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Unobtrusive physiological monitoring in an airplane seat

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Abstract

Air travel has become the preferred mode of long-distance transportation for most of the world’s travelers. People of every age group and health status are traveling by airplane and thus the airplane has become part of our environment, in which people with health-related limitations need assistive support. Since the main interaction point between a passenger and the airplane is the seat, this work presents a smart airplane seat for measuring health-related signals of a passenger. We describe the design, implementation and testing of a multimodal sensor system integrated into the seat. The presented system is able to measure physiological signals, such as electrocardiogram, electrodermal activity, skin temperature, and respiration. We show how the design of the smart seat system is influenced by the trade-off between comfort and signal quality, i.e. incorporating unobtrusive sensors and dealing with erroneous signals. Artifact detection through sensor fusion is presented and the working principle is shown with a feasibility study, in which normal passenger activities were performed. Based on the presented method, we are able to identify signal regions in which the accuracies for detecting the heart- and respiration-rate are 88 and 82%, respectively, compared to 40 and 76% without any artifact removal.

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References

  1. Smith LN (2008) An otolaryngologist’s experience with in-flight commercial airline medical emergencies: three case reports and literature review. Am J Otolaryngol Head Neck Med Surg 29(5):346–351

    Google Scholar 

  2. Drummond R, Drummond AJ (2002) On a wing and a prayer: medical emergencies on board commercial aircraft. Can J Emerg Med 4(4):276–280

    Google Scholar 

  3. Goodwin T (2000) In-flight medical emergencies: an overview. Br Med J 321(7272):1338–1341

    Article  Google Scholar 

  4. Liu H, Salem B, Rauterberg M (2008) Adaptive user preference modeling and its application to in-flight entertainment. In: Proceedings of the 3rd international conference on digital interactive media in entertainment and arts. ACM, New York, pp 289–294

  5. Such O, Muehlsteff J, Pinter R, Aubert X, Falck T, Elixmann M et al (2006) On-body sensors for personal healthcare. Advances in Healthcare Technology, pp 463–488

  6. Such O, Muehlsteff J (2006) The challenge of motion artifact suppression in wearable monitoring solutions. 3rd IEEE/EMBS international summer school on medical devices and biosensors, pp 49–52

  7. Healey J, Picard R (2005) Detecting stress during real-world driving tasks using physiological sensors. IEEE Trans Intell Transp Syst 6(2):156–166

    Article  Google Scholar 

  8. Kapoor A, Burleson W, Picard RW (2007) Automatic prediction of frustration. Int J Human Comp Stud 65(8):724–736

    Article  Google Scholar 

  9. Lim YG, Kim KK, Park S (2006) ECG measurement on a chair without conductive contact. IEEE Trans Biomed Eng 53(5):956–959

    Article  Google Scholar 

  10. Steffen M, Aleksandrowicz A, Leonhardt S (2007) Mobile noncontact monitoring of heart and lung activity. IEEE Trans Biomed Circ Syst 1(4):250–257

    Article  Google Scholar 

  11. Zakrzewski M, Kolinummi A, Vanhala J (2006) Contactless and unobtrusive measurement of heart rate in home environment. In: Engineering in Medicine and Biology Society, 2006. EMBS’06. 28th annual international conference of the IEEE, pp 2060–2063

  12. Suzuki S, Matsui T, Imuta H, Uenoyama M, Yura H, Ishihara M et al (2008) A novel autonomic activation measurement method for stress monitoring: non-contact measurement of heart rate variability using a compact microwave radar. Med Biol Eng Comput Med Biol Eng Comput 46(7):709–714

    Google Scholar 

  13. Junnila S, Akhbardeh A, Varri A, Koivistoinen T (2005) An EMFi-film sensor based ballistocardiographic chair: performance and cycle extraction method. In: IEEE workshop on signal processing systems design and implementation, pp 373–377

  14. Anttonen J, Surakka V (2005) Emotions and heart rate while sitting on a chair. In: Conference on human factors in computing systems: proceedings of the SIGCHI conference on human factors in computing systems, vol 2, pp 491–499

  15. Gibbs P, Asada H (2005) Reducing motion artifact in wearable bio-sensors using MEMS accelerometers for active noise cancellation. In: Proceedings of the 2005 American control conference, pp 1581–1586

  16. Han H, Kim MJ, Kim J (2007) Development of real-time motion artifact reduction algorithm for a wearable photoplethysmography. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th annual international conference of the IEEE, pp 1538–1541

  17. Asada H, Jiang HH, Gibbs P (2004) Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors, vol 1

  18. Schumm J, Bächlin M, Setz C, Arnrich B, Roggen D, Tröster G (2008) Effect of movements on the electrodermal response after a startle event. Methods Inform Med 47(3):186

    Google Scholar 

  19. Zhai J, Barreto A (2006) Stress detection in computer users based on digital signal processing of noninvasive physiological variables. In: Engineering in Medicine and Biology Society, 2006. EMBS’06. 28th annual international conference of the IEEE

  20. Crosby ME, Auernheimer B, Aschwanden C, Ikehara C (2001) Physiological data feedback for application in distance education. In: Proceedings of the 2001 workshop on perceptive user interfaces. ACM, New York, pp 1–5

  21. Picard RW, Vyzas E, Healey J (2001) Toward machine emotional intelligence: analysis of affective physiological state. In: Proceedings of IEEE Transactions on pattern analysis and machine intelligence, pp 1175–1191

  22. Chan M, Estève D, Escriba C, Campo E (2008) A review of smart homes—present state and future challenges. Comp Methods Prog Biomed 91(1):55–81

    Article  Google Scholar 

  23. Leonhardt S, Aleksandrowicz A, Steffen M (2006) Magnetic and capacitive monitoring of heart and lung activity as an example for personal healthcare. In: Proceedings of 3rd IEEE/EMBS international summer school on medical devices and biosensors, pp 57–60

  24. Boucsein W (1992) Electrodermal activity. Plenum Press, New York

    Google Scholar 

  25. Piacentini R (2004) Emotions at fingertips, “Revealing individual features in galvanic skin response signals”. Universit degli studi di Roma “La Sapienza”

  26. Mattmann C, Amft O, Harms H, Tröster G, Clemens F (2007) Recognizing upper body postures using textile strain sensors. In: 11th IEEE international symposium on wearable computers, pp 1–8

  27. Arlington VANS (1998) Testing and reporting performance results of cardiac rhythm and ST segment measurement algorithms. ANSI-AAMI EC57:1998

  28. Hamilton PS, Tompkins WJ (1986) Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. EEE Trans Biomed Eng 33(12):1157–1165

    Google Scholar 

  29. Dokhan B, Setz C, Arnrich B, Tröster G (2007) Monitoring passenger’s breathing—a feasibility study. In: Swiss Society of Biomedical Engineering Annual Meeting. Neuchâtel, Switzerland

  30. European SEAT-Project (Nr: 030958) (2006) Deliverable D5.1: IFE and comfort in aircraft cabin—state of the art

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Acknowledgments

This project is funded by the EU research project SEAT (http://www.seat-project.org), contract number: 030958, all views here reflect the author’s opinion and not that of the commission. The authors would like to thank Urs Egger who supported the technical part of this project.

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Authors and Affiliations

  1. Electronics Laboratory, ETH Zurich, Gloriastrasse 35, Zurich, Switzerland

    Johannes Schumm, Cornelia Setz, Marc Bächlin, Marcel Bächler, Bert Arnrich & Gerhard Tröster

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  1. Johannes Schumm
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  2. Cornelia Setz
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  3. Marc Bächlin
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  4. Marcel Bächler
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  5. Bert Arnrich
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  6. Gerhard Tröster
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Correspondence to Johannes Schumm.

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Schumm, J., Setz, C., Bächlin, M. et al. Unobtrusive physiological monitoring in an airplane seat. Pers Ubiquit Comput 14, 541–550 (2010). https://doi.org/10.1007/s00779-009-0272-1

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  • DOI: https://doi.org/10.1007/s00779-009-0272-1

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