Abstract:
Cardiovascular diseases CVDs are the leading cause of death all over the world, and the number of death are increasing day by day. This problem is getting more and more severe and due to its complexity CVDs are also become one of the major threat to human life. This problem is threatening to human life more in rural areas as compared to urban areas. Especially the villages and tribal areas, where no cardiologist could easily be available. The cardiovascular pathology turns to a serious problem if not properly detected, monitored and diagnosed at right time. So there is a dire need to control that alarming condition by proposing a solution which provides a proper, reliable and reasonable solution of that problem. There are other techniques as well to detect CVDs. Phtoplethysmogram PPG, Electrocardiogram ECG, as well. But the installation of heavy machinery in the rural areas is not easily possible. Also there are no such cardiologists are available for early treatment and detection of CVDs. In Phonocardiogram PCG also, cardiologists are required. So there is a dire need of design an automated robust hardware clinical decision support system for early detection of cardiovascular pathology. The objective of our project is to save the human lives from the threat of CVDs. For that purpose we fed the real time PCG signal of the patient into the proposed algorithm and then classify it using hybrid classifier as normal or abnormal. To make a smart stethoscope reliable to use even by a layman for detecting cardiovascular diseases.
