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Method for automatic and unsupervised classification of high-frequency oscillations in physiological recordings.
Problem:
Automatic detection and classification of high frequency oscillations (HFO) data for use in clinical diagnosis and therapy has been limited. Currently, researchers visually inspect for high frequency oscillations.
Solution:
An algorithm to automatically extract quantitative local seizure information from multielectrode data. The automated HFO detection and classification algorithm is comprised of three major stages:
Inventor:
Brian Litt, MD, Department of Neurology
Advantages:
Applications:
Stage of Development:
Intellectual Property:
Published U.S. Patent Application US20120245481
Reference Media:
Blanco, et al. 2010. “Unsupervised classification of high-frequency oscillations in human neocortical epilepsy and control patients.” J Neurophysiol, 104(5) 2900-2912.
Docket # X5675