Highly Efficient Back-End-of-Line Compatible Flexible Si-Based Optical Memristive Crossbar Array for Edge
Dayanand Kumar1, Hanrui Li1, Dhananjay D Kumbhar1
1Smart, Advanced Memory Devices and Applications (SAMA) Laboratory, Electrical and Computer Engineering, Computer Electrical Mathematical Science and Engineering, King Abdullah University of Science and Technology (KAUST), 23955-6900, Thuwal, Saudi Arabia.
Nano-Micro Letters
|July 8, 2024
Summary
This study introduces a novel optoelectronic synapse for smart edge devices, enhancing healthcare applications like seizure prediction and gesture recognition. The device offers ultra-low power fine-tuning and light-triggered functions for neuromorphic computing.
Area of Science:
- Materials Science
- Neuroscience
- Computer Engineering
Background:
- The Internet-of-Things (IoT) drives demand for miniaturized, powerful smart edge devices.
- 3D integration offers enhanced processing and reduced energy consumption in edge devices.
- Optoelectronic synapses are key components for advanced neuromorphic computing.
Purpose of the Study:
- To demonstrate a back-end-of-line compatible optoelectronic synapse for healthcare applications.
- To evaluate the device's performance in electroencephalogram (EEG)-based seizure prediction, electromyography (EMG)-based gesture recognition, and electrocardiogram (ECG)-based arrhythmia detection.
- To showcase the potential for ultra-low power fine-tuning and light-triggered synaptic functions.
Main Methods:
- Development of a back-end-of-line compatible optoelectronic synapse.
- Application of transfer learning methods on biomedical datasets (EEG, EMG, ECG).
- Fabrication and testing of a 5x5 optoelectronic synapse array.
Main Results:
- Achieved classification accuracy improvements of 2.93% (EEG), 4.90% (ECG), and 7.92% (EMG) using the pretrained model.
- Demonstrated ultra-low power (2.8 × 10^-13 J) fine-tuning via optical programming.
- Exhibited light-sensitive characteristics enabling light-triggered synaptic functions and simulation of visual perception.
Conclusions:
- The flexible optoelectronic synapse shows significant potential for neuromorphic physiological signal processing.
- The device is promising for artificial visual systems in wearable applications.
- Optoelectronic synapses offer efficient solutions for patient-specific edge computing needs.
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