Sleep-wake classification via quantifying heart rate variability by convolutional neural network.

Journal: Physiological measurement

Published Date: Aug 20, 2018

Abstract

OBJECTIVE: Fluctuations in heart rate are intimately related to changes in the physiological state of the organism. We exploit this relationship by classifying a human participant's wake/sleep status using his instantaneous heart rate (IHR) series.

Authors

John Malik

Department of Mathematics, Duke University, Durham, NC, United States of America.
Yu-Lun Lo

Department of Thoracic Medicine, Healthcare Center, Chang Gung Memorial Hospital, School of Medicine, Chang Gung University, Taoyuan, Taiwan.
Hau-Tieng Wu

Mathematics, University of Toronto, Toronto, Ontario, Canada.

Keywords

Adult Databases, Factual Electrocardiography Female Healthy Volunteers Heart Rate Humans Male Neural Networks, Computer Signal Processing, Computer-Assisted Sleep Wakefulness

External Resources

View on PubMed Access via DOI PubMed (30043757)

Sleep-wake classification via quantifying heart rate variability by convolutional neural network.

Abstract

Authors

Keywords

External Resources

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