Generic Implementation of a Distress Sound Extraction System for Elder Care

Dan Istrate (1) , Michel Vacher (1) , Jean-François Serignat (1)

1 CLIPS-IMAG - Equipe GEOD, Groupe d'étude sur l'oral et le dialogue

— Medical remote monitoring at home is an al-ternative to improve the patient's comfort, to detect distress situation rapidly and reduce hospitalization costs. Physiologic and position sensors give already numerous information, but sound classification can give interesting additional information. A Real-Time implementation of a smart sound system capable of detecting and identifying sound events in noisy conditions is presented in this paper. The advantage of this implementation is the use of a generic PC station: the hardware requirements are only a sound card, a microphone and an internet link used to transmit alarm. In the case of an alarm, the information can be sent through network to a remote monitoring center and/or to a close person by email or SMS. The system is composed of 2 modules: detection and classification. The event detection module is carried out in real time in order to extract possible alarm sounds. The sound classification module is launched in a parallel task; it carries out a first segmentation between sound and speech. In the speech case, a speech recognition system is launched (not described in this paper) and in the sound case, a classification between predefined classes is carried out.

Domaines: Autre [cs.OH]

Dan Istrate, Michel Vacher, Jean-François Serignat. Generic Implementation of a Distress Sound Extraction System for Elder Care. The 28th IEEE EMBS Annual International Conference, EMBC, Aug 2006, New-York, United States. pp.3309 - 3312, ⟨10.1109/IEMBS.2006.259469⟩. ⟨hal-01094411⟩