Detection of Left Ventricular Ejection Fraction Abnormality Using Fusion of Acoustic and Biopotential Characteristics of Precordium

• Main Authors: Shokouhmand, Arash, Wen, Haoran, Khan, Samiha, Puma, Joseph A., Patel, Amisha, Green, Philip, Ayazi, Farrokh, Tavassolian, Negar
• Format: Conference Proceeding
• Language: English
• Subjects: accelerometer contact microphone; Echocardiography; electrocardiogram; Electrocardiography; Heart; Heart beat; left ventricular ejection fraction (LVEF); left ventricular ejection time (LVET); pre-ejection period; Recording; Science - general; US Government; wearable sensors
• ISSN: 2168-9229
• DOI: 10.1109/SENSORS52175.2022.9967355

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%.