Overview / Usage

Phonocardiogram is a chart or record of the sounds made by the heart. The aim of the project is to classify a heart as normal and abnormal based on the phonocardiogram of the heart. This will open up a wide spectre of innovation and research in the biomedical field. This will help people get treated properly and quicker in a very cost effective manner.

Methodology / Approach

The approach towards the project is divided into parts.

1. Segmentation: The pre requisite of the project is segmentation of the phonocardiogram. The segmentation is done with Hidden Markov model which lets segment a signal into 4 parts namely s1,s2,s3 and s4. The segmentation helps usconcentrate on the murmurs(noises) in each section and then extract viable features for the classification task.
2. Classification: A perceptron model was proposed that would be based on statistical features of a signal. Support Vector machine was proposed too. Both the apporaches were no where near to make a good precision or accuracy.

Technologies Used

• Intel Python
• Matlab

Repository

https://github.com/forkbomb-666/phonocardiogram

Collaborators