RETRACTED ARTICLE: Epileptic seizure detection by analyzing high dimensional phase space via Poincaré section
暂无分享,去创建一个
[1] Pedro J. García-Laencina,et al. Efficient feature selection and linear discrimination of EEG signals , 2013, Neurocomputing.
[2] Ramaswamy Palaniappan,et al. Effects of Hidden Unit Sizes and Autoregressive Features in Mental Task Classification , 2005, IEC.
[3] J. Chae,et al. Nonlinear analysis of the EEG of schizophrenics with optimal embedding dimension. , 1998, Medical engineering & physics.
[4] O. Farooq,et al. Automated seizure detection in scalp EEG using multiple wavelet scales , 2012, 2012 IEEE International Conference on Signal Processing, Computing and Control.
[5] Qi Xu,et al. Fuzzy support vector machine for classification of EEG signals using wavelet-based features. , 2009, Medical engineering & physics.
[6] Min Wang,et al. Automatic detection of interictal epileptiform discharges based on time-series sequence merging method , 2013, Neurocomputing.
[7] C. M. Michel,et al. Temporal and spatial determination of EEG-seizure onset in the frequency domain , 2000, Clinical Neurophysiology.
[8] Min-You Chen,et al. Phase space reconstruction for improving the classification of single trial EEG , 2014, Biomed. Signal Process. Control..
[9] Aggelos K. Katsaggelos,et al. Analysis of High-Dimensional Phase Space via Poincaré Section for Patient-Specific Seizure Detection , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[10] Tarik Al-Ani,et al. Phase space and power spectral approaches for EEG-based automatic sleep-wake classification in humans: A comparative study using short and standard epoch lengths , 2013, Comput. Methods Programs Biomed..
[11] Kumpati S. Narendra,et al. Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.
[12] F. Takens. Detecting strange attractors in turbulence , 1981 .
[13] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[14] Jae-Kwon Kim,et al. Classification of normal and epileptic seizure EEG signals using wavelet transform, phase-space reconstruction, and Euclidean distance , 2014, Comput. Methods Programs Biomed..
[15] D. Looney,et al. Time-Frequency Analysis of EEG Asymmetry Using Bivariate Empirical Mode Decomposition , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[16] Yusuf Uzzaman Khan,et al. Feature extraction and classification of EEG for automatic seizure detection , 2011, 2011 International Conference on Multimedia, Signal Processing and Communication Technologies.
[17] Jin Wu-yin. Implementation method of brain-computer interface system based on Fourier transform , 2008 .
[18] Boualem Boashash,et al. A review of time-frequency matched filter design with application to seizure detection in multichannel newborn EEG , 2014, Digit. Signal Process..
[19] R. Temam. Infinite Dimensional Dynamical Systems in Mechanics and Physics Springer Verlag , 1993 .
[20] Wim Van Paesschen,et al. Incorporating structural information from the multichannel EEG improves patient-specific seizure detection , 2012, Clinical Neurophysiology.
[21] C. Stam,et al. Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field , 2005, Clinical Neurophysiology.