Complexity analysis of the magnetoencephalogram background activity in Alzheimer's disease patients.
暂无分享,去创建一个
Roberto Hornero | Daniel Abásolo | Alberto Fernández | Miguel López | Carlos Gómez | D. Abásolo | R. Hornero | Carlos Gómez | Alberto Fernández | M. López | A. Fernández
[1] Erik W. Jensen,et al. EEG complexity as a measure of depth of anesthesia for patients , 2001, IEEE Trans. Biomed. Eng..
[2] D. Ruelle,et al. Fundamental limitations for estimating dimensions and Lyapunov exponents in dynamical systems , 1992 .
[3] Soo-Yong Kim,et al. Non-linear dynamical analysis of the EEG in Alzheimer's disease with optimal embedding dimension. , 1998, Electroencephalography and clinical neurophysiology.
[4] Ole Jensen,et al. Altered generation of spontaneous oscillations in Alzheimer's disease , 2005, NeuroImage.
[5] H. Kaiser. The Application of Electronic Computers to Factor Analysis , 1960 .
[6] Seung-Hyun Jin,et al. EEG in schizophrenic patients: mutual information analysis , 2002, Clinical Neurophysiology.
[7] G. Edelman,et al. A measure for brain complexity: relating functional segregation and integration in the nervous system. , 1994, Proceedings of the National Academy of Sciences of the United States of America.
[8] Jaeseung Jeong. EEG dynamics in patients with Alzheimer's disease , 2004, Clinical Neurophysiology.
[9] Roberto Hornero,et al. Analysis of EEG background activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure. , 2006, Medical engineering & physics.
[10] José María Amigó,et al. Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity , 2004, Neural Computation.
[11] László Fésüs,et al. Transglutaminase‐mediated crosslinking of neural proteins in Alzheimer's disease and other primary dementias , 2002 .
[12] H Sattel,et al. Discrimination of Alzheimer's disease and normal aging by EEG data. , 1997, Electroencephalography and clinical neurophysiology.
[13] J. Calabrese,et al. Quantification of occipital EEG changes in Alzheimer's disease utilizing a new metric: The fractal dimension , 1994, Biological Psychiatry.
[14] EEG complexity measurement of focal ischemic cerebral injury , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).
[15] K. Coburn,et al. EEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures. , 1994, Electroencephalography and clinical neurophysiology.
[16] B. Rockstroh,et al. Focal temporoparietal slow activity in Alzheimer’s disease revealed by magnetoencephalography , 2002, Biological Psychiatry.
[17] R. Cattell. The Scree Test For The Number Of Factors. , 1966, Multivariate behavioral research.
[18] Radhakrishnan Nagarajan,et al. Quantifying physiological data with Lempel-Ziv complexity-certain issues , 2002, IEEE Transactions on Biomedical Engineering.
[19] Brian J Cummings,et al. β-amyloid deposition and other measures of neuropathology predict cognitive status in Alzheimer's disease , 1996, Neurobiology of Aging.
[20] Jinghua Xu,et al. Information transmission in human cerebral cortex , 1997 .
[21] Robert X. Gao,et al. Complexity as a measure for machine health evaluation , 2004, IEEE Transactions on Instrumentation and Measurement.
[22] Xu-Sheng Zhang,et al. Derived fuzzy knowledge model for estimating the depth of anesthesia , 2001, IEEE Transactions on Biomedical Engineering.
[23] B. Reisberg. Functional assessment staging (FAST). , 1988, Psychopharmacology bulletin.
[24] C. J Stam,et al. A neural complexity measure applied to MEG data in Alzheimer's disease , 2003, Clinical Neurophysiology.
[25] F Angeleri,et al. EEG spectral analysis in vascular and Alzheimer dementia. , 1995, Electroencephalography and clinical neurophysiology.
[26] J. Trojanowski. The cellular and molecular correlates of cognitive impairments in the Alzheimer's disease brain , 1996, Neurobiology of Aging.
[27] Xu-Sheng Zhang,et al. Detecting ventricular tachycardia and fibrillation by complexity measure , 1999, IEEE Transactions on Biomedical Engineering.
[28] S. Folstein,et al. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.
[29] Schuster,et al. Easily calculable measure for the complexity of spatiotemporal patterns. , 1987, Physical review. A, General physics.
[30] 秦 浩起,et al. Characterization of Strange Attractor (カオスとその周辺(基研長期研究会報告)) , 1987 .
[31] Soo-Yong Kim,et al. Nonlinear Dynamic Analysis of the EEG in Patients with Alzheimer’s Disease and Vascular Dementia , 2001, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[32] Brian J Cummings,et al. Beta-amyloid deposition and other measures of neuropathology predict cognitive status in Alzheimer's disease. , 1996, Neurobiology of aging.
[33] G. Edelman,et al. Complexity and coherency: integrating information in the brain , 1998, Trends in Cognitive Sciences.
[34] R. Ilmoniemi,et al. Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .
[35] Maria V. Sanchez-Vives,et al. Application of Lempel–Ziv complexity to the analysis of neural discharges , 2003, Network.
[36] L Huang,et al. Prediction of response to incision using the mutual information of electroencephalograms during anaesthesia. , 2003, Medical engineering & physics.
[37] Steeve Zozor,et al. On Lempel–Ziv complexity for multidimensional data analysis , 2005 .
[38] Abraham Lempel,et al. On the Complexity of Finite Sequences , 1976, IEEE Trans. Inf. Theory.
[39] P. Grassberger,et al. Measuring the Strangeness of Strange Attractors , 1983 .
[40] M. Folstein,et al. Clinical diagnosis of Alzheimer's disease , 1984, Neurology.
[41] M. Zweig,et al. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. , 1993, Clinical chemistry.
[42] Hongkui Jing,et al. Comparison of human ictal, interictal and normal non-linear component analyses , 2000, Clinical Neurophysiology.
[43] H. Abarbanel,et al. Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.
[44] P. Grassberger,et al. Characterization of Strange Attractors , 1983 .
[45] X. -S. Zhang,et al. Predicting movement during anaesthesia by complexity analysis of electroencephalograms , 1999, Medical & Biological Engineering & Computing.
[46] S. Rombouts,et al. Investigation of EEG non-linearity in dementia and Parkinson's disease. , 1995, Electroencephalography and clinical neurophysiology.
[47] N Radhakrishnan,et al. Estimating regularity in epileptic seizure time-series data. A complexity-measure approach. , 1998, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.
[48] C. Stam,et al. Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls , 1999, Clinical Neurophysiology.
[49] A. Kolmogorov. Three approaches to the quantitative definition of information , 1968 .