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Combining the Information of Unconstrained Electrocardiography and Ballistography in the Detection of Night-Time Heart Rate and Respiration Rate

Combining the Information of Unconstrained Electrocardiography and Ballistography in the Detection of Night-Time Heart Rate and Respiration Rate

Antti Vehkaoja, Mikko Peltokangas, Jarmo Verho, Jukka Lekkala
Copyright: © 2013 |Volume: 1 |Issue: 3 |Pages: 16
ISSN: 2166-7241|EISSN: 2166-725X|EISBN13: 9781466634640|DOI: 10.4018/ijmstr.2013070104
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MLA

Vehkaoja, Antti, et al. "Combining the Information of Unconstrained Electrocardiography and Ballistography in the Detection of Night-Time Heart Rate and Respiration Rate." IJMSTR vol.1, no.3 2013: pp.52-67. http://doi.org/10.4018/ijmstr.2013070104

APA

Vehkaoja, A., Peltokangas, M., Verho, J., & Lekkala, J. (2013). Combining the Information of Unconstrained Electrocardiography and Ballistography in the Detection of Night-Time Heart Rate and Respiration Rate. International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), 1(3), 52-67. http://doi.org/10.4018/ijmstr.2013070104

Chicago

Vehkaoja, Antti, et al. "Combining the Information of Unconstrained Electrocardiography and Ballistography in the Detection of Night-Time Heart Rate and Respiration Rate," International Journal of Monitoring and Surveillance Technologies Research (IJMSTR) 1, no.3: 52-67. http://doi.org/10.4018/ijmstr.2013070104

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Abstract

An unobtrusive bed integrated system for monitoring physiological parameters during sleep is presented and evaluated. The system uses textile electrodes attached to a bed sheet for measuring multiple channels of electrocardiogram. The channels are also combined in order to form several additional ECG leads. One lead at a time is selected for beat-to-beat-interval detection. The system also includes force sensors located under a bed post for detecting respiration and movements. The movement information is also used to assist in heart rate detection and combining the ECG derived respiration information with respiration information derived from force sensors, is investigated. The authors tested the system with ten subjects in one hour recordings and achieved an average of 95.9% detection coverage and 99 percentile absolute error of 3.47 ms for the BB-interval signal. The relative mean absolute error of the detected respiration cycle lengths was 2.1%.

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