|dc.description.abstract||With the fast developments of industrial society, the living pressure of daily life is increasing. Besides, the inappropriate dietary habit also results in the increment of population with cardiovascular problems. In the investigation of top ten leading causes of death during the past five years, more than half of deaths were related to cardiovascular diseases, such as heat failure, brain vascular disease, diabetes, high blood pressure, and kidney-related diseases. It is worthy to notice that more than 30.3% in the death toll in Taiwan was caused by cardiovascular diseases (CVD), and it also caused 31% in global death. Therefore, how to discover vital signs or biomarkers for early detection of CVD in daily life is important issue.
Owing to the novel technologies in internet, smart phones, smart watch, and smart bands in recent years, the miniaturization of medical devices enable the coupling between wearable devices and medical instruments. It becomes a tremendous business market that causes interests of scientist and engineers to pursue. In this thesis, we develop a cross-platform heat-rate analysis program based on QT language. The developed program enables ECG signals measured by smart watch and ECG holter can be wirelessly transmitted to different display device (e.g., android pads, notebook, or desktops) which enables users can monitor their health condition in real time. The present system utilized temporal-frequency analysis to extract different features of heart rates, such as autonomous system regulation, ECG-derived respiration rate (EDR), heart-rate variability (HRV). Further development of the system can be used to estimate other pre-cursors for CVD not only for homecare applications but also for clinics.