Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep

M. Migliorini, R. Cabiddu, S. Cerutti, L. T. Mainardi, Juha M. Kortelainen, A. M. Bianchi

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

3 Citations (Scopus)

Abstract

A high frequency of cardiac arrhythmias has been reported in sleep disordered patients. In order to detect the presence of arrhythmia during sleep, cardiac activity needs to be monitored. Several devices exist able to provide reliable Heart Rate Variability (HRV) measures in a minimally-intrusive way. Hence, there is the need for the development of robust methods for arrhythmia detection based on HRV measures. In the present study a method for automatic arrhythmia detection based on the analysis of an inter-beat series was developed and validated on recordings coming from the MIT-BIH Arrhythmia Database. The method was also applied on a beat to beat interval series obtained from the ballistocardiographic (BCG) signal of one subject, which was recorded during sleep using an innovative bed sensor which allowed for a noncontact and unobtrusive recording. When compared to the results of arrhythmia detection performed on the electrocardiographic (ECG) signal (concurrently acquired using polysomnography) using Cardioline Cube HOLTER analysis software, our method achieved a sensitivity of 55.6%, a specificity of 94.7% and an accuracy of 91.8%. Our results suggest that the bed sensor could represent a reliable tool to assist the clinician in arrhythmia detection. (13 refs.)
Original languageEnglish
Title of host publicationComputers in Cardiology CinC 2011
Subtitle of host publicationComputing in Cardiology 2011
Place of PublicationPiscataway, NJ, USA
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages337-340
Volume38
ISBN (Electronic)978-1-4577-0611-0
ISBN (Print)978-1-4577-0612-7
Publication statusPublished - 2011
MoE publication typeA4 Article in a conference publication
Event2011 Computing in Cardiology Conference, CinC 2011 - Hangzhou, China
Duration: 18 Sep 201121 Sep 2011

Conference

Conference2011 Computing in Cardiology Conference, CinC 2011
Abbreviated titleCinC 2011
CountryChina
CityHangzhou
Period18/09/1121/09/11

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Sensors
Sleep

Cite this

Migliorini, M., Cabiddu, R., Cerutti, S., Mainardi, L. T., Kortelainen, J. M., & Bianchi, A. M. (2011). Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep. In Computers in Cardiology CinC 2011: Computing in Cardiology 2011 (Vol. 38, pp. 337-340). Piscataway, NJ, USA: IEEE Institute of Electrical and Electronic Engineers .
Migliorini, M. ; Cabiddu, R. ; Cerutti, S. ; Mainardi, L. T. ; Kortelainen, Juha M. ; Bianchi, A. M. / Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep. Computers in Cardiology CinC 2011: Computing in Cardiology 2011. Vol. 38 Piscataway, NJ, USA : IEEE Institute of Electrical and Electronic Engineers , 2011. pp. 337-340
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title = "Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep",
abstract = "A high frequency of cardiac arrhythmias has been reported in sleep disordered patients. In order to detect the presence of arrhythmia during sleep, cardiac activity needs to be monitored. Several devices exist able to provide reliable Heart Rate Variability (HRV) measures in a minimally-intrusive way. Hence, there is the need for the development of robust methods for arrhythmia detection based on HRV measures. In the present study a method for automatic arrhythmia detection based on the analysis of an inter-beat series was developed and validated on recordings coming from the MIT-BIH Arrhythmia Database. The method was also applied on a beat to beat interval series obtained from the ballistocardiographic (BCG) signal of one subject, which was recorded during sleep using an innovative bed sensor which allowed for a noncontact and unobtrusive recording. When compared to the results of arrhythmia detection performed on the electrocardiographic (ECG) signal (concurrently acquired using polysomnography) using Cardioline Cube HOLTER analysis software, our method achieved a sensitivity of 55.6{\%}, a specificity of 94.7{\%} and an accuracy of 91.8{\%}. Our results suggest that the bed sensor could represent a reliable tool to assist the clinician in arrhythmia detection. (13 refs.)",
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Migliorini, M, Cabiddu, R, Cerutti, S, Mainardi, LT, Kortelainen, JM & Bianchi, AM 2011, Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep. in Computers in Cardiology CinC 2011: Computing in Cardiology 2011. vol. 38, IEEE Institute of Electrical and Electronic Engineers , Piscataway, NJ, USA, pp. 337-340, 2011 Computing in Cardiology Conference, CinC 2011, Hangzhou, China, 18/09/11.

Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep. / Migliorini, M.; Cabiddu, R.; Cerutti, S.; Mainardi, L. T.; Kortelainen, Juha M.; Bianchi, A. M.

Computers in Cardiology CinC 2011: Computing in Cardiology 2011. Vol. 38 Piscataway, NJ, USA : IEEE Institute of Electrical and Electronic Engineers , 2011. p. 337-340.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

TY - GEN

T1 - Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep

AU - Migliorini, M.

AU - Cabiddu, R.

AU - Cerutti, S.

AU - Mainardi, L. T.

AU - Kortelainen, Juha M.

AU - Bianchi, A. M.

PY - 2011

Y1 - 2011

N2 - A high frequency of cardiac arrhythmias has been reported in sleep disordered patients. In order to detect the presence of arrhythmia during sleep, cardiac activity needs to be monitored. Several devices exist able to provide reliable Heart Rate Variability (HRV) measures in a minimally-intrusive way. Hence, there is the need for the development of robust methods for arrhythmia detection based on HRV measures. In the present study a method for automatic arrhythmia detection based on the analysis of an inter-beat series was developed and validated on recordings coming from the MIT-BIH Arrhythmia Database. The method was also applied on a beat to beat interval series obtained from the ballistocardiographic (BCG) signal of one subject, which was recorded during sleep using an innovative bed sensor which allowed for a noncontact and unobtrusive recording. When compared to the results of arrhythmia detection performed on the electrocardiographic (ECG) signal (concurrently acquired using polysomnography) using Cardioline Cube HOLTER analysis software, our method achieved a sensitivity of 55.6%, a specificity of 94.7% and an accuracy of 91.8%. Our results suggest that the bed sensor could represent a reliable tool to assist the clinician in arrhythmia detection. (13 refs.)

AB - A high frequency of cardiac arrhythmias has been reported in sleep disordered patients. In order to detect the presence of arrhythmia during sleep, cardiac activity needs to be monitored. Several devices exist able to provide reliable Heart Rate Variability (HRV) measures in a minimally-intrusive way. Hence, there is the need for the development of robust methods for arrhythmia detection based on HRV measures. In the present study a method for automatic arrhythmia detection based on the analysis of an inter-beat series was developed and validated on recordings coming from the MIT-BIH Arrhythmia Database. The method was also applied on a beat to beat interval series obtained from the ballistocardiographic (BCG) signal of one subject, which was recorded during sleep using an innovative bed sensor which allowed for a noncontact and unobtrusive recording. When compared to the results of arrhythmia detection performed on the electrocardiographic (ECG) signal (concurrently acquired using polysomnography) using Cardioline Cube HOLTER analysis software, our method achieved a sensitivity of 55.6%, a specificity of 94.7% and an accuracy of 91.8%. Our results suggest that the bed sensor could represent a reliable tool to assist the clinician in arrhythmia detection. (13 refs.)

M3 - Conference article in proceedings

SN - 978-1-4577-0612-7

VL - 38

SP - 337

EP - 340

BT - Computers in Cardiology CinC 2011

PB - IEEE Institute of Electrical and Electronic Engineers

CY - Piscataway, NJ, USA

ER -

Migliorini M, Cabiddu R, Cerutti S, Mainardi LT, Kortelainen JM, Bianchi AM. Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep. In Computers in Cardiology CinC 2011: Computing in Cardiology 2011. Vol. 38. Piscataway, NJ, USA: IEEE Institute of Electrical and Electronic Engineers . 2011. p. 337-340