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Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis
Abstract:This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1340062Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1288
 J. B. Weinberg, and X. Yu, “Robotics in education: Low-cost platforms for teaching integrated systems,” Robotics & Automation Magazine, IEEE, 10(2), pp. 4-6, 2003.
 B. Robins, K. Dautenhahn, R. Te Boekhorst, and A. Billard, “Robotic assistants in therapy and education of children with autism: Can a small humanoid robot help encourage social interaction skills?” Universal Access in the Information Society, 4(2), pp. 105-120, 2005.
 T. Kanda, R. Sato, N. Saiwaki, and H. Ishiguro, “A two-month field trial in an elementary school for long-term human–robot interaction,” Robotics, IEEE Transactions on, 23(5), pp. 962-971, 2007.
 L. Geppert, Qrio, the robot that could. Ieee Spectrum, 41(5), pp. 34-37, 2004.
 M. Fujita, and R. Enteretainment, “Entertainment Robot: AIBO,” The journal of the Institute of Image Information and Television Engineers, 54(5), pp. 657-661, 2000.
 H. I. Krebs, e., “Rehabilitation robotics: Performance-based progressive robot-assisted therapy,” Autonomous Robots, 15(1), pp. 7-20, 2003.
 T. Mukai, et al., “Development of a nursing-care assistant robot riba that can lift a human in its arms,” In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference, pp. 5996-6001. October 2010.
 T. Nef, and R. Riener, “ARMin-design of a novel arm rehabilitation robot,” In Rehabilitation Robotics, ICORR 2005. 9th International Conference, pp. 57-60, IEEE, June 2005.
 K. Wada, T. Shibata, T. Saito, and K. Tanie, “Effects of robot-assisted activity for elderly people and nurses at a day service center,” Proceedings of the IEEE, 92(11), pp. 1780-1788, 2004.
 S. Shamsuddin, H. Yussof, L. Ismail, F. A. Hanapiah, S. Mohamed, H. A. Piah, and N. I. Zahari, “Initial response of autistic children in humanrobot interaction therapy with humanoid robot NAO,” In Signal Processing and its Applications (CSPA), 2012 IEEE 8th International Colloquium, pp. 188-193, IEEE, March 2012.
 H. Kozima, C. Nakagawa, and Y. Yasuda, “Interactive robots for communication-care: A case-study in autism therapy,” In Robot and Human Interactive Communication, ROMAN 2005. IEEE International Workshop, pp. 341-346, August 2005.
 R. Yamazaki, S. Nishio, H. Ishiguro, M. Nørskov, N. Ishiguro, and G. Balistreri, “Social acceptance of a teleoperated android: Field study on elderly’s engagement with an embodied communication medium in denmark,” In Social Robotics, pp. 428-437, Springer Berlin Heidelberg, 2012.
 T. Fong, I. Nourbakhsh, and K. Dautenhahn, “A survey of socially interactive robots,” Robotics and autonomous systems, 42(3), pp. 143- 166, 2003.
 P. London, J. T. Hart, and M. P. Leibovitz, “EEG alpha rhythms and susceptibility to hypnosis,” Nature, 1968.
 M. E. Sabourin, S. D. Cutcomb, H. J. Crawford, and K. Pribram, “EEG correlates of hypnotic susceptibility and hypnotic trance: Spectral analysis and coherence,” International Journal of Psychophysiology, 10(2), pp. 125-142, 1990.
 R. Freeman, A. Barabasz, M. Barabasz, and D. Warner, “Hypnosis and distraction differ in their effects on cold pressor pain,” American Journal of Clinical Hypnosis, 43(2), pp. 137-148, 2000.
 J. D. Williams, and J. H. Gruzelier, “Differentiation of hypnosis and relaxation by analysis of narrow band theta and alpha frequencies,” International Journal of Clinical and Experimental Hypnosis, 49(3), pp. 185-206, 2001.
 N. F. Graffin, W. J. Ray, and R. Lundy, “EEG concomitants of hypnosis and hypnotic susceptibility,” Journal of Abnormal Psychology, 104(1), pp. 123-131, 1995.
 G. Ádám, I. Mészáros, and É. I. Bányai, eds. Brain and behaviour: proceedings of the 28th International Congress of Physiological Sciences, Budapest, 1980. Vol. 17. Elsevier, 2013.
 http://www.sccn.ucsd.edu/eeglab (Accessed on 20/12/2016)
 A. A. Fingelkurts, A. A. Fingelkurts, S. Kallio, and A. Revonsuo, “Cortex functional connectivity as a neurophysiological correlate of hypnosis: an EEG case study,” Neuropsychologia 45.7, pp. 1452-1462, 2007
 P., Sauseng, and W. Klimesch, “What does phase information of oscillatory brain activity tell us about cognitive processes?” Neuroscience & Biobehavioral Reviews, 32(5), pp. 1001-1013, 2008.
 W. Klimesch, M. Doppelmayr, A. Yonelinas, N. E. A. Kroll, M. Lazzara, D. Röhm, and W. Gruber, “Theta synchronization during episodic retrieval: neural correlates of conscious awareness,” Cognitive Brain Research, 12(1), pp. 33-38, 2001.
 T. Fernández, et al., “EEG activation patterns during the performance of tasks involving different components of mental calculation,” Electroencephalography and clinical Neurophysiology, 94(3), pp. 175- 182, 1995.
 V. Galea, E. Z. Woody, H. Szechtman, and M. R. Pierrynowski, “Motion in response to the hypnotic suggestion of arm rigidity: A window on underlying mechanisms,” Intl. Journal of Clinical and Experimental Hypnosis, 58(3), pp. 251-268, 2010.
 M. J. Batty, S. Bonnington, B. K. Tang, M. B. Hawken, and J. H. Gruzelier, “Relaxation strategies and enhancement of hypnotic susceptibility: EEG neurofeedback, progressive muscle relaxation and self-hypnosis,” Brain research bulletin, 71(1), pp. 83-90, 2006.
 J. H. Gruzelier, “EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants,” Neuroscience & Biobehavioral Reviews, 44, pp. 124-141, 2014.
 K. Thornton, “Improvement/rehabilitation of memory functioning with neurotherapy/QEEG biofeedback,” The Journal of head trauma rehabilitation, 15(6), pp. 1285-1296, 2000.
 B. H. Cho, et al., “Neurofeedback training with virtual reality for inattention and impulsiveness,” Cyberpsychology & Behavior, 7(5), pp. 519-526, 2004.