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Authors: Amro Khasawneh 1 ; Sergio A. Alvarez 2 ; Carolina Ruiz 1 ; Shivin Misra 1 and Majaz Moonis 3

Affiliations: 1 Worcester Polytech. Inst., United States ; 2 Boston College, United States ; 3 U. Massachusetts Medical School, United States

ISBN: 978-989-8425-34-8

Keyword(s): Clustering, EEG, ECG, HRV, Sleep.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Medical and Nursing Informatics ; Pattern Recognition and Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Unsupervised clustering of staged human polysomnographic recordings reveals a hierarchy of sleep composition types described primarily by sleep efficiency and slow wave sleep content. Associations are found between these sleep clusters and health-related variables including BMI, smoking habits, and heart disease, showing that sleep types correspond to objective and medically relevant groupings. The present work describes the sleep type hierarchy, and studies the EEG and ECG correlates of sleep composition type. It is found that measures of EEG variation such as δ, θ, and α spectral content, as well as average heart rate, and measures of heart rate variability, including the standard deviation of the sequence of RR intervals, and Hjörth activity and mobility of the ECG signal, differ significantly among sleep composition type clusters. EEG analysis is shown to allow approximate reconstruction of sleep type without the need for ECG data, while ECG alone is found to be insufficient for a ccurate sleep type classification. (More)

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Paper citation in several formats:
Khasawneh A., A. Alvarez S., Ruiz C., Misra S. and Moonis M. (2011). EEG AND ECG CHARACTERISTICS OF HUMAN SLEEP COMPOSITION TYPES.In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011) ISBN 978-989-8425-34-8, pages 97-106. DOI: 10.5220/0003173900970106

@conference{healthinf11,
author={Amro Khasawneh and Sergio A. Alvarez and Carolina Ruiz and Shivin Misra and Majaz Moonis},
title={EEG AND ECG CHARACTERISTICS OF HUMAN SLEEP COMPOSITION TYPES},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011)},
year={2011},
pages={97-106},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003173900970106},
isbn={978-989-8425-34-8},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011)
TI - EEG AND ECG CHARACTERISTICS OF HUMAN SLEEP COMPOSITION TYPES
SN - 978-989-8425-34-8
AU - Khasawneh A.
AU - A. Alvarez S.
AU - Ruiz C.
AU - Misra S.
AU - Moonis M.
PY - 2011
SP - 97
EP - 106
DO - 10.5220/0003173900970106

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