Electroencephalography (EEG) analysis extracts critical information from brain signals, enabling brain disease diagnosis and providing fundamental support for brain–computer interfaces. However, performing an artificial intelligence analysis of EEG signals with high energy efficiency poses significant challenges 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 constructed diffractive neural networks for classification, which monitors the brain state to identify symptoms 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 performance results. Along with the channel selection mechanism, both numerical evaluations and experimental 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.

中文翻译：

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EEG 光电处理器：使用衍射光子计算单元检测癫痫发作

脑电图（EEG）分析从大脑信号中提取关键信息，实现脑部疾病诊断并为脑机接口提供基础支持。然而，以高能效对脑电图信号进行人工智能分析给边缘计算设备上的电子处理器带来了重大挑战，特别是对于大型神经网络模型。在此，我们提出了一种基于衍射光子计算单元（DPU）的脑电图光处理器，可有效处理颅外和颅内脑电图信号并检测癫痫发作。第二时间窗口内的脑电图通道信号被光学编码为构建的衍射神经网络的输入以进行分类，该网络监测大脑状态以识别癫痫发作的症状。我们开发了自由空间和集成 DPU 作为边缘计算系统，并使用基准数据集演示了它们在实时癫痫发作检测中的应用，即波士顿儿童医院 (CHB)-麻省理工学院 (MIT) 的颅外和癫痫- iEEG-多中心颅内脑电数据集，具有出色的计算性能结果。除了通道选择机制之外，数值评估和实验结果都验证了所提出的用于监督临床诊断的光处理器具有足够高的分类精度。我们的研究为利用光子计算技术处理大规模脑电信号并促进更广泛的应用开辟了新的研究方向。