Occipital EEG Activity for the Detection of Nocturnal Hypoglycemia

Cuong Q. Ngo, Bao C.Q. Truong, Timothy W. Jones, Hung T. Nguyen

Research output: Chapter in Book/Conference paperConference paper

6 Citations (Scopus)

Abstract

Nocturnal hypoglycemia is dangerous that threatens patients because of its unclear symptoms during sleep. This paper is a study of hypoglycemia from 8 patients with type 1 diabetes (T1D) at night. O1 and O2 EEG data of the occipital lobe associated with glycemic episodes were analyzed. Frequency features were computed from Power Spectral Density using Welch's method. Centroid alpha frequency reduced significantly (P < 0.0001) while centroid theta increased considerably (P < 0.01). Spectral entropy of the unified theta-alpha band rose significantly (P < 0.005). These occipital features acted as the input of a Bayesian regularized neural network for detecting hypoglycemic episodes. The classification results were 73% and 60% of sensitivity and specificity, respectively.

Original languageEnglish
Title of host publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages3862-3865
Number of pages4
ISBN (Electronic)9781538636466
DOIs
Publication statusPublished - 26 Oct 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States
Duration: 18 Jul 201821 Jul 2018

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2018-July
ISSN (Print)1557-170X

Conference

Conference40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
CountryUnited States
CityHonolulu
Period18/07/1821/07/18

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