## 1 Introduction  
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]. However, 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]. Therefore, a variety of approaches to detect the early symptoms of cardiovascular disease based on physiological signal measurement technologies have been developed. A Holter monitor is one of the most popular professional ECG acquisition devices, featuring a dozen electrodes that attach to the surface of the user's chest and record ECG variation over a 24 h period. The recorded ECG data is expressed in raw data that can only be analyzed by medical staff and is thus not suitable for personal use. Health bands and smart watches with PPG sensors are also one possible solution to provide individual users with readings of their heart rates and SpO\({}_{2}\) measurement via wearable technology. The small size, light weight, and strong practicality of wearable technology makes it suitable for anyone to use throughout the day. However, the displayed heart rate and SpO\({}_{2}\) are calculated by sample data measured every 10 s, which introduces an error value due to incomplete data and computing processing. Furthermore, these data are measured from the wrist or fingers, not directly from the heart. Heart sounds are the most intuitive signal for observing the status of the cardiovascular system. A normal cardiac cycle comprises four main segments: the first heart sound (S1), the systole pause interval, the second heart sound (S2), and the diastole pause interval [6]. For heart-sound auscultation, the most common method is to use analog stethoscopes with a frequency range of 20 to 200 Hz and a \"bell\" that is placed on the chest [7,8]. The measured sounds pass through the connecting tube to the doctor's ears for heart auscultation. However, ambient noise and the doctor's level of experience affect the accuracy of the auscultation and can cause misdiagnoses. [PERSON] and [PERSON] conducted a study with 453 physicians and 88 medical students to investigate the accuracy of stethoscope use in detecting heart status abnormalities [9]. All participants listened to 12 cardiac events recorded directly from patients, followed by a multichoice questionnaire, and only 20% of the cardiac events were properly recognized. With the development of digital technologies, 3M (USA) and other medical-device companies have presented various smart stethoscopes utilizing digital acoustic sensors to record the heart sound into a phonocardiogram (PCG) for signal processing and visualization [10, 11, 12]. However, all commercial products focus solely on signal-processing methods to analyze heart sounds, which still suffer from lower accuracy and other limitations in the diagnosis of abnormal heart status. For a more objective method of analyzing heart sounds, multiple comparison methods for cardiovascular-system-related physiological signals have been used. [PERSON] et al. developed an ECG, PPG, PCG three-channel microcontroller unit (MCU) system for segmentation and characterization of the PCG signal [13]. The PCG cycle was computed along time and frequency domains using ECG and carotid pulse as references, but only the heart-murmur signal was able to be detected and classified, and the system itself was complex due to the three-channel signal measurement. Then, [PERSON] et al. demonstrated that the parameters of PPG variability (PPGV) are highly correlated with the parameters of heart-rate variability (HRV), and indicate that PPG could be used as an alternative measurement of HRV [14]. Following this, [PERSON] et al. presented a signal-processing method that can identify S1 and S2 heart sounds automatically by simultaneously recording, processing, and fusing the extracted fiducial points of the PCG and PPG signals [15,16].