Application of Deep Learning in the Identification of Cerebral Hemodynamics Data Obtained from Functional Near-Infrared Spectroscopy: A Preliminary Study of Pre- and Post-Tooth Clenching Assessment

Application of Deep Learning in the Identification of Cerebral Hemodynamics Data Obtained from Functional Near-Infrared Spectroscopy: A Preliminary Study of Pre- and Post-Tooth Clenching Assessment

In fields using functional near-infrared spectroscopy (fNIRS), there is a need for an easy-to-understand method that allows visual presentation and rapid analysis of data and test results. This preliminary study examined whether deep learning (DL) could be applied to the analysis of fNIRS-derived br...

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Bibliographic Details
Main Authors: Shinya Takagi, Shigemitsu Sakuma, Ichizo Morita, Eri Sugimoto, Yoshihiro Yamaguchi, Naoya Higuchi, Kyoko Inamoto, Yoshiko Ariji, Eiichiro Ariji, Hiroshi Murakami
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Journal of Clinical Medicine
Subjects:
deep learning
deoxy-hemoglobin
functional near-infrared spectroscopy
oxy-hemoglobin
Online Access:https://www.mdpi.com/2077-0383/9/11/3475

Internet

https://www.mdpi.com/2077-0383/9/11/3475

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