Example of an EEGEpileptic seizures, caused by disruptions in the normal electrical activity of the brain can cause victims to suffer convulsions and unconsciousness. At the moment, there is no way to predict when such seizures would happen besides manually checking records of electrical activity of patient’s brains that have been recorded using EEGs (electroencephalograms). Normally it isn’t a problem to review EEG data, but when you have weeks’ worth of readings and multiple patients to take care of – it can become a time consuming process. Some researchers at Concordia University have managed to detect recognizable characteristics of approaching seizures and devised an algorithm based on those patterns. The system is undergoing testing right now and results have been very successful, with a high rate of seizure detection and low rate of false positives. It’ll be awhile before it sees the light of day in our hospitals, but when it does, it’ll be extremely beneficial.


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