EEG Opto-Processor:Epileptic Seizure Detection Using Diffractive Photonic Computing Units

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外文摘要：Electroencephalography(EEG)analysis extracts critical information from brain signals,enabling brain disease diagnosis and providing fundamental support for brain-computer interfaces.However,perform-ing an artificial intelligence analysis of EEG signals with high energy efficiency poses significant chal-lenges for electronic processors on edge computing devices,especially with large neural network models.Herein,we propose an EEG opto-processor based on diffractive photonic computing units(DPUs)to process extracranial and intracranial EEG signals effectively and to detect epileptic seizures.The signals of the EEG channels within a second-time window are optically encoded as inputs to the con-structed diffractive neural networks for classification,which monitors the brain state to identify symp-toms of an epileptic seizure.We developed both free-space and integrated DPUs as edge computing systems and demonstrated their applications for real-time epileptic seizure detection using benchmark datasets,that is,the Children's Hospital Boston(CHB)-Massachusetts Institute of Technology(MIT)extracranial and Epilepsy-iEEG-Multicenter intracranial EEG datasets,with excellent computing perfor-mance results.Along with the channel selection mechanism,both numerical evaluations and experimen-tal results validated the sufficiently high classification accuracies of the proposed opto-processors for supervising clinical diagnosis.Our study opens a new research direction for utilizing photonic computing techniques to process large-scale EEG signals and promote broader applications.

外文关键词：

Epileptic seizure detectionEEG analysisDiffractive photonic computing unitPhotonic computing

作者：

Tao Yan、Maoqi Zhang、Hang Chen、Sen Wan、Kaifeng Shang、Haiou Zhang、Xun Cao、Xing Lin、Qionghai Dai

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作者单位：

Department of Automation,Tsinghua University,Beijing 100084,China

Institute for Brain and Cognitive Sciences,Tsinghua University,Beijing 100084,China

Department of Electronic Engineering,Tsinghua University,Beijing 100084,China

School of Electronic Science and Engineering,Nanjing University,Nanjing 210023,China

Beijing National Research Center for Information Science and Technology,Tsinghua University,Beijing 100084,China

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基金：

National Major Science and Technology Projects of ChinaNational Major Science and Technology Projects of ChinaNational Natural Science Fundation of ChinaNational Natural Science Fundation of ChinaTsinghua University Initiative Scientific Research Program

项目编号：

2021ZD01099022020AA01055006227513962088102

出版年：

2024

DOI：

10.1016/j.eng.2024.01.008

工程(英文)

CSTPCDEI

ISSN：2095-8099

年,卷(期)：2024.35(4)