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 sig-nificant sounds before initiating the classification step. An algorithm based on the Wavelet Transform is evaluated in noisy environment. Then Wavelet based cepstral coeffi-cients are proposed and their results are compared with more classical parameters. Detection algorithm and sound classification methods are applied to medical telemonitor-ing. In our opinion, microphones surveying life sounds are better preserving patient privacy than video cameras.