This week I worked on removing noise from the heart sound data. I did this by first finding the average of all the peaks and then removing extra high or low amplitudes. Below is the graph of the original heart sound, along with the heart sound after the loud and quiet noises are removed.
Next I used a Fourier transform to find the heart sound in frequency. I then got rid of all the frequencies that are not within the range of 20Hz to 150 Hz – the range of the human heart sound – using a low pass and high pass filter. In addition to this, I also experimented with other algorithms such as the moving average; however it had a very slow computation speed and it did not remove the noise as well as desired. I am currently on schedule, since my goal was to finish the denoising algorithm. Although it does not one hundred percent get rid of all the noise yet, it is pretty close. This week I will work on segmenting the heart sound into 5 full lub dub beats using deep learning. I did some research this week of which algorithms work best, but I have not decided which to move forward with yet.