Machine-based patient-specific seizure classification system
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United States of America Patent
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Dec 26, 2017
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Feb 18, 2014
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Feb 15, 2013
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Abstract
This disclosure is directed to a machine-based patient-specific seizure classification system. In general, an example system may comprise a non-linear SVM seizure classification system-on-chip (SoC) with multichannel EEG data acquisition and storage for epileptic patients is presented. The SoC may integrate a hardware-efficient log-linear Gaussian Basis Function engine, floating point piecewise linear natural log, and low-noise, high dynamic range readout circuits. In at least one example implementation, the SoC may consume 1.83 μJ/classification while classifying 8 channel results with an average detection rate, average false alarm rate and latency of 95.1%, 0.94% and <2 s, respectively.
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