Title: Curtailing insomnia in a non-intrusive hardware less approach with machine learning

Authors: Shriram K. Vasudevan; T.B. Raguraman; Sini Raj Pulari

Addresses: K. Ramakrishnan College of Technology, Kariyamanikam Road, Samayapuram, Trichy – 621112, India ' Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, 641112, India ' Bahrain Polytechnic, Road 4003, Block 840, Isa Town, University of Bahrain's Campus Site, Kingdom of Bahrain

Abstract: The significant challenges nowadays with the expanded utilisation of cell phones are restlessness and a risk to mental health. Rest time is implied for the cerebrum to revive. If the rest time is disturbed because of a non-stop outer aggravation, it upsets the profound rest. Most of us prefer music as the option to induce sleep and relax. Headphones or earphones are used for the same. It is shrewd to turn off the music after an individual rests, which the majority of us do not do, as we by at that point, are rested. This causes damage. Excessive usage of earphones or headphones is one part of it and unnecessary feed to the ears while sleeping shall trigger noise-induced hearing loss. Here, we propose a framework built with machine learning as the key. This will guarantee that the music player stops once the individual using it has dozed off. This ensures proper rest and forestalls sleep deprivation/NIHL.

Keywords: machine learning; insomnia; sleep loss; noise-induced hearing loss; technology for sleep; hearing loss.

DOI: 10.1504/IJMEI.2022.126524

International Journal of Medical Engineering and Informatics, 2022 Vol.14 No.6, pp.537 - 549

Received: 28 Nov 2020
Accepted: 09 Jan 2021
Published online: 28 Oct 2022 *

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