Abstract
EEG based monitoring for the purpose of assessing a patient's neurological status is conspicuous and uncomfortable at best. We are analyzing a set of physiological signals that may be monitored comfortably by a wrist worn device. We have found that these signals and machine based classification allows us to accurately discriminate among four stress states of individuals. Further, we have found a clear change in these signals during the 70 minutes preceding a single convulsive epileptic seizure. Our classification accuracy on all data has been greater than 90% to date.
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