One dimensional local binary patterns of electroencephalogram signals for detecting Alzheimer's disease
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Norman Poh | Santosh Tirunagari | Daniel Abásolo | Samaneh Kouchaki | S. Kouchaki | N. Poh | D. Abásolo | Santosh Tirunagari
[1] Yanhui Guo,et al. Time–frequency texture descriptors of EEG signals for efficient detection of epileptic seizure , 2016, Brain Informatics.
[2] David Windridge,et al. Windowed DMD as a microtexture descriptor for finger vein counter-spoofing in biometrics , 2015, 2015 IEEE International Workshop on Information Forensics and Security (WIFS).
[3] Matti Pietikäinen,et al. Gray Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2000, ECCV.
[4] W. Szurhaj,et al. Is long-term electroencephalogram more appropriate than standard electroencephalogram in the elderly? , 2017, Clinical Neurophysiology.
[5] John J. Soraghan,et al. 1-D Local binary patterns based VAD used INHMM-based improved speech recognition , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).
[6] Yilmaz Kaya,et al. 1D-local binary pattern based feature extraction for classification of epileptic EEG signals , 2014, Appl. Math. Comput..
[7] Matti Pietikäinen,et al. A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..
[8] David Windridge,et al. Detection of Face Spoofing Using Visual Dynamics , 2015, IEEE Transactions on Information Forensics and Security.
[9] Santosh Tirunagari,et al. Local binary patterns as a feature descriptor in alignment-free visualisation of metagenomic data , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).
[10] Paolo Maria Rossini,et al. Searching for signs of aging and dementia in EEG through network analysis , 2017, Behavioural Brain Research.
[11] Arab Ali Chérif,et al. Time-frequency image descriptors-based features for EEG epileptic seizure activities detection and classification , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[12] H. Möller,et al. Rediscovery of the case described by Alois Alzheimer in 1911: historical, histological and molecular genetic analysis , 1997, Neurogenetics.
[13] John J. Soraghan,et al. Local binary patterns for 1-D signal processing , 2010, 2010 18th European Signal Processing Conference.
[14] J. Morris,et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.
[15] Roberto Hornero,et al. Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy , 2005, Clinical Neurophysiology.
[16] C. Stam,et al. Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field , 2005, Clinical Neurophysiology.
[17] L. Berg,et al. Frequency analysis of the resting awake EEG in mild senile dementia of Alzheimer type. , 1983, Electroencephalography and clinical neurophysiology.
[18] J. Rabey,et al. Quantitative EEG After Brain Stimulation and Cognitive Training in Alzheimer Disease , 2017, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[19] M. Riepe,et al. Memantine in Moderate-to-severe Alzheimer's Disease , 2006 .
[20] B. Miller,et al. CME Practice parameter : Diagnosis of dementia ( an evidence-based review ) Report of the Quality Standards Subcommittee of the American Academy of Neurology , 2001 .
[21] Jaeseung Jeong. EEG dynamics in patients with Alzheimer's disease , 2004, Clinical Neurophysiology.
[22] Roberto Hornero,et al. Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer’s disease patients , 2008, Medical & Biological Engineering & Computing.
[23] Samantha Simons,et al. Univariate and Multivariate Generalized Multiscale Entropy to Characterise EEG Signals in Alzheimer's Disease , 2017, Entropy.
[24] 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.
[25] Matti Pietikäinen,et al. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[26] D. Abásolo,et al. Entropy analysis of the EEG background activity in Alzheimer's disease patients , 2006, Physiological measurement.
[27] Samantha Simons,et al. Classification of Alzheimer's disease from quadratic sample entropy of electroencephalogram. , 2015, Healthcare technology letters.