학술논문

A Memristor-Inspired Computation for Epileptiform Signals in Spheroids
Document Type
Working Paper
Source
AICAS, Hangzhou, China, 2023, pp. 1-5
Subject
Electrical Engineering and Systems Science - Signal Processing
Computer Science - Artificial Intelligence
Language
Abstract
In this paper we present a memristor-inspired computational method for obtaining a type of running spectrogram or fingerprint of epileptiform activity generated by rodent hippocampal spheroids. It can be used to compute on the fly and with low computational cost an alert-level signal for epileptiform events onset. Here, we describe the computational method behind this fingerprint technique and illustrate it using epileptiform events recorded from hippocampal spheroids using a microelectrode array system.
Comment: published in 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)