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Improving the classification of newborn EEG time-frequency representations using a combined time-frequency signal and image approach
(2012 , Conference Paper)
This paper presents new time-frequency (T-F) features to improve the classification of non-stationary signals such as EEG signals. Previous methods were based only on signal features that were derived from the instantaneous ...
Automated class-based compression for real-time epileptic seizure detection
(
IEEE Computer Society
, 2018 , Conference Paper)
The emergence of next generation wireless networking technologies has motivated a paradigm shift in development of viable mobile-Health applications for ubiquitous real-time healthcare monitoring. However, remote healthcare ...
Energy efficient EEG monitoring system for wireless epileptic seizure detection
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
Wireless EEG monitoring systems have been successfully used for seizure detection outside clinical settings. The wireless EEG sensor nodes consume a considerable amount of battery energy to acquire, encode and transmit the ...
Effective seizure detection through the fusion of single-feature enhanced-k-NN classifiers of EEG signals
(
IEEE
, 2013 , Conference Paper)
Electroencephalogram (EEG) physiological signals are widely used for detecting epileptic seizure. To reduce complexity stemming from the dimensionality problem, EEG signals are often reduced into a smaller set of discriminant ...
Evidence theory-based approach for epileptic seizure detection using EEG signals
(
IEEE
, 2012 , Conference Paper)
Electroencephalogram (EEG) is one of the potential physiological signals used for detecting epileptic seizure. Discriminant features, representing different brain conditions, are often extracted for diagnosis purposes. ...
Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals
(
IEEE Computer Society
, 2012 , Conference Paper)
This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The ...