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Issue No.04 - Oct.-Dec. (2012 vol.11)
pp: 28-34
Johannes Schumm , ETH Zurich
Bert Arnrich , ETH Zurich
Gerhard Tröster , ETH Zurich
ABSTRACT
A contactless electrocardiogram (ECG) system in an airplane seat aims to monitor the well-being of passengers afraid to fly, but passenger movements can disturb the signal. The authors discuss how passenger activity influences ECG signals and present a novel method for automatically appraising signal quality.
INDEX TERMS
Electrocardiography, Medical services, Sensor systems and applications, Biomedical telemetry, Biosensors, Biomedical monitoring, Data mining, Cardiovascular system, sensors, J.3 Life and Medical Sciences, J.3.b Health, data mining, pervasive computing, C.2.2.a ECG, healthcare, pervasive computing
CITATION
Johannes Schumm, Bert Arnrich, Gerhard Tröster, "ECG Monitoring in an Airplane Seat: Appraising the Signal Quality", IEEE Pervasive Computing, vol.11, no. 4, pp. 28-34, Oct.-Dec. 2012, doi:10.1109/MPRV.2011.40
REFERENCES
1. L.N. Smith, “An Otolaryngologist's Experience with In-Flight Commercial Airline Medical Emergencies: Three Case Reports and Literature Review,” Am. J. Otolaryngology-Head and Neck Medicine and Surgery, vol. 29, no. 5, 2008, pp. 346–351.
2. L.J. Van Gerwen et al., “Multicomponent Standardized Treatment Programs for Fear of Flying: Description and Effectiveness,” Cognitive and Behavioral Practice, vol. 9, no. 2, 2002, pp. 138–149.
3. M. Steffen, A. Aleksandrowicz, and S. Leonhardt, “Mobile Noncontact Monitoring of Heart and Lung Activity,” IEEE Trans. Biomedical Circuits and Systems, vol. 1, no. 4, 2007, pp. 250–257.
4. J. Schumm et al., “Unobtrusive Physiological Monitoring in an Airplane Seat,” Personal and Ubiquitous Computing, vol. 14, no. 6, 2010, pp. 541–550.
5. O. Such and J. Muehlsteff, “On-Body Sensors for Personal Healthcare,” Advances in Healthcare Technology: Shaping the Future of Medical Care, Springer, 2006, pp. 463–488.
6. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods, Cambridge Univ. Press, 2000.
7. J.A. Healey and R.W. Picard, “Detecting Stress During Real-World Driving Tasks Using Physiological Sensors,” IEEE Trans. Intelligent Transportation, vol. 6, no. 2, 2005, pp. 156–166.
8. P.S. Hamilton, “Open Source ECG Analysis Software Documentation,” EP Limited, 2002; www.eplimited.comosea13.pdf.
9. “Testing and Reporting Performance Results of Cardiac Rhythm and ST Segment Measurement Algorithms,” Am. Nat'l Standards Inst. and the Assoc. for the Advancement of Medical Instrumentation, AAMI EC 57, 1998; http://marketplace.aami.org/eseries/scriptcontent/ docs/Preview%20FilesEC570404preview.pdf .
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