Sleep Spindle Detection and Prediction Using a Mixture of Time Series and Chaotic Features

Sleep Spindle Detection and Prediction Using a Mixture of Time Series and Chaotic Features

It is well established that sleep spindles (bursts of oscillatory brain electrical activity) are significant indicators of learning, memory and some disease states. Therefore, many attempts have been made to detect these hallmark patterns automatically. In this pilot investigation, we paid special a...

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Bibliographic Details
Main Authors: Amin Hekmatmanesh, Mohammad Mikaeili, Khosrow Sadeghniiat-Haghighi, Huapeng Wu, Heikki Handroos, Radek Martinek, Homer Nazeran
Format: Article
Language:English
Published: VSB-Technical University of Ostrava 2017-01-01
Series:Advances in Electrical and Electronic Engineering
Subjects:
chaotic features
discriminative capacity
fractal dimension
intensity map
sleep eeg
spindle.
Online Access:http://advances.utc.sk/index.php/AEEE/article/view/2174

Internet

http://advances.utc.sk/index.php/AEEE/article/view/2174

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