Event driven neural network on a mixed signal neuromorphic processor for EEG based epileptic seizure detection.

ABSTRACT: Long-term monitoring of biomedical signals is essential for the modern clinical management of neurological conditions such as epilepsy. However, developing wearable systems that are able to monitor, analyze, and detect epileptic seizures with long-lasting operation times using current technologies is still an open challenge. Brain-inspired spiking neural networks (SNNs) represent a promising signal processing and computing framework as they can be deployed on ultra-low power neuromorphic computing systems, for this purpose. Here, we introduce a novel SNN architecture, co-designed and validated on a mixed-signal neuromorphic chip, that shows potential for always-on monitoring of epileptic activity. We demonstrate how the hardware implementation of this SNN captures the phenomenon of partial

SUBMITTER: Bartels J 

PROVIDER: S-EPMC12059009 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature