MoviBed - Sleep Analysis Using Capacitive Sensors

  • Maxim Djakow
  • Andreas Braun
  • Alexander Marinc
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8516)


Sleep disorders are a wide-spread phenomenon that can gravely affect personal health and well-being. An individual sleep analysis is a first step in identifying unusual sleeping patterns and providing suitable means for further therapy and preventing escalation of symptoms. Typically such an analysis is an intrusive method and requires the user to stay in a sleep laboratory. In this work we present a method for detecting sleep patterns based on invisibly installed capacitive proximity sensors integrated into the bed frame. These sensors work with weak electric fields and do not disturb sleep. Using the movements of the sleeping person we are able to provide a continuous analysis of different sleep phases. The method was tested in a prototypical setup over multiple nights.


Capacitive proximity sensor sleep analysis smart furniture 


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  1. 1.
    Pilcher, J.J., Huffcutt, A.J.: Effects of sleep deprivation on performance: A meta-analysis. Sleep J. Sleep Res. Sleep Med. 19, 318–326 (1996)Google Scholar
  2. 2.
    Moser, D., Anderer, P., Gruber, G., Parapatics, S.: Sleep classification according to AASM and Rechtschaffen & Kales: effects on sleep scoring parameters. Sleep (2009)Google Scholar
  3. 3.
    Littner, M.M., Kushida, C.: Practice parameters for the role of actigraphy in the study of sleep and circadian rhythms: an update for 2002. Sleep (2003)Google Scholar
  4. 4.
    Jones, C., Campbell, S., Zone, S.: Familial advanced sleep-phase syndrome: A short-period circadian rhythm variant in humans. Nat. Med. (1999)Google Scholar
  5. 5.
    Zimmerman, T.G., Smith, J.R., Paradiso, J.A., Allport, D., Gershenfeld, N.: Applying electric field sensing to human-computer interfaces. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI 1995, pp. 280–287. ACM Press, New York (1995)Google Scholar
  6. 6.
    Braun, A., Hamisu, P.: Using the human body field as a medium for natural interaction. In: Proceedings of the 2nd International Conference on PErvsive Technologies Related to Assistive Environments - PETRA 2009, pp. 1–7. ACM Press, New York (2009)Google Scholar
  7. 7.
    Große-Puppendahl, T.A., Marinc, A., Braun, A.: Classification of User Postures with Capacitive Proximity Sensors in AAL-Environments. In: Keyson, D.V., et al. (eds.) AmI 2011. LNCS, vol. 7040, pp. 314–323. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  8. 8.
    Braun, A., Heggen, H.: Context recognition using capacitive sensor arrays in beds. Technik für ein selbstbestimmtes Leben - 5. Deutscher AAL-Kongress. VDE VERLAG GmbH, Berlin (2012)Google Scholar
  9. 9.
    Krejcar, O., Jirka, J., Janckulik, D.: Use of mobile phones as intelligent sensors for sound input analysis and sleep state detection. Sensors (2011)Google Scholar
  10. 10.
    AppZoo GmbH, (retrieved January 27, 2014)
  11. 11.
    Schulz, H.: Rethinking sleep analysis. J. Clin. Sleep Med. 4, 99–103 (2008)Google Scholar
  12. 12.
    Wilde-Frenz, J., Schulz, H.: Rate and distribution of body movements during sleep in humans. Percept. Mot. Skills (1983)Google Scholar
  13. 13.
    Salmi, T., Leinonen, L.: Automatic analysis of sleep records with static charge sensitive bed. Electroencephalogr. Clin. Neurophysiol. 64, 84–87 (1986)CrossRefGoogle Scholar
  14. 14.
    Wimmer, R., Kranz, M., Boring, S., Schmidt, A.: A Capacitive Sensing Toolkit for Pervasive Activity Detection and Recognition. In: Fifth Annu. IEEE Int. Conf. Pervasive Comput. Commun. PerCom 2007, pp. 171–180 (2007)Google Scholar
  15. 15.
    Grosse-Puppendahl, T., Berghoefer, Y., Braun, A., Wimmer, R., Kuijper, A.: OpenCapSense: A Rapid Prototyping Toolkit for Pervasive Interaction Using Capacitive Sensing. In: IEEE Int. Conf. Pervasive Comput. Commun. (March 18-22, 2013)Google Scholar
  16. 16.
    Guerrero-Mora, G., Elvia, P.: Sleep-wake detection based on respiratory signal acquired through a Pressure Bed Sensor. Engineering in Medicine and Biology Society, EMBC (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Maxim Djakow
    • 1
  • Andreas Braun
    • 2
  • Alexander Marinc
    • 2
  1. 1.Hochschule DarmstadtDarmstadtGermany
  2. 2.Fraunhofer Institute for Computer Graphics Research IGDDarmstadtGermany

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