Detection of Left Ventricular Ejection Fraction Abnormality Using Fusion of Acoustic and Biopotential Characteristics of Precordium
- Resource Type
- Conference
- Authors
- Shokouhmand, Arash; Wen, Haoran; Khan, Samiha; Puma, Joseph A.; Patel, Amisha; Green, Philip; Ayazi, Farrokh; Tavassolian, Negar
- Source
- 2022 IEEE Sensors Sensors, 2022 IEEE. :1-4 Oct, 2022
- Subject
- Engineering Profession
General Topics for Engineers
Heart
Science - general
Heart beat
Echocardiography
US Government
Electrocardiography
Recording
left ventricular ejection fraction (LVEF)
wearable sensors
accelerometer contact microphone
electrocardiogram
pre-ejection period
left ventricular ejection time (LVET)
- Language
- ISSN
- 2168-9229
This study develops a wearable monitoring platform for the detection of abnormal left ventricular ejection fraction (LVEF) using a fusion of an accelerometer contact microphone (ACM) and an electrocardiogram (ECG) sensor. Two signal processing chains are designed to annotate ACM and ECG recordings. Afterwards, the pre-ejection period (PEP) and left ventricular ejection time (LVET) are estimated as the time difference between the first heart sound (S 1 ) and the R-peak in ECG signals, and the time difference between the first and second heart sounds (S 1 and S 2 ), respectively. The ratio of PEP to LVET is then utilized to differentiate between healthy and abnormal-LVEF groups. The model is evaluated on 15 subjects (8 healthy subjects and 7 subjects with LVEF abnormality) where the ground truth values are the LVEF parameter acquired by the echocardiography machine. An average (± standard deviation) accuracy of 84.47% (± 17.58%) is obtained for the detection of LVEF abnormality for a total of 5989 heartbeats. It is demonstrated that the proposed method is capable of LVEF abnormality detection with accuracies within the range of 54.35% - 100%.