Robust arterial blood pressure onset detection method from signal artifacts

Seung Bo Lee, Eun Suk Song, Hakseung Kim, Dong Ju Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Arterial blood pressure (ABP) is used in various areas such as brain computer interface and clinical field. The morphological analysis of the ABP signal allows researchers to identify important information such as cardiovascular system and psychopathology. Detection of onset, which is the most important landmark in the ABP waveform, is essential for morphology analysis of ABP. Since the physiological signal is vulnerable to the risk of contamination, the robust onset detection method is needed. This study proposed a pulse onset detection method based on Monte Carlo approach that is robust from artifacts. The 10 cases of ABP signals were analyzed to detect signal onset. When we assessed the time difference from the actual onset, there was an average error of 2.4μs. The results suggested that the proposed method could achieve robustness in pulse detection and facilitated pulse wave analysis using clinical recordings with various artifacts.

Original languageEnglish
Title of host publication2018 6th International Conference on Brain-Computer Interface, BCI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-3
Number of pages3
Volume2018-January
ISBN (Electronic)9781538625743
DOIs
Publication statusPublished - 2018 Mar 9
Event6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of
Duration: 2018 Jan 152018 Jan 17

Other

Other6th International Conference on Brain-Computer Interface, BCI 2018
CountryKorea, Republic of
CityGangWon
Period18/1/1518/1/17

Fingerprint

Blood pressure
Artifacts
Arterial Pressure
Pulse
Brain-Computer Interfaces
Cardiovascular system
Pulse Wave Analysis
Brain computer interface
Cardiovascular System
Psychopathology
Contamination
Research Personnel
Psychological Signal Detection

Keywords

  • arterial blood pressure
  • artifact
  • component
  • onset detection
  • systolic peak

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Behavioral Neuroscience

Cite this

Lee, S. B., Song, E. S., Kim, H., & Kim, D. J. (2018). Robust arterial blood pressure onset detection method from signal artifacts. In 2018 6th International Conference on Brain-Computer Interface, BCI 2018 (Vol. 2018-January, pp. 1-3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2018.8311518

Robust arterial blood pressure onset detection method from signal artifacts. / Lee, Seung Bo; Song, Eun Suk; Kim, Hakseung; Kim, Dong Ju.

2018 6th International Conference on Brain-Computer Interface, BCI 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-3.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, SB, Song, ES, Kim, H & Kim, DJ 2018, Robust arterial blood pressure onset detection method from signal artifacts. in 2018 6th International Conference on Brain-Computer Interface, BCI 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-3, 6th International Conference on Brain-Computer Interface, BCI 2018, GangWon, Korea, Republic of, 18/1/15. https://doi.org/10.1109/IWW-BCI.2018.8311518
Lee SB, Song ES, Kim H, Kim DJ. Robust arterial blood pressure onset detection method from signal artifacts. In 2018 6th International Conference on Brain-Computer Interface, BCI 2018. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-3 https://doi.org/10.1109/IWW-BCI.2018.8311518
Lee, Seung Bo ; Song, Eun Suk ; Kim, Hakseung ; Kim, Dong Ju. / Robust arterial blood pressure onset detection method from signal artifacts. 2018 6th International Conference on Brain-Computer Interface, BCI 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-3
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