Abstract
Back pain causes more global disability than any other health problem studied and the number of patients is growing. In Europe and in the US it is the number one cause of lost work days. This paper propounds a new approach by exploring the effect of utilizing a humanoid robot as a therapy-assistive tool in educating children to perform back exercises designed by a professional therapist. In our previous research a NAO robot was programmed and employed as a robotic assistant to a human physiotherapist to perform exercises in an elementary school in Slovakia. This paper goes further in designing a Wizard of Oz, where the exercises can be controlled and intervened by motivational behaviors of the robot (emotional expressions). Currently we are developing a system based on reinforcement learning that should adopt the motivational interventions from the Wizard. The promising results of this study in the physical therapy suggest the effective future use of social robots in reducing the symptoms of the most extended global disability in the world.
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Frank, J.W., et al.: Disability resulting from occupational low back pain: Part I: What do we know about primary prevention? A review of the scientific evidence on prevention before disability begins. Spine 21(24), 2908–2917 (1996)
Harreby, M., et al.: Are radiologic changes in the thoracic and lumbar spine of adolescents risk factors for low back pain in adults? A 25-year prospective cohort study of 640 school children. Spine 21, 2298–2302 (1995)
Loney, P.L., Stratford, P.W.: The prevalence of low back pain in adults: a methodological review of the literature. Physical therapy 79(4), 384–396 (1999)
Vos, T., et al.: Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet 380(9859), 2163–2196 (2013)
COST Action B13, Biomedicine and Molecuar Biosciences, Guidelines for the Management of Low Back Pain in Europe, Last updated: May 02, 2011. COST is supported by the EU Framework Programme Horizon (2020). http://www.cost.eu/COST_Actions/bmbs/Actions/B13
Weiss, H.R., et al.: Physical exercises in the treatment of idiopathic scoliosis at risk of brace treatment. Scoliosis 1(6), 1–7 (2006)
Negrini, S., et al.: Physical exercises as a treatment for adolescent idiopathic scoliosis. A Systematic Review. Developmental Neurorehabilitation 6(3–4), 227–235 (2003)
Leboeuf-Yde, C., Kyvik, K.O.: At what age does low back pain become a common problem?: A study of 29,424 individuals aged 12‐41 Years. Spine 23(2), 228–234 (1998)
Institute for Health Metrics and Evaluation ©, University of Washington (2013). htttp://vizhub.healthdata.org/irank/heat.php
Rabbitt, S.M., Kazdin, A.E., Scassellati, B.: Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use. Clinical Psychology Review 35, 35–46 (2015)
Kidd, C.D., Breazeal, C.: A robotic weight loss coach. In: Proceedings of the National Conference on Artificial Intelligence, vol. 22(2), p. 1985. AAAI Press, Menlo Park. MIT Press, Cambridge, 1999, 2007
Tapus, A., Tapus, C., Mataric, M.J.: The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia. In: Proceedings of the IEEE International Conference on Rehabilitation Robotics (2009)
Baxter, P., et al.: Long-term human-robot interaction with young users. In: Proceedings of the 6th IEEE/ACM International Conference on Human-Robot Interaction (Robots with Children Workshop) (2011)
Scassellati, B., Admoni, H., Mataric, M.J.: Robots for use in autism research. Annual Review of Biomedical Engineering 14, 275–294 (2012)
Alemi, M., Meghdari, A., Ghanbarzadeh, A., Moghadam, L.J., Ghanbarzadeh, A.: Impact of a social humanoid robot as a therapy assistant in children cancer treatment. In: Beetz, M., Johnston, B., Williams, M.-A. (eds.) ICSR 2014. LNCS, vol. 8755, pp. 11–22. Springer, Heidelberg (2014)
Fasola, J., Mataric, M.J.: Using socially assistive human–robot interaction to motivate physical exercise for older adults. Proceedings of the IEEE 100(8), 2512–2526 (2012)
Kose, H., et al.: Socially interactive robotic platforms as sign language tutors. International Journal of Humanoid Robotics 11(1) (2014)
Deshmukh, A., et al.: Empathic robotic tutors: map guide. In: Proceedings of the 10th IEEE/ACM International Conference on Human-Robot Interaction Extended Abstracts (2015)
Bhargava, S., et al.: Demonstration of the emote wizard of Oz interface for empathic robotic tutors. In: Proceedings of SIGdial
Serholt, S., et al.: Emote: embodied-perceptive tutors for empathy-based learning in game environment. In: European Conference GBL (2013)
Brown, L.V., Kerwin, R., Howard, A.M.: Applying behavioral strategies for student engagement using a robotic educational agent. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2013)
Komatsubara, T., et al.: Can a social robot help children’s understanding of science in classrooms? In: Proceedings of the 2nd International Conference on Human-Agent Interaction (2014)
Leite, I., Martinho, C., Paiva, A.: Social robots for long-term interaction: a survey. International Journal of Social Robotics 5(2), 291–308 (2013)
Vircikova, M., Sincak, P.: Experience with the children-humanoid interaction in rehabilitation therapy for spinal disorders. In: Kim, J.-H., Matson, E., Myung, H., Xu, P. (eds.) Robot Intelligence Technology and Applications. AISC, vol. 208, pp. 347–357. Springer, Heidelberg (2013)
Villano, M., et al.: DOMER: a wizard of Oz interface for using interactive robots to scaffold social skills for children with autism spectrum disorders. In: Proceedings of the 6th IEEE/ACM International Conference on Human-Robot Interaction (2011)
Lu, D.V., Smart, W.D.: Polonius: a wizard of Oz interface for HRI experiments. In: Proceedings of the 6th IEEE/ACM International Conference on Human-Robot Interaction (2011)
Steinfeld, A., Jenkins, O.C., Scassellati, B.: The Oz of wizard: simulating the human for interaction research. In: Proceedings of the 4th IEEE/ACM International Conference on Human-Robot Interaction (2009)
Riek, L.D.: Wizard of Oz studies in HRI: a systematic review and new reporting guidelines. Journal of Human-Robot Interaction 1(1) (2012)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
Thomaz, A.L.: Socially Guided Machine Learning. PhD Thesis (2006)
Thomaz, A.L., Cakmak, M.: Social Learning Mechanisms for Robots (2009)
Suay, H.B., Chernova, S.: Effect of human guidance and state space size on interactive reinforcement learning. In: Proceedings of the 20th International Symposium on Robot and Human Interactive Communication RO-MAN (2011)
Mitsunaga, N., et al.: Adapting Robot Behavior for Human-Robot Interaction. IEEE Transactions on Robotics 24(4) (2008)
Kartoun, U., Stern, H., Edan, Y.: A human-robot collaborative reinforcement learning algorithm. Journal of Intelligent & Robotic Systems 60(2), 217–239 (2010)
Broekens, J.: Emotion and reinforcement: affective facial expressions facilitate robot learning. In: Huang, T.S., Nijholt, A., Pantic, M., Pentland, A. (eds.) ICMI/IJCAI Workshops 2007. LNCS (LNAI), vol. 4451, pp. 113–132. Springer, Heidelberg (2007)
Olsen, D.R., Goodrich, M.A.: Metrics for evaluating human-robot interactions. In: Proceedings of PERMIS (2003)
Knox, W.B., Stone, P.: Interactively shaping agents via human reinforcement: the TAMER framework. In: Proceedings of the 5th International Conference on Knowledge Capture (2009)
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Magyar, G., Vircikova, M. (2015). Socially-Assistive Emotional Robot that Learns from the Wizard During the Interaction for Preventing Low Back Pain in Children. In: Tapus, A., André, E., Martin, JC., Ferland, F., Ammi, M. (eds) Social Robotics. ICSR 2015. Lecture Notes in Computer Science(), vol 9388. Springer, Cham. https://doi.org/10.1007/978-3-319-25554-5_41
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