46 citations · 176 across the 25 of their papers we have counts for
10 papers · 1 filter
A 97 fJ/Conversion Neuron-ADC with Reconfigurable Sampling and Static Power Reduction
Jinbo Chen, Hui Wu, Jie Yang +1
A bio-inspired Neuron-ADC with reconfigurable sampling and static power reduction for biomedical applications is proposed in this work. The Neuron-ADC leverages level-crossing samp…
Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond
Di Wu, Jie Yang, Mohamad Sawan
Machine learning on electromyography (EMG) has recently achieved remarkable success on a variety of tasks, while such success relies heavily on the assumption that the training and…
A Compact Online-Learning Spiking Neuromorphic Biosignal Processor
Chaoming Fang, Ziyang Shen, Fengshi Tian +2
Real-time biosignal processing on wearable devices has attracted worldwide attention for its potential in healthcare applications. However, the requirement of low-area, low-power a…
SpikeSEE: An Energy-Efficient Dynamic Scenes Processing Framework for Retinal Prostheses
Chuanqing Wang, Chaoming Fang, Yong Zou +2
Intelligent and low-power retinal prostheses are highly demanded in this era, where wearable and implantable devices are used for numerous healthcare applications. In this paper, w…
Binary Single-dimensional Convolutional Neural Network for Seizure Prediction
Shiqi Zhao, Jie Yang, Yankun Xu +1
Nowadays, several deep learning methods are proposed to tackle the challenge of epileptic seizure prediction. However, these methods still cannot be implemented as part of implanta…
Recent Trends and Future Prospects of Neural Recording Circuits and Systems: A Tutorial Brief
Jinbo Chen, Mahdi Tarkhan, Hui Wu +3
Recent years have seen fast advances in neural recording circuits and systems as they offer a promising way to investigate real-time brain monitoring and the closed-loop modulation…
An Event-Driven Compressive Neuromorphic System for Cardiac Arrhythmia Detection
Jinbo Chen, Fengshi Tian, Jie Yang +1
Wearable electrocardiograph (ECG) recording and processing systems have been developed to detect cardiac arrhythmia to help prevent heart attacks. Conventional wearable systems, ho…
Multichannel Synthetic Preictal EEG Signals to Enhance the Prediction of Epileptic Seizures
Yankun Xu, Jie Yang, Mohamad Sawan
Epilepsy is a chronic neurological disorder affecting 1\% of people worldwide, deep learning (DL) algorithms-based electroencephalograph (EEG) analysis provides the possibility for…
Neuro-BERT: Rethinking Masked Autoencoding for Self-supervised Neurological Pretraining
Di Wu, Siyuan Li, Jie Yang +1
Deep learning associated with neurological signals is poised to drive major advancements in diverse fields such as medical diagnostics, neurorehabilitation, and brain-computer inte…
Bridging the Gap Between Patient-specific and Patient-independent Seizure Prediction via Knowledge Distillation
Di Wu, Jie Yang, Mohamad Sawan
Objective. Deep neural networks (DNNs) have shown unprecedented success in various brain-machine interface applications such as epileptic seizure prediction. However, existing appr…