Information for Paper ID 6297
Paper Information:
Paper Title: A Neuromorphic Device for Detecting High-Frequency Oscillations in Human iEEG 
Student Contest: No 
Affiliation Type: Academia 
Keywords: Electrophysiological signals, Neural-recording, Event-based processing, Epilepsy, intracranial EEG, Biomarker 
Abstract: Among diagnostic biomarkers, high frequency oscillations in human iEEG are used to identify epileptogenic brain tissue during epilepsy surgery. However, current methods typically analyse the raw data offline using complex time-consuming algorithms. We developed a compact neuromorphic sensory-processing system-on-chip that can monitor the iEEG signals and detect high frequency oscillations in real-time using spiking neural networks. To this end, we present an integrated device with an analog front-end that can extract predefined spectral features and encode them as address-events, and a neuromorphic processor core that implements a network of integrate and fire neurons with dynamic synapses. 
Track ID:
Track Name: Bio-electronics- Bio-inspired and Bio-engineering Circuits & Systems 
Final Decision: Accept as Lecture 
Session Name: Biomedical Applications (Lecture)