Optimization of multi-dimensional time series processing for...

Details Optimization of multi-dimensional time series processing for... Optimization of multi-dimensional time series processing for...

2008-05-13

2008-05-13

Nasser, Robert L (Department: 3735)

Surgery

Diagnostic testing

Detecting brain electric signal

Reexamination Certificate

active

10648354

ABSTRACT:
Characterizing the behavior of a chaotic, multi-dimensional system is achieved by measuring each of a number of signals associated with the system, and generating therefrom, a spatio-temporal response based on each signal. Chaoticity profiles are then generated for each spatio-temporal response. Over a period of time, a determination is made as to whether a certain level of dynamic entrainment and/or disentrainment exists between the chaoticity profiles associated with one or more critical channel groups of a selected predictor, where a predictor represents a given number of critical channel groups “x”, a given number of channels per group “y”, and a total number of channels N. Characterizing the behavior of the system is based on this determination.

REFERENCES:
patent: 5365939 (1994-11-01), Ochs
patent: 5857978 (1999-01-01), Hively et al.
patent: 5995868 (1999-11-01), Dorfmeister et al.
patent: 6061593 (2000-05-01), Fischell et al.
patent: 6304775 (2001-10-01), Iasemidis et al.
patent: 6507754 (2003-01-01), Le Van Quyen et al.
patent: WO 01/21067 (2001-03-01), None
Iasemidis et al., “Phase Space Topography of the Electrocorticogram and the Lyapunov Exponent in Partial Seizures,” Brain Topography, vol. 2, No. 3, pp. 187-201 (1990).
Pincus, “Approximate Entropy as a Measure of System Complexity,” Proceedings of the National Academy of Science of the United States of America, vol. 88, pp. 2297-2301 (1991).
J.C. Sackellares et al., “Epileptic Seizures as Neural Resetting Mechanisms,” Epilepsia, vol. 38, Suppl. 3, p. 189, (1997).
L. D. Iasemidis et al., “Dynamical Resetting of Human Brain at Epileptic Seizures: Application of Nonlinear Dynamics and Global Optimization Techniques,” IEEE Transactions on Biomedical Engineering, vol. 51, No. 3, pp. 493-506, (2004).
Wolf et al., “Determining Lyapunov Exponents from a Time Series,” Physica D., vol. 16D, pp. 285-317 (1985).
Eckmann et al. “Lyapunov Exponents from Time Series,” Physical Review A, vol. 34, No. 6, pp. 4971-4972 (1986).
Iasemidis et al., “Adaptive Epileptic Seizure Prediction System,” IEEE Transactions in Biomedical Engineering, vol. 50, No. 5, pp. 616-627, (2003).
Iasemidis et al., “Prediction of Human Epileptic Seizures Based on Optimization and Phase Changes of Brain Electrical Activity,” Optimization Methods and Software, vol. 18, No. 1, pp. 81-104, (2003).
Iasemidis et al., “Seizure Warning Algorithm Based on Spatiotemporal Dynamics of Intracranial EEG,” Mathematical Programming, vol. 101, No. 2, pp. 365-385, (2004).

Affiliated with

Also associated with

Rating

Optimization of multi-dimensional time series processing for... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Optimization of multi-dimensional time series processing for..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optimization of multi-dimensional time series processing for... will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3921241