Sound Detection and Classification for Medical Telesurvey

Medical Telesurvey needs human operator assistance by smart information systems. This paper deals with the sound event detection in a noisy environment and presents a first classification approach. Detection is the first step of our sound analysis system and is necessary to extract the significant sounds before initiating the classification step. An algorithm based on the Wavelet Transform is evaluated in noisy environment. Then Wavelet based cepstral coefficients are proposed and their results are compared with more classical parameters. Detection algorithm and sound classification methods are applied to medical telemonitoring. In our opinion, microphones surveying life sounds are better preserving patient privacy than video cameras.