An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
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2021-05-25
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Journal Article
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yes
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Abstract
The analysis of biomedical signals for clinical studies and therapeutic applications can benefit from embedded devices that can process these signals locally and in real-time. An example is the analysis of intracranial EEG (iEEG) from epilepsy patients for the detection of High Frequency Oscillations (HFO), which are a biomarker for epileptogenic brain tissue. Mixed-signal neuromorphic circuits offer the possibility of building compact and low-power neural network processing systems that can analyze data on-line in real-time. Here we present a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing iEEG, and show how it can reliably detect HFO, thereby achieving state-of-the-art accuracy, sensitivity, and specificity. This is a first feasibility study towards identifying relevant features in iEEG in real-time using mixed-signal neuromorphic computing technologies.
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published
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Volume
12 (1)
Pages / Article No.
3095
Publisher
Nature
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Subject
Biosensors; Network models; Neural decoding
Organisational unit
09699 - Indiveri, Giacomo / Indiveri, Giacomo