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Adaptive compression and optimization for real-time energy-efficient wireless EEG monitoring systems
(
IEEE
, 2013 , Conference Paper)
Recent technological advances in wireless body sensor networks (WBSN) have made it possible for the development of innovative medical applications to improve health care and the quality of life. Electroencephalography ...
Design and analysis of an adaptive compressive sensing architecture for epileptic seizure detection
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as a representative signal carrying valuable information pertaining to the current brain state. In this work, we investigate the stability of ...
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 ...
Optimum power and rate allocation in video sensor networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2013 , Conference Paper)
In a sensor network, each sensor has a limited energy supply. Therefore, it is critical to minimize the power consumed by each sensor to maximize its lifetime. Video sensor networks differ from conventional sensor networks ...
EEG feature extraction and selection techniques for epileptic detection: A comparative study
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as representative signal carrying valuable information pertaining to the current brain state. For these techniques to be efficient and reliable, ...
Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring
(
IEEE
, 2013 , Conference Paper)
Brain is the most important part in the human body controlling muscles and nerves; Electroencephalogram (EEG) signals record brain electric activities. EEG signals capture important information pertinent to different ...
Energy-aware cross-layer optimization for EEG-based wireless monitoring applications
(
IEEE Computer Society
, 2013 , Conference Paper)
Body Area Sensor Networks (BASNs) for healthcare applications have gained significant research interests recently due to the growing number of patients with chronic diseases requiring constant monitoring. Because of the ...
Bayesian network based heuristic for energy aware EEG signal classification
(
SpringerLink
, 2013 , Conference Paper)
A major challenge in the current research of wireless electroencephalograph (EEG) sensor-based medical or Brain Computer Interface applications is how to classify EEG signals as accurately and energy efficient as possible. ...
Adaptive energy-aware encoding for DWT-based wireless EEG tele-monitoring system
(
IEEE Computer Society
, 2013 , Conference Paper)
Recent technological advances in wireless body sensor networks (WBSN) have made it possible for the development of innovative medical applications to improve health care and the quality of life. Electroencephalography ...
Area spectral efficiency of underlay cognitive radio transmission over rayleigh fading channels
(
IEEE
, 2013 , Conference Paper)
Cognitive radio is a promising technology to improve the spectrum utilization by allowing the unlicensed (secondary) user share a frequency bandwidth with the licensed (primary) owner under the condition that no harmful ...