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Estimation of Splitting Interval in Second Heart Sound by Optimizing a Demixing Vector

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

Abstract

A non-invasive method to estimate the splitting interval (SI) of the second heart sound (S2) was developed and evaluated. Recently, there has been a growing need for a non-invasive SI estimation for the early detection of cardiovascular diseases. Therefore, we proposed an SI estimation algorithm by separating the aortic and pulmonary components (A2 and P2, respectively) from S2 with an optimized demixing vector and mathematical model of S2. Herein, we evaluated the SI estimation performance of our algorithm. As a result, our algorithm could determine a simulated S2's SI with an error of $1.3+1.0$ ms. A2 and P2 were separated from recorded human S2 signals. The resulting SI estimation of the recorded data showed a correlation coefficient with S2-S2 intervals of $r=- 0.67$. This negative correlation is consistent with reported physiological features of the heart.

Original languageEnglish
Title of host publication2023 IEEE SENSORS, SENSORS 2023 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350303872
DOIs
StatePublished - 2023
Event2023 IEEE SENSORS, SENSORS 2023 - Vienna, Austria
Duration: Oct 29 2023Nov 1 2023

Publication series

NameProceedings of IEEE Sensors

Conference

Conference2023 IEEE SENSORS, SENSORS 2023
Country/TerritoryAustria
CityVienna
Period10/29/2311/1/23

Keywords

  • demixing vector
  • microphone array
  • sensor signal processing
  • splitting of second heart sound

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