ECG-PPG device for real time detection of various cardiovascular diseases

Abstract

The mortality rate in men and women around the world is increasing every year due to Cardiovascular diseases (CVD). Patients having high probability of cardiac abnormalities have to get it identified as early as possible to treat the disease effectively. The physiological signals like ECG and PPG signals can be used for monitoring and detecting the cardiac abnormalities efficiently. In the proposed work, an ECG-PPG device extracts vital physiological signals from the human body and those signals are processed to detect arrhythmic abnormalities and estimate Blood Pressure (BP). The algorithm for processing the ECG signal extracts the feature points like R-peak, QRS complex, P-wave and T-wave and detects arrhythmic abnormalities. The accuracy of this algorithm depends upon how accurately it detects R-peak. The R-peak detection algorithm was tested with the arrhythmic ECG signals available on the MIT-BIH Arrhythmia Database with a extracting the time domain features from the signal with the help of R-peaks information from the ECG signal and estimating the BP. There are 4 different methods by which BP has been estimated and among them the least Root Mean Squared Error (RMSE) for Systolic Blood Pressure (SBP) is 13.18% and 9.98% for Diastolic Blood Pressure.