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Cardiac arrhythmia alarm from optical interferometric signals during resting or sleeping for early intervention

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Diagnostics of cardiac arrhythmias and frequent interventions may contribute to early detection of diseases or even prevent sudden death. Generally electrocardiograph with several on body electrodes at outpatient clinic is applied and the procedure requires a medical expert. We propose cardiac arrhythmia estimation on the basis of heartbeat detection with optical fibers integrated in the bedding. The modified Michelson's interferometer with error detection was used to measure and maximum a-posteriori probability was used to estimate the beat-to-beat intervals. The consistency of heartbeat intervals was examined with simultaneous measurement with clinical electrocardiograph in 10 healthy volunteers and 10 patients with diagnosed heart arrhythmias. Heart beat interval data obtained in patients were examined and irregularities/arrhythmias were identified from the medical guidelines. The current system enables assessment also in home environment without any on-body sensor placement or required assistance. Thus early intervention is possible as the irregularities are submitted to the nurse on duty and stored in the database for subsequent more detailed analysis.
Twórcy
autor
  • University Rehabilitation Institute, Republic of Slovenia, Linhartova 51, Ljubljana, Slovenia
autor
  • University of Ljubljana, Faculty of Computer Sciences, Ljubljana, Slovenia
autor
  • University Rehabilitation Institute, Republic of Slovenia, Ljubljana, Slovenia
autor
  • University of Maribor, Faculty of Electrical Engineering and Computer Sciences, Maribor, Slovenia
Bibliografia
  • [1] Watanabe K, Watanabe T, Watanabe H, Ando H, Ishikawa T, Kobayashi K. Noninvasive measurement of heartbeat, respiration, snoring and body movements of a subject in bed via a pneumatic method. IEEE Trans Bio-Med Eng 2005;52(12):2100–7. http://dx.doi.org/10.1109/TBME.2005.857637.
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  • [4] Shin JH, Hwang SH, Chang MH, Park KS. Heart rate variability analysis using a ballistocardiogram during Valsalva manoeuvre and post exercise. Physiol Meas 2011;32(8):1239–64.
  • [5] Mikhelson IV, Bakhtiari S, Elmer TW, Sahakian AV. Remote sensing of heart rate and patterns of respiration on a stationary subject using 94-GHz millimeter-wave interferometry. IEEE Trans Bio-Med Eng 2011;58(6):1671–7. http://dx.doi.org/10.1109/TBME.2011.2111371.
  • [6] Quiceno-Manrique AF, Godino-Llorente JI, Blanco-Velasco M, Castellanos-Dominguez G. Selection of dynamic features based on time-frequency representations for heart murmur detection from phonocardiographic signals. Ann Biomed Eng 2010;38(1):118–37. http://dx.doi.org/10.1007/s10439-009-9838-3.
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  • [8] Šprager S, Zazula D. Detection of heartbeat and respiration from optical interferometric signal by using wavelet transform. Comput Methods Programs Biomed 2013;111 (1):41–51. http://dx.doi.org/10.1016/j.cmpb.2013.03.003.
  • [9] Šprager S, Zazula D. Heartbeat and respiration detection from optical interferometric signals by using a multimethod approach. IEEE Trans Bio-Med Eng 2012;59 (10):2922–9. http://dx.doi.org/10.1109/TBME.2012.2213302.
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  • [14] Migliorini M, Cabiddu R, Cerutti S, Mainardi L, Kortelainen J, Bianchi A. Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep; 2011.
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  • [16] Pirš C, Cigale B, Zazula D, Usar D. System architecture of unobtrusive sensors for supporting home care and independent living. In: Long CA, Mastorakis NE, Mladenov V, editors. Proceedings of the SCSI 2013. Recent advances in electrical engineering series, vol. 16. European Society for Environmental Research and Sustainable Development; 2013. p. 434–9.
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  • [22] Šprager S, Zazula D. Optimization of heartbeat detection in fiber-optic unobtrusive measurements by using maximum a posteriori probability estimation. IEEE J Biomed Health Inform 2014;18(4):1161–8. http://dx.doi.org/10.1109/JBHI.2013.2282403.
  • [23] Kortelainen JM, Mendez MO, Bianchi AM, Matteucci M, Cerutti S. Sleep staging based on signals acquired through bed sensor. IEEE Trans Inf Technol Biomed: Publ IEEE Eng Med Biol Soc 2010;14(3):776–85. http://dx.doi.org/10.1109/TITB.2010.2044797.
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-96aac2ab-7ddc-46fe-ade1-f96881c644c5
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