Identification of S2 Paradoxical Splitting in Aortic Stenosis Subjects via Seismocardiogram Signals from a Wearable Accelerometer Contact Microphone

Brian Sang, Arash Shokouhmand, Haoran Wen, Samiha Khan, Joseph A. Puma, Amisha Patel, Philip Green, Negar Ebadi, Farrokh Ayazi

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Second heart sound (S2) splitting can be used as an indicator for the diagnosis of cardiovascular diseases; specifically, paradoxical S2 splitting is an indicator of aortic stenosis (AS). We present that S2 acoustic signatures can be captured accurately from the seismocardiogram (SCG) signals of a sensitive wearable accelerometer contact microphone (ACM) and validated by comparing with digital stethoscope phonocardiogram (PCG) signals. The ACM was placed on the pulmonic region of 18 subjects, ten with no known heart disease and eight with known heart disease, for 60 s of SCG data collection. Smoothed pseudo Wigner-Ville distribution is used to extract S2 time split and to identify S2 paradoxical splitting. Healthy subjects had SCG S2 time splits range agreeing with S2 time splits from the past literature from PCG signals. The ACM SCG signal was also used to identify and capture paradoxical splitting from subjects with known valvular heart diseases such as AS, from subjects with mild to severe diagnosis. In conclusion, a wearable ACM can be used to detect paradoxical splitting in subjects suspected with aortic valvular heart disease and shows high fidelity of capturing S2 time split through SCG signals.

Original languageEnglish
Pages (from-to)15424-15434
Number of pages11
JournalIEEE Sensors Journal
Volume23
Issue number14
DOIs
StatePublished - 15 Jul 2023

Keywords

  • Accelerometer contact microphone (ACM)
  • aortic stenosis (AS)
  • paradoxical splitting
  • time-frequency representation
  • wearable device

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