@inproceedings{d3ec42f8c6c3484ebdf7b0dc03cc2448,
title = "Deep learning model for acoustics signal based preventive healthcare monitoring and activity of daily living",
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.",
keywords = "AAL, ADL, Elderly well being, Healthcare, Monitoring, Sensor activation",
author = "Hemant Ghayvat and Sharnil Pandya and Ashish Patel",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2nd International Conference on Data, Engineering and Applications, IDEA 2020 ; Conference date: 28-02-2020 Through 29-02-2020",
year = "2020",
month = feb,
doi = "10.1109/IDEA49133.2020.9170666",
language = "English",
series = "2nd International Conference on Data, Engineering and Applications, IDEA 2020",
publisher = "IEEE",
booktitle = "2nd International Conference on Data, Engineering and Applications, IDEA 2020",
address = "United States",
}