Heart Rate Variability for Predicting Coronary Heart Disease using Photoplethysmography

Today, Coronary heart diseases (CHD) are discovered to be one of the main sources of death around the world. In that context, doctors and wellbeing experts urge on early identification and diagnosis of likely manifestations to guarantee the equivocation of an all-out heart-related illness. Photoplethysmography (PPG) is a discrete, ocular method that screens the peripheral blood vessels at various locations and identifies the fluctuations in blood volume. It is a most requisite technique as it can be embedded into wearable devices unlike ECG and other traditional techniques it helps us keep track of health through this method is beneficial for continuous monitoring and recording of BPM the major hurdle is to denoise the signal acquainted as all the studies and researches are done on PPG assume the signal to be ideal. Hence preprocessing is creating a great hindrance for further research and improvement of PPG in the field of medical science. This paper presents a novel technique with a ruff preprocessing method (8 filters) and diverge at a conclusion that Chebyshev type-2 nullifies and filters the PPG signal collected in a conventional environment.