Automated Change-Point Detection of EEG Signals Based on Structural Time-Series Analysis

Automated Change-Point Detection of EEG Signals Based on Structural Time-Series Analysis

Automated change-point detection of EEG signals is becoming essential for the monitoring of health behaviors and health status in a wide range of clinical applications. This paper presents a structural time-series analysis to capture and characterize the dynamic behavior of EEG signals, and develops...

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Bibliographic Details
Main Authors: Guangyuan Chen, Guoliang Lu, Wei Shang, Zhaohong Xie
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Change detection
distance metric
EEG monitoring
similarity metric
time series analysis
Online Access:https://ieeexplore.ieee.org/document/8918063/

Internet

https://ieeexplore.ieee.org/document/8918063/

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