PMID: 16617615Apr 19, 2006Paper

Information extraction from sound for medical telemonitoring

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
Dan IstrateJean-François Serignat

Abstract

Today, the growth of the aging population in Europe needs an increasing number of health care professionals and facilities for aged persons. Medical telemonitoring at home (and, more generally, telemedicine) improves the patient's comfort and reduces hospitalization costs. Using sound surveillance as an alternative solution to video telemonitoring, this paper deals with the detection and classification of alarming sounds in a noisy environment. The proposed sound analysis system can detect distress or everyday sounds everywhere in the monitored apartment, and is connected to classical medical telemonitoring sensors through a data fusion process. The sound analysis system is divided in two stages: sound detection and classification. The first analysis stage (sound detection) must extract significant sounds from a continuous signal flow. A new detection algorithm based on discrete wavelet transform is proposed in this paper, which leads to accurate results when applied to nonstationary signals (such as impulsive sounds). The algorithm presented in this paper was evaluated in a noisy environment and is favorably compared to the state of the art algorithms in the field. The second stage of the system is sound classification, which ...Continue Reading

Citations

Oct 10, 2013·Telemedicine Journal and E-health : the Official Journal of the American Telemedicine Association·Hulya Gokalp, Malcolm Clarke
Mar 19, 2019·European Journal of Cancer Care·Rajib RanaJeff Dunn
Jan 1, 2013·Journal of Ambient Intelligence and Humanized Computing·Kin Fun Li
Feb 3, 2020·The Journal of the Acoustical Society of America·Mingsian R BaiHing-Cheung So
May 28, 2013·International Journal of Telemedicine and Applications·David MaunderBranko Celler

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