Highly Efficient Back‑End‑of‑Line Compatible Flexible Si‑Based Optical Memristive Crossbar Array for Edge Neuromorphic Physiological Signal Processing and Bionic Machine Vision

作     者：Dayanand Kumar Hanrui Li Dhananjay D.Kumbhar Manoj Kumar Rajbhar Uttam Kumar Das Abdul Momin Syed Georgian Melinte Nazek El‑Atab Dayanand Kumar;Hanrui Li;Dhananjay D.Kumbhar;Manoj Kumar Rajbhar;Uttam Kumar Das;Abdul Momin Syed;Georgian Melinte;Nazek El-Atab

作者机构：SmartAdvanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer EngineeringComputer Electrical Mathematical Science and EngineeringKing Abdullah University of Science and Technology(KAUST)23955‑6900 ThuwalSaudi Arabia 

出 版 物：《Nano-Micro Letters》 (纳微快报（英文版）)

年 卷 期：2024年第16卷第11期

页      面：323-339页

核心收录：

学科分类：080903[工学-微电子学与固体电子学] 0711[理学-系统科学] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080203[工学-机械设计及理论] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0802[工学-机械工程] 

基　　金：financial support by the Semiconductor Initiative at the King Abdullah University of Science and Technology supported by King Abdullah University of Science and Technology(KAUST)Research Funding(KRF)under Award No.ORA-2022-5314 

主　　题：Neuromorphic computing Electrophysiological signal Artificial vision system Image recognition Memristor 

摘      要：The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices,opening numerous opportunities across countless domains,including personalized healthcare and advanced *** 3D integration,edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy ***,we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications,including electroencephalogram(EEG)-based seizure prediction,electromyography(EMG)-based gesture recognition,and electrocardiogram(ECG)-based arrhythmia *** experiments on three biomedical datasets,we observe the classification accuracy improvement for the pretrained model with 2.93%on EEG,4.90%on ECG,and 7.92%on EMG,*** optical programming property of the device enables an ultralow power(2.8×10^(-13) J)fine-tuning process and offers solutions for patient-specific issues in edge computing ***,the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions,making it promising for neuromorphic vision *** display the benefits of these intricate synaptic properties,a 5×5 optoelectronic synapse array is developed,effectively simulating human visual perception and memory *** proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.