Validation of algorithm with noise tolerance methods to detect R-wave

Won Kyu Lee, Hong Ji Lee, Jeong Su Lee, Hee Nam Yoon, Soo Young Sim, Yong Gyu Lim, Kwangsuk Park

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

Abstract

Long-term monitoring of electrocardiogram (ECG) is one of the basic measurement in healthcare and provides decisive information regarding cardiovascular system status. In all ECG applications, the R-wave detection is important. However, it is difficult to detect R-wave automatically because signals obtained in daily life frequently include noise from various sources. Daily life monitoring ECG signal is particularly measured over cloth during walking and sleeping states by using non-invasive sensor, so that it usually presents higher noise level. To improve detection accuracy under noisy condition, we developed algorithm which has some noise tolerance techniques that analyze characteristics of R-wave. The proposed algorithm was evaluated by using the records of the MIT-BIH Polysomnographic database and the data from nonintrusive vital sign monitoring system previously developed in our laboratory. Algorithm reliability was assessed by detection error rate (De), sensitivity (Se) and positive predictivity (P+). The result shows average De of 2.62%, average Se of 98.29% and average P++ of 99.03%. We suggest that our R-wave detection method is useful in the presence of noisy signals.

Original languageEnglish
Title of host publicationThe 15th International Conference on Biomedical Engineering, ICBME 2013
EditorsJames Goh
PublisherSpringer Verlag
Pages539-542
Number of pages4
Volume43
ISBN (Electronic)9783319029122
DOIs
StatePublished - 1 Jan 2014
Event15th International Conference on Biomedical Engineering, ICBME 2013 - Singapore, Singapore
Duration: 4 Dec 20137 Dec 2013

Other

Other15th International Conference on Biomedical Engineering, ICBME 2013
CountrySingapore
CitySingapore
Period4/12/137/12/13

Fingerprint

Electrocardiography
Error detection
Monitoring
Cardiovascular system
Sensors

Keywords

  • Electrocardiogram (ECG)
  • Noise tolerance
  • Peak detection algorithm
  • Physiological monitoring in daily life

Cite this

Lee, W. K., Lee, H. J., Lee, J. S., Yoon, H. N., Sim, S. Y., Lim, Y. G., & Park, K. (2014). Validation of algorithm with noise tolerance methods to detect R-wave. In J. Goh (Ed.), The 15th International Conference on Biomedical Engineering, ICBME 2013 (Vol. 43, pp. 539-542). Springer Verlag. https://doi.org/10.1007/978-3-319-02913-9_137
Lee, Won Kyu ; Lee, Hong Ji ; Lee, Jeong Su ; Yoon, Hee Nam ; Sim, Soo Young ; Lim, Yong Gyu ; Park, Kwangsuk. / Validation of algorithm with noise tolerance methods to detect R-wave. The 15th International Conference on Biomedical Engineering, ICBME 2013. editor / James Goh. Vol. 43 Springer Verlag, 2014. pp. 539-542
@inproceedings{3b21f6c83d4c414bbb96387d83c2e363,
title = "Validation of algorithm with noise tolerance methods to detect R-wave",
abstract = "Long-term monitoring of electrocardiogram (ECG) is one of the basic measurement in healthcare and provides decisive information regarding cardiovascular system status. In all ECG applications, the R-wave detection is important. However, it is difficult to detect R-wave automatically because signals obtained in daily life frequently include noise from various sources. Daily life monitoring ECG signal is particularly measured over cloth during walking and sleeping states by using non-invasive sensor, so that it usually presents higher noise level. To improve detection accuracy under noisy condition, we developed algorithm which has some noise tolerance techniques that analyze characteristics of R-wave. The proposed algorithm was evaluated by using the records of the MIT-BIH Polysomnographic database and the data from nonintrusive vital sign monitoring system previously developed in our laboratory. Algorithm reliability was assessed by detection error rate (De), sensitivity (Se) and positive predictivity (P+). The result shows average De of 2.62{\%}, average Se of 98.29{\%} and average P++ of 99.03{\%}. We suggest that our R-wave detection method is useful in the presence of noisy signals.",
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Lee, WK, Lee, HJ, Lee, JS, Yoon, HN, Sim, SY, Lim, YG & Park, K 2014, Validation of algorithm with noise tolerance methods to detect R-wave. in J Goh (ed.), The 15th International Conference on Biomedical Engineering, ICBME 2013. vol. 43, Springer Verlag, pp. 539-542, 15th International Conference on Biomedical Engineering, ICBME 2013, Singapore, Singapore, 4/12/13. https://doi.org/10.1007/978-3-319-02913-9_137

Validation of algorithm with noise tolerance methods to detect R-wave. / Lee, Won Kyu; Lee, Hong Ji; Lee, Jeong Su; Yoon, Hee Nam; Sim, Soo Young; Lim, Yong Gyu; Park, Kwangsuk.

The 15th International Conference on Biomedical Engineering, ICBME 2013. ed. / James Goh. Vol. 43 Springer Verlag, 2014. p. 539-542.

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

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Lee WK, Lee HJ, Lee JS, Yoon HN, Sim SY, Lim YG et al. Validation of algorithm with noise tolerance methods to detect R-wave. In Goh J, editor, The 15th International Conference on Biomedical Engineering, ICBME 2013. Vol. 43. Springer Verlag. 2014. p. 539-542 https://doi.org/10.1007/978-3-319-02913-9_137