A Memristor-Inspired Computation for Epileptiform Signals in Spheroids
arXiv:2307.04607 · doi:10.1109/AICAS57966.2023.10168611
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.
published in 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)