Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
권호 표지

Snoring Detection Sleep Pillow

코골이 감지 수면베개

  • Tran, Minh (Department of Electronic Engineering, Keimyung University) ;
  • Ahn, Dohyun (Department of Biomedical Engineering, Kyungpook National University) ;
  • Park, Jaehee (Department of Electronic Engineering, Keimyung University)
  • 쩐밍 (계명대학교 전자공학과) ;
  • 안도현 (경북대학교 의공학과) ;
  • 박재희 (계명대학교 전자공학과)
  • Received : 2019.06.02
  • Accepted : 2019.06.26
  • Published : 2019.06.30
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Abstract

People sleep about one-third of their lives and their sleep time varies according to age. Adult usually sleep 8 hours a day. However, that dose not guarantee good sleep. The cause of this is due to sleep disorders like snoring and sleep apnea. In this paper, the smart pillow for detecting snoring among sleep disorders is investigated. This pillow consists of two microphones located on the left and right side of the pillow. For simple detecting, the snoring signal was converted into the pulse using a peak detection circuit. The decision of the snoring occurrence was by pulse duration. The accuracy of the snoring detection was about 97%. The research results show that the smart pillow can be use to detect the snoring during sleeping.

사람들은 일생동안 1/3을 잠을 자며 그들의 잠자는 시간은 나이에 따라 변하게 된다. 일반적으로 어른들은 하루에 8시간의 잠을 잔다. 그러나 항상 좋은 잠자리를 기대할 수는 없다. 실제로 50대 이상의 많은 사람들은 수면 문제를 가지고 있다. 이는 코골이, 수면 무호흡과 같은 수면 장애요소들 때문에 발생하는 것이다. 이 논문에서는 수면 장애요소 중 하나인 코골이를 검출하는 스마트 베개에 대해서 조사하였다. 스마트 베개는 베개의 오른쪽과 왼쪽 부분에 위치한 두 개의 마이크로폰으로 구성되어져 있다. 쉽게 코골이는 검출하기 위하여 피크 검출회로를 사용하여 코골이 신호를 펄스신호로 변형시켰으며, 펄스폭을 사용하여 코골이 이벤트 발생을 판단하였다. 측정된 코골이 검출 정확도는 약 98.6%이었다. 본 연구에서 얻은 연구 결과들이 스마트 베개가 수면 중 코골이를 검출할 수 있음을 보여 주었다.

Keywords

References

  1. A. Chesson, M. Littner, D. Davila, W. Anderson, M. Damberger, K. Hartse, S. Johnson, and M. Wise, "Practice parameters for the use of light therapy in the treatment of sleep disorders", Sleep, vol. 22, pp.641-660, 1999. https://doi.org/10.1093/sleep/22.5.641
  2. S. Elliott, M. Kim, J. Beaulieu, and G. Stefano, "Sound therapy induced relaxation: down regulating stress processes and pathologies", Medical Science Monitor, vol. 9, pp.116-121, 2003.
  3. M. David, J. Patrie, R. Felder, and M. Alwan, "Development and preliminary validation of heart rate and breathing rate detection using a passive, ballistocardiography-based sleep monitoring system", IEEE Tran. Inf. Technol. Biomed., vol. 13, pp.111-120, 2009. https://doi.org/10.1109/TITB.2008.2007194
  4. J. Kelly, R. Strecker, and M. Bianchi, " Recent developments in home sleep-monitoring devices", ISRN Neurol., vol. 2012, pp.1-10, 2012.
  5. S. Gyualy, D. Gould, B. Sawyer, D. Pond, A. Mant, and N. Saunders, "Evaluation of a microprocessor-based portable home monitoring system to measure breathing during sleep", Sleep, vol. 10, pp. 130-142, 1987. https://doi.org/10.1093/sleep/10.2.130
  6. H. Ju, Y. Park, J. Park, B. Lee, J. lee, and J. Lee, "Real-Time Driver's Biological Signal Monitoring System", Sensors Mater., vol. 27, pp.51-59, 2015.
  7. D. Ahn, T. Minh, J. Lee, and J. Park, "Respiration measurement sleeping pillow system", Journal of Sensor Science and Technology, vol. 26, pp.280-285, 2017. https://doi.org/10.5369/JSST.2017.26.4.280
  8. X. Zhu, W. Chen, T. Nemoto, Y. Kanemitsu, K. Kitamura, K. Yamakoshi, and D. Wei, "Real-time monitoring of respiration rhythm and pulse rate during sleep", IEEE Tran. Biomed. Eng., vol. 53, pp.2553-2563, 2006. https://doi.org/10.1109/TBME.2006.884641
  9. S. Eom, J. Park, and J. Lee. "Optical fiber arterial pulse wave sensor." Microwave Opt. Technol. Lett., vol.52, pp.1318-1321, 2010. https://doi.org/10.1002/mop.25200
  10. H. Lee, Y. Jang, and W. Chung, "Motor Imagery based Application Control using 2 Channel EEG Sensor", Journal of Sensor Science and Technology, vol. 25, pp.257-263, 2016. https://doi.org/10.5369/JSST.2016.25.4.257
  11. F. Bezombes, M. Lalor, and D. Burton, " Contact microphone using optical fibre bragg gratting technology", J. Phys.: Conf. Ser., vol 76, pp.1-6, 2007. https://doi.org/10.1088/0031-8949/76/1/001
  12. H. Shin and J. Cho, " Unconstrained snoring detection using a smartphone during ordinary sleep", Biomed. Eng. Online, vol 13, pp. 1-14, 2014. https://doi.org/10.1186/1475-925X-13-1
  13. K. Watanabe, T. Watanabe, H. watanabe, H. Ando, T. Ishihawa, and K. Kobayashi, " Noninvasive measurement of heartbeat, respiration, snoring and body movements of a subject in Bed via a pneumatic method," IEEE Trnas. Biomed. Eng., vol. 52, pp. 2100-2107, 2005. https://doi.org/10.1109/TBME.2005.857637
  14. T. Penzel, G. Amend, K. Meinzer, J. Peter, and P. Wichert, " MESAM; a heart rate and snoring recorder for detection of obstructive sleep apnea," Sleep, vol. 13, pp. 175-182, 1990. https://doi.org/10.1093/sleep/13.2.175
  15. J. Kim, Y. Noh, and D. Jeong, " Implementation of real-time heart activity monitoring system using heart sound, Journal of Convergence Signal Processing, vol. 1p, pp. 14-19, 2018.