Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals-Reference-Cited by-同舟云学术

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Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals

Published:2018-10 Issue:10 Volume:24 Page:753-772
ISSN:1530-5627
Container-title:Telemedicine and e-Health
language:en
Short-container-title:Telemedicine and e-Health

Author:

Hwang Bosun¹,You Jiwoo²,Vaessen Thomas³,Myin-Germeys Inez³,Park Cheolsoo²,Zhang Byoung-Tak¹

Affiliation:

1. Department of Computer Science and Engineering, Seoul National University, Seoul, Korea.

2. Department of Computer Engineering, Kwangwoon University, Nowon-gu, Seoul, Korea.

3. KU Leuven, Department of Neurosciences, Center for Contextual Psychiatry, Leuven, Belgium.

Publisher

Mary Ann Liebert Inc

Subject

Health Information Management,Health Informatics,General Medicine

Link

https://www.liebertpub.com/doi/pdf/10.1089/tmj.2017.0250

Reference21 articles.

1. Autonomic nervous system activity in emotion: A review

2. The effect of mental stress on heart rate variability and blood pressure during computer work

3. DETECTION OF HUMAN STRESS USING SHORT-TERM ECG AND HRV SIGNALS

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