What is it about?
The developed analytics provide • Monitoring multivariate EEG signals in real-time for possible change of the eye state. • Use of data-driven methods that can handle multivariate, non-linear, and non-stationary signals. • Fast eye state change detection with high accuracy. • Huge improvement in comparison to published studies.
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Why is it important?
Detecting eye states has many applications including classification of sleep-waking states in infants or hospitalized patients, detection of driving drowsiness where it estimated to be responsible for at least 72,000 crashes, 44,000 injuries, and 800 deaths in 2013, human-computer interface design, alertness of pilots especially fighter jet pilots, and stress feature identification, among others.
Perspectives
A non-provisional patent is filed with the USPTO as we have developed analytics which perform significantly better than alternatives.
Dr. Abolfazl Saghafi
University of the Sciences in Philadelphia
Read the Original
This page is a summary of: Random eye state change detection in real-time using EEG signals, Expert Systems with Applications, April 2017, Elsevier,
DOI: 10.1016/j.eswa.2016.12.010.
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