The heart is one of the most important organs of the body. It controls the flows of blood through our body. So any diseases related to the heart can be fatal. Almost 18million people die each year from heart-related diseases. That is why heart diseases can not be ignored.
A phonocardiogram (PCG) is the sound that the heart creates when it pumps blood through blood vessels. Doctors use stethoscopes to listen to sound and analyze heart conditions. But human hearing is not appropriate for accurately analyze PCG signals. In a cardiac cycle, two different sound is generated, first one called systolic (S1) and the second one is diastolic murmur (S2). Two valves of the heart, mitral and tricuspid, when they close generate S1. And another two valves aortic and pulmonary, generate S2 when they close. Abnormal heart sounds may contain some extra noise and murmurs caused by different diseased conditions of the heart and circulatory system. To detect those extra sounds, the human ear is not very suitable. So, diagnosis of heart sounds is very limited by only hearing the sound of the cardiac cycle.
PCG signal contains valuable information which can be used to detect many heart diseases. So our project focuses on an automated system for extracting features from PCG signals. Users can select any PCG signal and extract features from that PCG signal.
Why PCG signal is important?
People who are from non-medical backgrounds have very little knowledge about heart conditions. Even for doctors, it is very difficult to determine anything just from hearing heart sounds.
PCG signal contains valuable information about a heart condition. It is more trustworthy to take a decision based on extracted information from PCG signal than hearing heart sounds and take the decision from that.
So the more important features we can get from the PCG signal the more it will help us to detect heart diseases easily. So the importance of PCG signal processing and its features important can not be ignored.
