A No-Patient-Data Seizure Classifier Soc for Real-Time Classification of Seven Seizure Types Using Feature Fusion and Near-Memory Computing

The proposed multi-seizure-type classifier (MSTC) SoC is the first on-chip classification of multiple seizure types, integrating frequency-based feature fusion (FF) and digital ternary near memory computing (NMC) to achieve a classification accuracy of 91.63 % with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$24.72 \mu ~\mathrm{s}$</tex> computational latency. The MSTC SoC is also the first true zero-shot seizure detection system requiring no patient data for retraining, achieving 93.07 % sensitivity and 94.23 % specificity.