Abstract
The widely used oximeter design was adopted and improved as the configuration mainframe in this study to acquire PPG signals. When users wear a finger probe and input their height, the device acquires PPG signals through the probe circuit, then filters and amplifies the signals to remove unnecessary noise, and uses an ARM-M4 to analyze the main peak, dicrotic wave, and wave valley of the PPG waveform to calculate related indexes for the final assessment. After 100 s, the HRV, sine wave ratio, and SI results are estimated, and a cardiovascular disease risk assessment is presented using a risk level from 0 to 5. This study uses the stiffness index (SI), sine wave ratio (SIN), and heart rate variability (HRV) to assess cardiovascular status. The SI is derived from PPG signal characteristics and reflects vascular stiffness based on blood flow rebound time. However, some PPG signals lack a dicrotic wave (sine waves), which is often caused by severe arterial stiffness. These waveforms lead to errors in SI calculation due to misidentification of the dicrotic wave. The appearance of a sine wave indicates that blood pulsation is abnormal; however, it will make the SI calculation algorithm produce a seemingly normal health performance. To address this, the auxiliary line method was introduced to identify sine waves, and the SIN ratio occurring in contiguous PPG waves was incorporated to calculate their proportion in PPG signals, aiding SI analysis and arterial stiffness evaluation. The total power (TP) value obtained via HRV frequency-domain analysis reflects autonomic nervous activity. As reduced autonomic function may relate to cardiovascular diseases, TP is included as an evaluation indicator. By analyzing PPG signals, calculating SI and SIN, and integrating the HRV indicator, this study evaluates arterial stiffness and cardiovascular health, helping participants understand their physical condition more quickly and conveniently, and potentially preventing cardiovascular diseases at an early stage.