Deep learning model for acoustics signal based preventive healthcare monitoring and activity of daily living

Hemant Ghayvat, Sharnil Pandya, Ashish Patel

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

23 Citations (Scopus)

Abstract

To cope with the increasing healthcare costs and nursing shortages in the Aging Society the care system is transferred, as much as possible, to the home environment, making use of ambient assisted living (AAL) monitoring and communication possibilities and to actively involve informal cares to fill in large part of the care that is needed. The proposed system is the AAL based, acoustics sensing system ready to dissect, recognize, and distinguish specific acoustic events occurring in day-by-day life situations, which empowers not only the individual subjects but also the healthcare professionals to remotely follow the status of each individual continuously. This system only processes the background acoustics related to the activity of daily living (ADL) for preventive healthcare. The novel contribution of the research is based on prototype development, audio signal processing algorithms and deep learning algorithms to satisfy the research gap.

Original languageEnglish
Title of host publication2nd International Conference on Data, Engineering and Applications, IDEA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728157184
DOIs
Publication statusPublished - Feb 2020
Externally publishedYes
Event2nd International Conference on Data, Engineering and Applications, IDEA 2020 - Bhopal, India
Duration: 28 Feb 202029 Feb 2020

Publication series

Name2nd International Conference on Data, Engineering and Applications, IDEA 2020

Conference

Conference2nd International Conference on Data, Engineering and Applications, IDEA 2020
Country/TerritoryIndia
CityBhopal
Period28/02/2029/02/20

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