Multi-center validation study of automated classification of pathological slowing in adult scalp electroencephalograms via frequency features

Multi-center validation study of automated classification of pathological slowing in adult scalp electroencephalograms via frequency features

Pathological slowing in the electroencephalogram (EEG) is widely investigated for the diagnosis of neurological disorders. Currently, the gold standard for slowing detection is the visual inspection of the EEG by experts, which is time-consuming and subjective. To address those issues, we propose th...

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Bibliographic Details
Main Authors: Peh, Wei Yan, Thomas, John, Bagheri, Elham, Chaudhari, Rima, Karia, Sagar, Rathakrishnan, Rahul, Saini, Vinay, Shah, Nilesh, Srivastava, Rohit, Tan, Yee-Leng, Dauwels, Justin
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Electrical and electronic engineering
Electroencephalogram
EEG Slowing
Online Access:https://hdl.handle.net/10356/159814

Internet

https://hdl.handle.net/10356/159814

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