Abstract
We present a 16-channel seizure detection system-on-chip (SoC) with 0.92µW/channel power dissipation in a total area of 1.1mm2 including a closed-loop neural stimulator. A set of four features are extracted from the spatially filtered neural data to achieve a high detection accuracy at minimal hardware cost. The performance is demonstrated by early detection and termination of kainic acid-induced seizures in freely moving rats and by offline evaluation on human intracranial EEG (iEEG) data. Our design improves upon previous works by over 40× reduction in power-area product per channel. This improvement is a key step towards integration of larger arrays with higher spatiotemporal resolution to further boost the detection accuracy.
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