Real-time sleep quality assessment using single-lead ECG and multi-stage SVM classifier

Author

Bsoul, Majdi ; Minn, Hlaing ; Nourani, Mehrdad ; Gupta, Gopal ; Tamil, Lakshman

Author_Institution

Alcatel-Lucent, Plano, TX, USA

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

1178

Lastpage

1181

Abstract

Sleep efficiency measures provide an objective assessment to gauge the quality of individual´s sleep. In this study we present a home-based, automated and non-intrusive system that is based on Electrocardiogram (ECG) measurements and uses a multi-stage Support Vector Machines (SVM) classifier to measure three indices for sleep quality assessment per 30 s epoch segment: Sleep Efficiency Index, Delta-Sleep Efficiency Index and Sleep Onset Latency. This method provides an alternative to the intrusive and expensive Polysomnography (PSG) and scoring by Rechtschaffen and Kales visual method.

Keywords

electrocardiography; medical signal processing; signal classification; sleep; support vector machines; delta-sleep efficiency index; electrocardiogram; multistage SVM classifier; multistage Support Vector Machine classifier; real-time sleep quality assessment; single-lead ECG; sleep efficiency index; sleep onset latency; Electrocardiography; Feature extraction; Indexes; Sleep; Support vector machines; Time series analysis; Algorithms; Artificial Intelligence; Computer Systems; Diagnosis, Computer-Assisted; Electrocardiography; Humans; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Sleep Stages;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5626011

Filename

5626011