TY - JOUR
T1 - Identification of S2 Paradoxical Splitting in Aortic Stenosis Subjects via Seismocardiogram Signals from a Wearable Accelerometer Contact Microphone
AU - Sang, Brian
AU - Shokouhmand, Arash
AU - Wen, Haoran
AU - Khan, Samiha
AU - Puma, Joseph A.
AU - Patel, Amisha
AU - Green, Philip
AU - Ebadi, Negar
AU - Ayazi, Farrokh
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2023/7/15
Y1 - 2023/7/15
N2 - 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.
AB - 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.
KW - Accelerometer contact microphone (ACM)
KW - aortic stenosis (AS)
KW - paradoxical splitting
KW - time-frequency representation
KW - wearable device
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U2 - 10.1109/JSEN.2023.3280407
DO - 10.1109/JSEN.2023.3280407
M3 - Article
AN - SCOPUS:85161504130
SN - 1530-437X
VL - 23
SP - 15424
EP - 15434
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 14
ER -