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Respiration Rate Measurement based on Motion Compensation using Infrared Camera

열화상 카메라를 이용한 움직임 보정 기반 호흡 수 계산

  • Kwon, Jun Hwan (Dept. of Medical Engineering, Yonsei University College of Medicine) ;
  • Shin, Cheung Soo (Dept. of Anesthesiology and Pain Medicine, Yonsei University College of Medicine) ;
  • Kim, Jeongmin (Dept. of Anesthesiology and Pain Medicine, Yonsei University College of Medicine) ;
  • Oh, Kyeong Taek (Dept. of Medical Engineering, Yonsei University College of Medicine) ;
  • Yoo, Sun Kook (Dept. of Medical Engineering, Yonsei University College of Medicine)
  • Received : 2018.03.14
  • Accepted : 2018.08.01
  • Published : 2018.09.30

Abstract

Respiration is the process of moving air into and out of the lung. Respiration changes the temperature in the chamber while exchanging energy. Especially the temperature of the face. Respiration monitoring using an infrared camera measures the temperature change caused by breathing. The conventional method assumes that motion is not considered and measures respiration. These assumptions can not accurately measure the respiration rate when breathing moves. In addition, the respiration rate measurement is performed by counting the number of peaks of the breathing waveform by displaying the position of the peak in a specific window, and there is a disadvantage that the breathing rate can not be measured accurately. In this paper, we use KLT tracking and block matching to calibrate limited weak movements during breathing and extract respiration waveform. In order to increase the accuracy of the respiration rate, the position of the peak used in the breath calculation is calculated by converting from a single point to a high resolution. Through this process, the respiration signal could be extracted even in weak motion, and the respiration rate could be measured robustly even in various time windows.

Keywords

References

  1. J. Mead and J.L. Whittenberger, "Physical Properties of Human Lungs Measured During Spontaneous Respiration," Journal of Applied Physiology, Vol. 5, Issue 12, pp. 779-796, 1953. https://doi.org/10.1152/jappl.1953.5.12.779
  2. P. Corbishley and E.R. Villegas, "Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 1, pp. 196-204, 2008. https://doi.org/10.1109/TBME.2007.910679
  3. K. Storck, M. Karlsson, P. Ask, and D. Loyd, “Heat Transfer Evaluation of the Nasal Thermistor Technique,” IEEE Transactions on Biomedical Engineering, Vol. 43, No. 12, pp. 1187-1191, 1996. https://doi.org/10.1109/10.544342
  4. B. Mazzanti, C. Lamberti, and J.D Bie, "Validation of an ECG-derived Respiration Monitoring Method," Computers in Cardiology, pp. 613-616, 2003.
  5. E.F Greneker, "Radar Sensing of Heartbeat and Respiration at a Distance with Security Applications," Proceeding of Society of Photographic Instrumentation Engineers, Vol. 3066, pp. 22-28 1997.
  6. K.T. Oh, C.S. Shin, J. Kim, and S.K. Yoo, “Level Set Based Respiration Rate Estimation Using Depth Camera,” Journal of Korea Multimedia Society, Vol. 20, No. 9, pp. 1491-1501, 2017. https://doi.org/10.9717/KMMS.2017.20.9.1491
  7. A.K. Abbas, K. Heimann, and K. Jergus, "Neonatal Non-contact Respiratory Monitoring Based on Real-time Infrared Thermography," BioMedical Engineering OnLine, Vol. 10, No. 93, pp. 1-17, 2011. https://doi.org/10.1186/1475-925X-10-1
  8. J. Fei and I. Pavlidis, "Virtual Thermistor," Proceeding of 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 250-253, 2007.
  9. S.L. Bennett, R. Goubran, and F. Knoefel, "Comparison of Motion-based Analysis to Thermal-based Analysis of Thermal Video in the Extraction of Respiration Patterns," Proceeding of 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3835-3839, 2017.
  10. J. Ruminski, "Analysis of the Parameters of Respiration Patterns Extracted from Thermal Image Sequences," Biocybernetics and Biomedical Engineering, Vol. 36, Issue 4, pp. 731-741, 2016. https://doi.org/10.1016/j.bbe.2016.07.006
  11. FLIR T420 Thermal Imaging Camera Specification, https://www.flir-direct.com/pdfs/cache/www.flir-direct.com/t420/datasheet/t420-datasheet.pdf 2018.09.18
  12. B.D. Lucas and T. Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision," Proceedings of the 7th International Joint Conference on Artificial Intelligence, Vol. 2, pp. 674-679, 1981.
  13. C. Tomasi and T. Kanade, "Detection and Tracking of Point Features," Technical Report CMU-CS-91-132, Carnegie Mellon University.
  14. F. Bourel, C. Chibelushi, and A. Low, "Robust Facial Feature Tracking," Proceedings of the British Machine Conference, pp. 1-10, 2000.
  15. E.H. Adelson, C.H. Anderson, J.R. Bergen, P.J. Burt, and J.M. Ogden "Pyramid Methods in Image Processing," Radio Corporation of America Engineer, Vol. 29, No. 6, pp. 33-41, 1984.
  16. Z. Kalal, K. Mikolajczyk, and J. Matas, "Forward-Backward Error: Automatic Detection of Tracking Failures," Proceeding of 2010 20th International Conference on Pattern Recognition, pp. 2756-2759, 2010.