A 16.4nJ/Class Patient-Independent Prototype-Based Spatio-Temporal CNN Processor with Forward-Inference-Based Adaptation for Robust and Low-Latency Seizure Detection

Yang Wang; Longyang Lin; Jerald Yoo; Jiamin Li

doi:10.1109/isscc49663.2026.11409275

A 16.4nJ/Class Patient-Independent Prototype-Based Spatio-Temporal CNN Processor with Forward-Inference-Based Adaptation for Robust and Low-Latency Seizure Detection

Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference 2026

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Authors: Yang Wang, Longyang Lin, Jerald Yoo, Jiamin Li

DOI: 10.1109/isscc49663.2026.11409275

Cited by: 0

References: 10

Abstract

We present a patient-independent, prototype-based spatio-temporal CNN processor for seizure detection, achieving high accuracy without patient-specific data, at an energy of 16.4nJ/class and latency of

Fields of Study & Subjects

Analog and Mixed-Signal Circuit Design EEG and Brain-Computer Interfaces Advanced Neural Network Applications

Publication details

Journal / source: Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference
Pages: 604–606
Publication date: 15 February 2026
Language: EN

References 10