Year: 2007
Type: article
Abstract: Estimation of the Hurst parameter provides information about the memory range or correlations (long vs. short) of processes (time-series).A new application for the Hurst parameter, real-time event detection, is identified.Hurst estimates using rescaled range, dispersional and bridgedetrended scaled windowed variance analyses of seizure time-series recorded from human subjects reliably detect their onset, termination and intensity.Detection sensitivity is unaltered by signal decimation and window size increases.The high sensitivity to brain state changes, ability to operate in real time and small computational requirements make Hurst parameter estimation using any of these three methods well suited for implementation into miniature implantable devices for contingent delivery of anti-seizure therapies.
Authors: Mark G. Frei, Ivan Osorio
Institution: University of Kansas Medical Center
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W1969375897