Cough detection and classification present necessary tools for the evaluation of pathology severity in chronic illnesses. In literature, several approaches have been proposed for this aim. The latter presented a relative success since none of them allow a standardized exploitation and interpretation of sensors results in order to provide an efficient cough detection and classification. This paper presents a new system that disposes of a prototype (hardware) for data acquisition, and software for exploiting the acquired data for cough detection, visualization and classification. Our prototype includes sensors such as ECG, thermistor, chest belt, accelerometer, oximeter, contact and audio microphones. The relevance of each sensor is evaluated within three features: mutual information obtained with the features, ability to distinguish cough from other event categories, and ability to detect cough events. The sensors values are interpreted and visualized with a graphical view where the detected cough extracts are visualized and organized accordingly to their similarity in terms of audio properties such as timbre, cough duration and signal energy.
Biomedical Engineering, Sensor, Audio Processing, Cough Detection, Cough Classification.