Please use this identifier to cite or link to this item: https://doi.org/10.1145/1873951.1874154
Title: Automated sleep quality measurement using EEG signal - First step towards a domain specific music recommendation system
Authors: Zhao, W.
Wang, X.
Wang, Y. 
Keywords: music recommendation
music therapy
sleep disorder
sleep quality analysis
Issue Date: 2010
Source: Zhao, W.,Wang, X.,Wang, Y. (2010). Automated sleep quality measurement using EEG signal - First step towards a domain specific music recommendation system. MM'10 - Proceedings of the ACM Multimedia 2010 International Conference : 1079-1082. ScholarBank@NUS Repository. https://doi.org/10.1145/1873951.1874154
Abstract: With the rapid pace of modern life, millions of people suffer from sleep problems. Music therapy, as a non-medication approach to mitigating sleep problems, has attracted increasing attention recently. However the adaptability of music therapy is limited by the time consuming task of choosing suitable music for users. Inspired by this observation, we discuss the concept of a domain specific music recommendation system, which automatically recommends music for users according to their sleep quality. The proposed system requires multidisciplinary efforts including automated sleep quality measurement and content-based music similarity measure. As a first step, we focus on the automated sleep quality measurement in this paper. An EEG-based approach is proposed to measure user's sleep quality. The advantages of our approach over standard Polysomnography (PSG) method are: 1) it measures sleep quality by recognizing three sleep categories rather than six sleep stages, thus higher accuracy can be expected; 2) three sleep categories are recognized by analyzing Electroencephalography (EEG) signal only, so the user experience is improved because he is attached with fewer sensors during sleep. We conduct experiments based on a standard data set. Our approach achieves high accuracy and shows promising potential for the music recommendation system. © 2010 ACM.
Source Title: MM'10 - Proceedings of the ACM Multimedia 2010 International Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/40879
ISBN: 9781605589336
DOI: 10.1145/1873951.1874154
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

7
checked on Dec 13, 2017

Page view(s)

72
checked on Dec 16, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.