Data processing: measuring – calibrating – or testing – Measurement system – Performance or efficiency evaluation
Reexamination Certificate
2007-08-28
2007-08-28
Raymond, Edward (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system
Performance or efficiency evaluation
C702S190000
Reexamination Certificate
active
10673329
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. Multiple dynamical profiles are then generated for each spatio-temporal response, where each of the multiple dynamical profiles correspond to a different one of multiple dynamical parameters. Over a period of time, a determination is made as to whether a certain level of dynamic entrainment and/or disentrainment exists between the dynamical profiles associated with a selected one or a selected combination of dynamical parameters. Seizure warnings and/or predictions are provided based on this determination.
REFERENCES:
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: 6484132 (2002-11-01), Hively et al.
patent: 6507754 (2003-01-01), Le Van Quyen et al.
patent: 2003/0065535 (2003-04-01), Karlov et al.
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, 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).
Chaovalitwongse Wanpracha A.
Dance Linda
Iasemidis Leonidas D.
Pardalos Panos M.
Sackellares James Chris
Arizona Board of Regents
Charioui Mohamed
Raymond Edward
University of Florida Research Foundation Inc.
Woodcock & Washburn LLP
LandOfFree
Multi-dimensional multi-parameter 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 Multi-dimensional multi-parameter time series processing for..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Multi-dimensional multi-parameter time series processing for... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3885203