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Anxiety detection using wearable monitoring

Published:03 November 2014Publication History

ABSTRACT

Social Anxiety Disorder (SAD) might be confused with shyness. However, experiencing anxiety can have profound short and long-term implications. During an anxiety span, the subject suffers from blushing, sweating or trembling. Social activities are harder to accomplish and the subject might tend to avoid them. Although there are tested methods to treat SAD such as Exposure Therapy (ET) and Pharmacotherapy, patients do not treat themselves or suspend treatment due economic, time or space barriers. Wearable computing technologies can be used to constantyly monitor user context offering the possibility to detect anxiety spans. In this work we used Google Glass and the Zephyr HxM Bluetooth band to monitor Spontaneous Blink Rate (SBR) and Heart Rate (HR) respectively. We conducted an experiment that involved 8 subjects in two groups: Mild SAD and No SAD. The experiment consisted on an induced anxiety situation where each participant gave a 10 minutes speech in front of 2 professors. We found higher average heart rates after induced anxiety spans on the mild SAD group. However, we found no evidence of increased SBR as an anxiety indicator. These results indicate that wearable devices can be used to detect anxiety.

References

  1. Wang, X., Zhao, X., Gnawali, O., Loverland, K. A., Prakasha V., and Shi W. 2013. A Real-Time Selective Speaker Cancellation System for Relieving Social Anxiety in Autistics. Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2013 7th International Conference on. Pages 420 -- 423, May 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Yuen, E. K., Herbert, J. D., Forman, E. M., Goetter, E. M., Juarascio, A. S., Rabin, S., Goodwin, C., and Bouchard, S. 2013. Acceptance based behavior therapy for social anxiety disorder through videoconferencing. Journal of Anxiety Disorders, Volume 27, Issue 4, Pages 389--397, May 2013.Google ScholarGoogle ScholarCross RefCross Ref
  3. Dagöö, J., Asplund, R. P., Bsenko, H. A., Hjerling, S., Holmberg, A., Westh, S., ÖIberg, L., Ljótsson, B., Carlbing, P., Furmark, T., and Andersson, G. 2014. Cognitive behavior therapy versus interpersonal psychotherapy for social anxiety disorder delivered via smartphone and computer: A randomized controlled trial. Journal of Anxiety Disorders, Volume 28, Issue 4, Pages 410--417, May 2014.Google ScholarGoogle ScholarCross RefCross Ref
  4. Moscovitch, D. A., Suvak, M. K., Hofmann, S. G. 2010. Emotional response patterns during social threat in individuals with generalized social anxiety disorder and non-anxious controls. Journal of Anxiety Disorders, Volume 24, Issue 7, Pages 785--791, October 2010.Google ScholarGoogle ScholarCross RefCross Ref
  5. Rennert, K., and Karapanos, E. 2013. FaceIt: Supporting Reflection upon Social Anxiety Events with Lifelogging. CHI 2013: Changing Perspectives, Paris, France, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Gaebler, M., Daniels, J. K., Lamke, J., Fydrich, T., and Walter, H. 2013. Heart rate variability and its neural correlates during emotional face processing in social anxiety disorder. Biological Psychology 94, Pages 319--330, 2013.Google ScholarGoogle Scholar
  7. Ishimaru, S., Kunze, K., and Kise, K. 2014. In the Blink of an Eye - Combining Head Motion and Eye Blink Frequency for Activity Recognition with Google Glass. AH'14, Kobe, Japan, March 07-09, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Deiters, D. D., Stevens, S., Hermann, C., and Gerlach, A. L. 2013. Internal and external attention in speech anxiety. Journal of Behavior Therapy and Experimental Psychiatry 44, pages 143--149, 2013.Google ScholarGoogle Scholar
  9. Hoque, M. E., Courgeon, M., Martin, J., Mutlu, B., and Picard, W.R. 2013. MACH: My Automated Conversation coacH. UbiComp'13, Zurich, Switzerland, September 8-12, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Harbort, J., Witthöft, M., Spiegel, J., Nick, K., and Hecht, H. 2013. The widening of the gaze cone in patients with social anxiety disorder and its normalization after CBT. Behaviour Research and Theray 51, pages 459--367, 2013.Google ScholarGoogle Scholar
  11. Yuen, E. K., Herbert, J. D., Forman, E. M., Goetter, E. M., Comer, R., and Bradley, J.C. Treatment of Social Anxiety Disorder Using Online Virtual Environments in Sencod Life. Behaviour Therapy 44, pages 51--616, 2013.Google ScholarGoogle Scholar
  12. Simm, W., Ferrario M.A., Gradinar A., and Whittle, J. 2014. Prototyping 'Clasp': Implications for Designing Digital Technology for and with Adults with Autism. DIS, Vancouver, BC, Canada, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Stein, M.B., and Stein, D. J. 2008. Social Anxiety Disorder. Lancet, 37:1115--25, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  14. Kang, S., Rizzo, A. S., and Gratch, J. 2012. Understanding the Nonverbal Behavior of Socially Anxious People during Intimate Self-disclosure. LNAI 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Repetto, C., Gaggioli, A., Pallavicini, F., Cipresso, P., Raspelli, S., and Riva G. 2013. Virtual reality and mobile phones in the treatment of generalized anxiety disorders: a phase-2 clinical trial. Pers Ubiquit Comput, 17:253--260, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Other conferences
      MexIHC '14: Proceedings of the 5th Mexican Conference on Human-Computer Interaction
      November 2014
      56 pages
      ISBN:9781450332859
      DOI:10.1145/2676690

      Copyright © 2014 ACM

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      Publication History

      • Published: 3 November 2014

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