Abstract
Cardiac auscultation is one of the most popular diagnosis approaches to determine cardiovascular status based on listening to heart sounds with a stethoscope. However, heart sounds can be masked by visceral sounds such as organ movement and breathing, and a doctor’s level of experience can more seriously affect the accuracy of auscultation results. To improve the accuracy of auscultation, and to allow nonmedical staff to conduct cardiac auscultation anywhere and anytime, a hybrid-type personal smart stethoscope with an automatic heart sound analysis function is presented in this paper. The device was designed with a folding finger-ring shape that can be worn on the finger and placed on the chest to measure photoplethysmogram (PPG) signals and acquire the heart sound simultaneously. The measured heart sounds are detected as phonocardiogram (PCG) signals, and the boundaries of the heart sound variation and the peaks of the PPG signal are detected in preprocessing by an advanced Shannon entropy envelope. According to the relationship between PCG and PPG signals, an automatic heart sound analysis algorithm based on calculating the time interval between the first and second heart sounds (S1, S2) and the peak of the PPG was developed and implemented via the manufactured prototype device. The prototype device underwent accuracy and usability testing with 20 young adults, and the experimental results showed that the proposed smart stethoscope could satisfactorily collect the heart sounds and PPG signals. In addition, within the developed algorithm, the device was as accurate in start-points of heart sound detection as professional physiological signal-acquisition systems. Furthermore, the experimental results demonstrated that the device was able to identify S1 and S2 heart sounds automatically with high accuracy.
Highlights
IntroductionAccording to a World Health Organization (WHO) report, cardiovascular disease is the leading cause of death worldwide, responsible for 8.9 million deaths in 2019 [1]
According to a World Health Organization (WHO) report, cardiovascular disease is the leading cause of death worldwide, responsible for 8.9 million deaths in 2019 [1].a portion of these deaths could be prevented through early diagnoses based on monitoring cardiovascular-related physiological signals such as heart sound, heart rate, electrocardiogram (ECG) readings, and blood pressure [2,3,4,5]
Because the PCG signal was processed with digital data directly and preprocessed to suppress environment noise and S3 and S4 heart sounds in the prototype device, S1 and S2 heart sounds were more promi
Summary
According to a World Health Organization (WHO) report, cardiovascular disease is the leading cause of death worldwide, responsible for 8.9 million deaths in 2019 [1]. A portion of these deaths could be prevented through early diagnoses based on monitoring cardiovascular-related physiological signals such as heart sound, heart rate, electrocardiogram (ECG) readings, and blood pressure [2,3,4,5]. A variety of approaches to detect the early symptoms of cardiovascular disease based on physiological signal measurement technologies have been developed. Health bands and smart watches with PPG sensors are one possible solution to provide individual users with readings of their heart rates and
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