Live Demonstration: A real-time event encoder for seizure monitoring on Neuromorphic Hardware

Long-term monitoring of biomedical signals is essential for modern data-driven clinical practices. This demonstration will present a low-power event-based pipeline for encoding and processing analog streaming signals in real time. This setup consists of an Analog Front-End (AFE) signal encoder directly integrated with a DYnamic Neuromorphic Asynchronous Processor (DYNAP-SE2). This system can produce a stream of spikes directly from analog sensors, for input to a Spiking Neural Network (SNN), implemented on the processor. By encoding correlated inputs and amplifying underlying partial synchronization patterns, we demonstrate the utilization of this setup in identifying evolving epileptic networks and detecting seizures.