Remote monitoring, distress detection by slightest invasive systems: Sound recognition based on hierarchical i-vectors

Maxime Robin, Dan Istrate, Jerome Boudy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Europe has a growing aging population, leading to the need for adapted healthcare services. Our work aims at proposing a solution for falls detection of elderly people using sound recognition based on a hierarchical i-vectors system. The system presented in this paper improves significantly the accuracy of sound recognition compared to the state of the art methods. The latter provides a good recognition rate of 81.98% on noiseless sounds. This system needs to be tested in a noisy environment and this can be improved by using new sound descriptors.

Original languageEnglish
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2744-2748
Number of pages5
ISBN (Electronic)9781509028092
DOIs
Publication statusPublished - 13 Sept 2017
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: 11 Jul 201715 Jul 2017

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Country/TerritoryKorea, Republic of
CityJeju Island
Period11/07/1715/07/17

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