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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Estimation of respiration rate using an accelerometer and thermal camera in eGlasses

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DOI: http://dx.doi.org/10.15439/2016F329

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 1431–1434 ()

Full text

Abstract. Respiration rate is a very important vital sign. Different methods of respiration rate measurement or estimation have been developed. However, especially interesting are those that enable remote and unobtrusive monitoring. In this study we investigated the use of smart glasses for the estimation of respiration rate especially useful for indoors applications. Two methods were analyzed. The first one is based on measurements of respiration-related body movements using an accelerometer. The second one uses thermal camera to observe temperature changes in nostril regions. For both methods signals were extracted, filtered and processed using two different respiration rate estimators. Both methods were validated during experiments with the participation of volunteers using the respiration belt as a reference measurement method. Results proved that for both methods it is possible to reliable estimate the respiration rate with Root Mean Square Error lower than 2 breaths per minute, which is sufficient for medical screening.

References

  1. Smart Glasses Portal, 2016, Available: http://www.smartglassesnews.org.
  2. Evena Medical, 2014, Available: http://evenamed.com/~even5672/products/glasses.
  3. C. Borchers, “Google Glass moves into the hospital at Beth Israel”, the Boston Globe, 14.06.2014, Available: http://www.bostonglobe.com
  4. J. Ruminski, A. Bujnowski, T. Kocejko, A. Andrushevich, M. Biallas, R. Kistler, “The data exchange between smart glasses and healthcare information systems using the HL7 FHIR standard”, 9th International Conference on Human System Interaction, IEEE, eXplore, 2016.
  5. J. Ruminski, K. Czuszynski, “Application of smart glasses for fast and automatic color correction in health care”, Proc. of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy, 2015.
  6. Philips, “Delivering vital patient data via Google Glass”, 03.10.2013, Available: http://www.healthcare.philips.com/main/about/future-of-healthcare/
  7. J. Hernandez, Y. Li, J. M. Rehg and R. W. Picard, "BioGlass: Physiological parameter estimation using a head-mounted wearable device," Wireless Mobile Communication and Healthcare (Mobihealth), 2014 EAI 4th International Conference on, Athens, 2014, pp. 55-58.
  8. J. Ruminski, “The accuracy of pulse rate estimation from the sequence of face images”, 9th International Conference on Human System Interaction, IEEE, eXplore, 2016.
  9. M. Z. Poh, D. J. McDuff, R. W. Picard "Non-contact, automated cardiac pulse measurements using video imaging and blind source separation", Opt. Expr., vol. 18, pp.10762 -10774, 2010.
  10. J. Ruminski, M. Smiatacz, A. Bujnowski, A. Andrushevich, M. Biallas, R. Kistler, "Interactions with recognized patients using smart glasses," in Human System Interactions (HSI), 2015 8th International Conference on, pp.187-194, 25-27 June 2015
  11. K. Czuszynski, J. Ruminski, “Interaction with medical data using QR-codes”, in Human System Interactions (HSI), 2014 7th International Conference on, pp.182-187, 16-18 June 2014.
  12. A. Kwasniewska, J. Klimiuk-Myszk, J. Ruminski, J. Forrier, B. Martin, I. Pecci, "Quality of graphical markers for the needs of eyewear devices," in Human System Interactions (HSI), 2015 8th International Conference on , vol., no., pp.388-395, 25-27 June 2015.
  13. P. Przystup, A. Bujnowski, J. Ruminski, J. Wtorek, “A multisensor detector of a sleep apnea for using at home”, The 6th HSI Conference, IEEE Xplore, pp. 513-517, 2013.
  14. F. Zhao, M. Li, Y. Qian, J. Z. Tsien, “Remote Measurements of Heart and Respiration Rates for Telemedicine”, PLoS One. 2013; 8(10).
  15. M. Z. Poh, D. J. McDuff, P. W. Picard, “Advancements in noncontact, multiparameter physiological measurements using a webcam”. IEEE Trans Biomed Eng 58: 7–11, 2011.
  16. A. K. Abbas, K. Heimann, K. Jergus, T. Orlikowsky, S. Leonhardt, “Neonatal non-contact respiratory monitoring based on real-time infrared thermography”, BioMedical Engineering OnLine, vol. 10:93, BioMed Central, 2011.
  17. E. A. Bernal, L.K. Mestha, E. Shilla, "Non contact monitoring of respiratory function via depth sensing," in Biomedical and Health Informatics (BHI), 2014 IEEE-EMBS International Conference on, pp.101-104, 1-4 June 2014.
  18. R. Murthy, I. Pavlidis , “Non-contact monitoring of respiratory function using infrared imaging,” IEEE Engineering in Medicine and Biology Magazine. vol.25, pp.57-57, 2006.
  19. J. Ruminski, “Evaluation of the respiration rate and pattern using a portable thermal camera”, Proc. of the 13th Quantitative Infrared Thermography Conference, Gdansk 2016.
  20. A. Kwasniewska, J. Ruminski, „Real-time facial feature tracking in poor quality thermal imagery”, Proc. of the 9th International Conference on Human System Interaction, IEEE, eXplore, 2016.
  21. L. Sörnmo, P. Laguna, “Bioelectrical Signal Processing in Cardiac and Neurological Applications”, Academic Press, 2005.
  22. J. Ruminski, B. Bobek-Billewicz, “Parametric imaging in dynamic susceptibility contrast MRI-phantom and in vivo studies,” IEMBS'04. 26th Annual International Conference of the IEEE, pp. 1104-1107, 2004.