ABSTRACT
In this study the potential of a Laser Doppler Vibrometer (LDV) was tested as a non-contact sensor for the classification of heart sounds. Of the twenty participants recorded using the LDV, five presented with Aortic Stenosis (AS), three were healthy and twelve presented with other pathologies. The recorded heart sounds were denoised and segmented using a combination of the Electrocardiogram (ECG) data and the complexity of the signal. Frequency domain features were extracted from the segmented heart sound cycles and used to train a K-nearest neighbor classifier. Due to the small number of participants, the classifier could not be trained to differentiate between normal and abnormal participants, but could successfully distinguish between participants who presented with AS and those who did not. A sensitivity of 80 % and a specificity of 100 % were achieved a test dataset.
