Two-stage wavelet shrinkage and EEG-EOG signal contamination model to realize quantitative validations for the artifact removal from multiresource biosignals
Tài liệu tham khảo
Urigüen, 2015, EEG artifact removal-state-of-the-art and guidelines, J. Neural Eng., 12, 031001, 10.1088/1741-2560/12/3/031001
Kamarajan, 2015, Advances in electrophysiological research, Alcohol Res.: Curr. Rev., 37, 53
Nicolas-Alonso, 2012, Brain computer interfaces, a review, Sensors, 12, 1211, 10.3390/s120201211
Sadasivan, 1996, Svd based technique for noise reduction in electroencephalographic signals, Signal Process., 55, 179, 10.1016/S0165-1684(96)00129-6
Vigário, 1997, Extraction of ocular artefacts from EEG using independent component analysis, Electroencephalogr. Clin. Neurophysiol., 103, 395, 10.1016/S0013-4694(97)00042-8
Joyce, 2004, Automatic removal of eye movement and blink artifacts from EEG data using blind component separation, Psychophysiology, 41, 313, 10.1111/j.1469-8986.2003.00141.x
Antoniadis, 1997, Wavelets in statistics: a review, J. Ital. Stat. Soc., 6, 97, 10.1007/BF03178905
Al-Fahoum, 2014, Methods of EEG signal features extraction using linear analysis in frequency and time-frequency domains, Int. Sch. Res. Notices
Jung, 2000, Removing electroencephalographic artifacts by blind source separation, Psychophysiology, 37, 163, 10.1111/1469-8986.3720163
Hyvärinen, 1999, Fast and robust fixed-point algorithms for independent component analysis, IEEE Trans. Neural Netw., 10, 626, 10.1109/72.761722
Picton, 2000, The correction of ocular artifacts: a topographic perspective, Clin. Neurophysiol., 111, 53, 10.1016/S1388-2457(99)00227-8
Makeig, 2011, EEG dynamics: an ICA perspective, vol. 3, 1
Akhtar, 2012, Employing spatially constrained ICA and wavelet denoising, for automatic removal of artifacts from multichannel EEG data, Signal Process., 92, 401, 10.1016/j.sigpro.2011.08.005
Vázquez, 2012, Blind source separation, wavelet denoising and discriminant analysis for EEG artefacts and noise cancelling, Biomed. Signal Process. Control, 7, 389, 10.1016/j.bspc.2011.06.005
Plöchl, 2012, Combining EEG and eye tracking: identification, characterization, and correction of eye movement artifacts in electroencephalographic data, Front. Hum. Neurosci., 6, 278, 10.3389/fnhum.2012.00278
Tyner, 1983
Noachtar, 1999, A glossary of terms most commonly used by clinical electroencephalographers and proposal for the report form for the EEG findings. The international federation of clinical neurophysiology, Electroencephalogr. Clin. Neurophysiol., Suppl. 52, 21
Smith, 2005, EEG in neurological conditions other than epilepsy: when does it help, what does it add?, J. Neurol. Neurosurg. Psychiatry, 76, ii8
Zou, 2012, Analysis of attention deficit hyperactivity disorder and control participants in EEG using ICA and PCA, vol. 7367, 403
Chen, 2001, Seizure frequency affects event-related potentials (p300) in epilepsy, J. Clin. Neurosci., 8, 442, 10.1054/jocn.2000.0908
Zhu, 2014, Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm, Comput. Methods Progr. Biomed., 115, 64, 10.1016/j.cmpb.2014.04.001
Loo, 2012, Clinical utility of EEG in attention-deficit/hyperactivity disorder: a research update, Neurotherapeutics, 9, 569, 10.1007/s13311-012-0131-z
Ting, 2008, EEG feature extraction based on wavelet packet decomposition for brain computer interface, Measurement, 41, 618, 10.1016/j.measurement.2007.07.007
Luvizotto, 2012, A wavelet-based neural model to optimize and read out a temporal population code, Front. Comput. Neurosci., 6, 21, 10.3389/fncom.2012.00021
Acharya, 2012, Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals, Int. J. Neural Syst., 22, 1250002, 10.1142/S0129065712500025
Verma, 2014, Multimodal fusion framework: a multiresolution approach for emotion classification and recognition from physiological signals, Neuroimage, 102, 162, 10.1016/j.neuroimage.2013.11.007
Faust, 2015, Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis, Seizure, 26, 56, 10.1016/j.seizure.2015.01.012
Donoho, 1993, Wavelet shrinkage and w.v.d.: a 10-minute tour, 109
Donoho, 1994, Ideal spatial adaptation by wavelet shrinkage, Biometrika, 81, 425, 10.1093/biomet/81.3.425
Donoho, 1995, Wavelet shrinkage: asymptopia?, J. R. Stat. Soc. Ser. B, 57, 301
Donoho, 1995, Adapting to unknown smoothness via wavelet shrinkage, J. Am. Stat. Assoc., 90, 1200, 10.1080/01621459.1995.10476626
Donoho, 1995, De-noising by soft-thresholding, IEEE Trans. Inf. Theory, 41, 613, 10.1109/18.382009
Coifman, 1995, Translation-invariant de-noising, vol. 103, 125
Donoho, 1998, Minimax estimation via wavelet shrinkage, Ann. Stat., 26, 879, 10.1214/aos/1024691081
Donoho, 1994, Threshold selection for wavelet shrinkage of noisy data, Proceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 1, A24, 10.1109/IEMBS.1994.412133
Gao, 1997, Waveshrink with firm shrinkage, Stat. Sin., 7, 855
Chipman, 1997, Adaptive bayesian wavelet shrinkage, J. Am. Stat. Assoc., 92, 1413, 10.1080/01621459.1997.10473662
Hu, 2002, Method of wavelet threshold denoising based on bayesian estimation, J. Infrared Millim. Waves, 21, 74
Bernas, 2008, Application of wavelet denoising to improve compression efficiency while preserving integrity of digital micrographs, J. Microscopy, 231, 81, 10.1111/j.1365-2818.2008.02019.x
Lang, 1996, Noise reduction using an undecimated discrete wavelet transform, Signal Process. Lett. IEEE, 3, 10, 10.1109/97.475823
Starck, 2007, The undecimated wavelet decomposition and its reconstruction, IEEE Trans. Image Process., 16, 297, 10.1109/TIP.2006.887733
A. Gyaourova, C. Kamath, I.K. Fodor, Undecimated wavelet transforms for image de-noising, Report, Lawrence Livermore National Lab., CA 18.
Raj, 2011, Denoising of medical images using undecimated wavelet transform, Proceedings of Recent Advances in Intelligent Computational Systems (RAICS), 483
Mamun, 2013, Effectiveness of wavelet denoising on electroencephalogram signals, J. Appl. Res. Technol., 11, 156, 10.1016/S1665-6423(13)71524-4
Kaushik, 2014, Biomedical signals analysis by DWT signal de-noising with neural networks, Res. J. Appl. Sci., 9, 244
Balamareeswaran, 2015, Denoising of EEG signals using discrete wavelet transform based scalar quantization, Biomed. Pharmacol. J., 8, 399, 10.13005/bpj/627
Khatun, 2016, Comparative study of wavelet-based unsupervised ocular artifact removal techniques for single-channel EEG data, IEEE J. Transl. Eng. Health Med., 4, 1, 10.1109/JTEHM.2016.2544298
Gholipour, 2010, Hardware implementation of lifting based wavelet transform, Proc. 2010 2nd International Conference on Signal Processing Systems (ICSPS) 1, 10.1109/ICSPS.2010.5555571
Jiang, 2010, Lifting wavelet packet transform based damage detection of composite plate structures, Proc. 2010 2nd International Conference on Signal Processing Systems (ICSPS) 3, 10.1109/ICSPS.2010.5555694
van der Laan, 2011, Accelerating wavelet lifting on graphics hardware using CUDA, IEEE Trans. Parallel Distrib. Syst., 22, 132, 10.1109/TPDS.2010.143
Cohen, 1993, Multiresolution analysis, wavelets, and fast algorithms on an interval, Comptes Rendus de l Académie des Sciences-Series I-Mathematics, 316, 417
Jansen, 2001
Nilsson, 1988, Corneal d.c. recordings of slow ocular potential changes such as the erg c-wave and the light peak in clinical work. equipment and examples of results, Documenta Ophthalmol., 68, 313, 10.1007/BF00156437
Lins, 1993, Ocular artifacts in EEG and event-related potentials I: Scalp topography, Brain Topogr., 6, 51, 10.1007/BF01234127
Picton, 2000, The correction of ocular artifacts: a topographic perspective, Clin. Neurophysiol., 111, 53, 10.1016/S1388-2457(99)00227-8
Luck, 2005
Keren, 2010, Saccadic spike potentials in gamma-band EEG: characterization, detection and suppression, Neuroimage, 49, 2248, 10.1016/j.neuroimage.2009.10.057
Wallstrom, 2004, Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods, Int. J. Psychophysiol., 53, 105, 10.1016/j.ijpsycho.2004.03.007
Dandekar, 2012, Neural saccadic response estimation during natural viewing, J. Neurophysiol., 107, 1776, 10.1152/jn.00237.2011
David, 2006, Mechanisms of evoked and induced responses in MEG/EEG, Neuroimage, 31, 1580, 10.1016/j.neuroimage.2006.02.034
Debatisse, 2005, Simultaneous multilobar electrocorticography (mEcoG) and scalp electroencephalography (scalp EEG) during intracranial vascular surgery: a new approach in neuromonitoring, Clin. Neurophysiol., 116, 2734, 10.1016/j.clinph.2005.08.011
Ray, 2007, Localizing value of scalp EEG spikes: a simultaneous scalp and intracranial study, Clin. Neurophysiol., 118, 69, 10.1016/j.clinph.2006.09.010
Ball, 2009, Signal quality of simultaneously recorded invasive and non-invasive EEG, Neuroimage, 46, 708, 10.1016/j.neuroimage.2009.02.028
Yamazaki, 2012, Comparison of dense array EEG with simultaneous intracranial EEG for interictal spike detection and localization, Epilepsy Res., 98, 166, 10.1016/j.eplepsyres.2011.09.007
Aghakhani, 2015, Co-localization between the bold response and epileptiform discharges recorded by simultaneous intracranial EEG-fMRI at 3 t, NeuroImage: Clin., 7, 755, 10.1016/j.nicl.2015.03.002
Ai, 2016, viewing area-sensitive influence of EOG artifacts revealed in the EEG topographic pattern analysis, Cogn. Neurodyn., 1
Long, 2014, Subsequent memory effect in intracranial and scalp EEG, Neuroimage, 84, 488, 10.1016/j.neuroimage.2013.08.052
Andrzejak, 2001, Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state, Phys. Rev. E Cover. Stat. Nonlinear Biol. Soft Matter Phys., 64, 061907, 10.1103/PhysRevE.64.061907
Department of Epileptology at the University Hospital of Bonn. EEG time series download, http://epileptologie-bonn.de/cms/ [online].
Stern, 1984, The endogenous eyeblink, Psychophysiology, 21, 22, 10.1111/j.1469-8986.1984.tb02312.x
Evinger, 1991, Eyelid movements. Mechanisms and normal data, Investig. Ophthalmol. Vis. Sci., 32, 387
Keren, 2010, Saccadic spike potentials in gamma-band EEG: characterization, detection and suppression, Neuroimage, 49, 2248, 10.1016/j.neuroimage.2009.10.057
Nason, 1995, The stationary wavelet transform and some statistical applications, vol. 103, 281
Pesquet, 1996, Time-invariant orthonormal wavelet representations, Proc. IEEE Trans. Signal Process., 44, 1964, 10.1109/78.533717
Freeman, 2006, Fine spatiotemporal structure of phase in human intracranial EEG, Clin. Neurophysiol., 117, 1228, 10.1016/j.clinph.2006.03.012
Borghini, 2012, Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness, Neurosci. Biobehav. Rev., 44, 58, 10.1016/j.neubiorev.2012.10.003
Ilmoniemi, 2008, TMS and electroencephalography: methods and current advances, 593
Nason, 1995, vol. 103, 261
Berg, 1991, Dipole models of eye movements and blinks, Electroencephalogr. Clin. Neurophysiol., 79, 36, 10.1016/0013-4694(91)90154-V
Berg, 1994, A multiple source approach to the correction of eye artifacts, Electroencephalogr. Clin. Neurophysiol., 90, 229, 10.1016/0013-4694(94)90094-9
Singh, 2017, vol. 2017, 1861645
Dey, 2016
Singh, 2017, The detection of the rise to stand movements using bereitschaftspotential from scalp electroencephalography (EEG), SICE J. Control Meas. Syst. Integr., 10, 149, 10.9746/jcmsi.10.149