BREATH AND POSITION MONITORING DURING SLEEPING WITH A DEPTH CAMERA

Meng-Chieh Yu, Huan Wu, Jia-Ling Liou, Ming-Sui Lee, Yi-Ping Hung

2012

Abstract

Sleep monitoring is increasingly seen as a common and important issue. In this paper, a depth analysis technique was developed to monitor user’s sleep conditions without any physical contact. In this research, a cross-section method was proposed to detect user’s head and torso from the depth images. Then, the system can monitor user’s breathing rate, sleep position, and sleep cycle. In order to evaluate the measurement accuracy of this system, two experiments were conducted. In the first experiment, eight participants with various body shapes were asked to join the experiment. They were asked to change the sleep positions (supine and side-lying) every fifteen breathing cycles in two circumstances (sleep with and without a thin quilt) on the bed. The experimental results showed that the system is promising to detect the head and torso with various sleeping postures. In the second experiment, a realistic over-night sleep monitoring experiment was conducted. The experimental results demonstrated that this system is promising to monitor the sleep conditions in realistic sleep conditions. To conclude, this study is important for providing a non-contact technology to detect multiple sleep conditions and assist users in better understanding of their sleep quality.

References

  1. Aoki, H. and Koshiji, K., 2006. Non-contact Respiration monitoring method for screening sleep respiratory disturbance using slit light pattern projection. World Congress on Medical Physics and Biomedical Engineering, 14(7), 680-683.
  2. Ancoli-Israel, S., Cole, R., Alessi, C., Chambers, M., Moorcroft, W., Pollak, C. P., 2003. The role of actigraphy in the study of sleep and circadian rhythms, Sleep , 26(3), 342-392.
  3. BaHammam, A., 2004. Comparison of nasal prong pressure and thermistor measurements for detecting respiratory events during sleep. Respiration, 71(4), 385-390.
  4. Idzikowski, C., 2003. Sleep position gives personality clue. BBC News, 16 September 2003.
  5. Born, J., Lange, T., Hansen, K., Molle, M. and Fehm, H. L., 1997. Effects of sleep and circadian rhythm on human circulating immune cells. The Journal of Immunology, 158(9), 4454-4464.
  6. Cantineau, J. P., Escourrou, P., Sartene, R., Gaultier, C., and Goldman, M., 1992. Accuracy of respiratory inductive plethysmography during wakefulness and sleep in patients with obstructive sleep apnea. Chest, 102(4), 1145-1151.
  7. Cartwright, R. D., 1984. Effect of sleep position on sleep apnea severit. Sleep, 7(2), 110-114.
  8. Douglas, N., Thomas, S., and Jan, M., 1992. Clinical value of polysomnography, Lancet, 339, 347-350.
  9. Fitbit, http://www.fitbit.com/ , retrieved on 2011/5.
  10. Harada, T., Sakata, A., Mori, T., and Sato, T., 2000. Sensor pillow system: monitoring respiration and body movement in sleep, Intelligent Robots and Systems, 1, pp. 351-356.
  11. Hoque, E., Dickerson, R. F., Stankovic, J. A., 2010. Monitoring body positions and movements during sleep using WISPs. Wireless Health, 44-53.
  12. Kushida, C. A., Chang, A., Gadkary, C., Guilleminault, C., Carrillo, O., and Dement, W.C., 2001. Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients. Sleep Med., 2(5), 389-396.
  13. Microsoft, Kinect, http://www.xbox.com/kinect, retrieved on 2011/3.
  14. Loord, H., and Hultcrantz, E., 2007. Positioner - a method for preventing sleep apnea. Acta Oto-laryngologica, 127(8), 861-868.
  15. Maquet, P., 2001. The role of sleep in learning and memory. Science, 294, 1048-1052.
  16. Malakuti, K. and Albu, A. B., 2010. Towards an intelligent bed sensor: Non-intrusive monitoring of sleep irregularities with computer vision techniques. International Conference on Pattern Recognition, 4004-4007.
  17. Nakajima, K., Matsumoto, Y., and Tamura, T., 2001. Development of real-time image sequence analysis for evaluating posture change and respiratory rate of a subject in bed. PHYSIOLOGICAL MEASUREMENT, 22, N21-N28.
  18. Philips Actiwatch, http://www.healthcare.philips.com/ , retrieved on 2010/8
  19. PneumaCare, http://www.pneumacare.com/ , retrieved on 2011/6.
  20. Wareham,R., Lasenby,J., Cameron, J., Bridge, P. D., and Iles, R., 2009. Structured light plethysmography (SLP) compared to spirometry: a pilot study, European Respiratory Society Annual Congress.
  21. Sadeh, A., Sharkey, K. M., and Carskadon, M. A., 1994. Activity-based sleep-wake identification: an empirical test of methodological issues. Sleep, 17(3), 201-207.
  22. Staderini, E. M., 2002. UWB radars in medicine. Aerospace and Electronic Systems Magazine, 17(1), 13-18.
  23. Spiegel, K., Leproult, R., and Cauter, D. V., 1999. Impact of sleep debt on metabolic and endocrine function. The LANCET, 354(9188), 1435-1439.
  24. Szollosi, I., Roebuck, T., Thompson, B., Naughton, M. T., 2002. Lateral sleeping position reduces severity of central sleep apnea/cheyne-stokes respiration, Sleep, 29 (8), 1045-1051.
  25. Thought Technology Ltd., http://www.thoughttechnology. com/, retrieved on 2010/6.
  26. Wang, C., Ahmed, A., and Hunter, A., 2007. Locating the upper body of covered humans in application to diagnosis of obstructive sleep apnea. Proceedings of the World Congress on Engineering, 662-667.
  27. Whyte, K. F., Gugger, M., Gould, G. A., Molloy, J., Wraith, P. K., and Douglas, N. J., 1991. Accuracy of respiratory inductive plethysmograph in measuring tidal volume during sleep, Journal of Applied Physiology, 71(5), 1866-1871.
  28. WakeMate, http://www.wakemate.com/ , retrieved on 2011/5.
  29. Ziganshin, E. G., Numerov, M. A., and Vygolov, S. A., 2010. UWB baby monitor. Ultrawideband and Ultrashort Impulse Signals, 159-161.
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Paper Citation


in Harvard Style

Yu M., Wu H., Liou J., Lee M. and Hung Y. (2012). BREATH AND POSITION MONITORING DURING SLEEPING WITH A DEPTH CAMERA . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2012) ISBN 978-989-8425-88-1, pages 12-22. DOI: 10.5220/0003702000120022


in Bibtex Style

@conference{healthinf12,
author={Meng-Chieh Yu and Huan Wu and Jia-Ling Liou and Ming-Sui Lee and Yi-Ping Hung},
title={BREATH AND POSITION MONITORING DURING SLEEPING WITH A DEPTH CAMERA},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2012)},
year={2012},
pages={12-22},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003702000120022},
isbn={978-989-8425-88-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2012)
TI - BREATH AND POSITION MONITORING DURING SLEEPING WITH A DEPTH CAMERA
SN - 978-989-8425-88-1
AU - Yu M.
AU - Wu H.
AU - Liou J.
AU - Lee M.
AU - Hung Y.
PY - 2012
SP - 12
EP - 22
DO - 10.5220/0003702000120022