Deep learning for healthcare applications based on physiological signals: A review.

Journal: Computer methods and programs in biomedicine

Published Date: Jul 1, 2018

Abstract

BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.2017.

Authors

Oliver Faust

Department of Engineering and Mathematics, Sheffield Hallam University, United Kingdom. Electronic address: o.faust@shu.ac.uk.
Yuki Hagiwara

Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore.
Tan Jen Hong

Department of Electronic & Computer Engineering, Ngee Ann Polytechnic, Singapore.
Oh Shu Lih

Department of Electronic & Computer Engineering, Ngee Ann Polytechnic, Singapore.
U Rajendra Acharya

School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Darling Heights, Australia.

Keywords

Algorithms Diagnosis, Computer-Assisted Electrocardiography Electroencephalography Electromyography Electrooculography Humans Linear Models Machine Learning Medical Informatics Neurons Quality of Health Care Signal Processing, Computer-Assisted

External Resources

View on PubMed Access via DOI PubMed (29852952)

Deep learning for healthcare applications based on physiological signals: A review.

Abstract

Authors

Keywords

External Resources

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