Feb 17, 2021 � In this paper, we investigate the feasibility of using Memristive Deep Learning Systems (MDLSs) to perform real-time epileptic seizure�...
Most existing hardware implementations detect epileptic seizures using traditional Machine Learning (ML) al- gorithms such as Linear Least Squares (LLS) [7],�...
Feb 22, 2021 � In this paper, we investigate the feasibility of using Memristive Deep Learning Systems (MDLSs) to perform real-time epileptic seizure�...
May 26, 2021 � In order to protect patients with epilepsy and improve their quality of life, equipment deployed on the human body can be used to detect the�...
Jul 28, 2023 � The aim of the study is to assess the possibilities of predicting epileptiform activity using the neuronal activity data recorded from the�...
Missing: Real- Mobile
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... Deep Learning: Toward a Mobile System. @article ... Towards Memristive Deep Learning Systems for Real-Time Mobile Epileptic Seizure Prediction.
An in-memory memristive crossbar simulator for seizure detection and prediction. Python-based neural network training and MATLAB memristive crossbar components.
Jan 21, 2024 � This paper presents a neuromorphic Spiking Convolutional Transformer, named Spiking Conformer, to detect and predict epileptic seizure segments.
During the past two decades, epileptic seizure detection and prediction algorithms have evolved rapidly. However, despite significant performance improvements,�...
Missing: Real- Time Mobile
... Towards memristive deep learning systems for Real-Time mobile epileptic seizure prediction. IEEE International Symposium on Circuits and Systems (ISCAS) 2021:1–�...