Rehabil.: Assistive Technol., 1–11, (2020). https://doi.org/10.1080/17483107.2020.1755376
Brachman, A., et al.: The effects of exergaming training on balance in healthy elderly women—a pilot study. IJERPH 18(4), 1412 (2021). https://doi.org/10.3390/ijerph18041412
Bourrelier, J., Ryard, J., Dion, M., Merienne, F., Manckoundia, P., Mourey, F.: Use of a virtual environment to engage motor and postural abilities in elderly subjects with and without mild cognitive impairment (MAAMI Project). IRBM 37(2), 75–80 (2016). https://doi.org/10.1016/j.irbm.2016.02.007
Gomes, T.T., Schujmann, D.S., Fu, C.: Rehabilitation through virtual reality: physical activity of patients admitted to the intensive care unit. Revista Brasileira de Terapia Intensiva 31(4) (2019). https://doi.org/10.5935/0103-507X.20190078
Stojan, R., Voelcker-Rehage, C.: A Systematic review on the cognitive benefits and neurophysiological correlates of exergaming in healthy older adults. JCM 8(5), 734 (2019). https://doi.org/10.3390/jcm8050734
Eggenberger, P., Annaheim, S., Kündig, K.A., Rossi, R.M., Münzer, T., de Bruin, E.D.: Heart rate variability mainly relates to cognitive executive functions and improves through exergame training in older adults: a secondary analysis of a 6-month randomized controlled trial. Front. Aging Neurosci. 12, 197 (2020). https://doi.org/10.3389/fnagi.2020.00197
Postolache, O. et al.: Tailored virtual reality for smart physiotherapy. In: 2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE), pp. 1–6, Bucharest, Romania, March 2019. https://doi.org/10.1109/ATEE.2019.8724903
Malik, M.: Heart rate variability: standards of measurement, physiological interpretation, and clinical use: task force of the European society of cardiology and the North American society for pacing and electrophysiology. Ann. Noninv. Electrocard. 1(2), 151–181 (1996). https://doi.org/10.1111/j.1542-474X.1996.tb00275.x
Shimmer: Shimmer3 ECG. https://www.shimmersensing.com/shimmer3-ecg/
Burns, A., et al.: SHIMMERTM – a wireless sensor platform for noninvasive biomedical research. IEEE Sensors J. 10(9), 1527–1534 (2010). https://doi.org/10.1109/JSEN.2010.2045498
van Gent, P., Farah, H., van Nes, N., van Arem, B.: HeartPy: a novel heart rate algorithm for the analysis of noisy signals. Transport. Res. F: Traffic Psychol. Behav. 66, 368–378 (2019). https://doi.org/10.1016/j.trf.2019.09.015
Tarvainen, M.P., Niskanen, J.-P., Lipponen, J.A., Ranta-aho, P.O., Karjalainen, P.A.: Kubios HRV – heart rate variability analysis software. Comput. Methods Programs Biomed. 113(1), 210–220 (2014). https://doi.org/10.1016/j.cmpb.2013.07.024
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Rodrigues, M.J., Postolache, O., Cercas, F. (2021). Autonomic Nervous System Assessment Based on HRV Analysis During Virtual Reality Serious Games. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_57
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