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EEG Signal Processing and Machine Learning. Saeid Sanei
Читать онлайн.Название EEG Signal Processing and Machine Learning
Год выпуска 0
isbn 9781119386933
Автор произведения Saeid Sanei
Жанр Программы
Издательство John Wiley & Sons Limited
8 Chapter 8Figure 8.1 Cross‐spectral coherence for a set of three electrode EEGs, one s...Figure 8.2 Connectivity pattern imposed in the generation of simulated signa...Figure 8.3 The result of application of S‐transform to a set of simulated so...Figure 8.4 Representation of node k and its neighbouring nodes for diffusion...Figure 8.5 The use of brain connectivity for diffusion adaptation filtering....Figure 8.6 An illustration of brain connectivity pattern. EEG signals collec...Figure 8.7 Variation of combination weights (brain connectivity parameters) ...Figure 8.8 Example of modelling the multirelational social network as a tens...Figure 8.9 Conceptual model of tensors decomposition for linked multiway BSS...
9 Chapter 9Figure 9.1 Four P100 components: (a) two normal P100 and (b) two abnormal P1...Figure 9.2 The average ERP signals for normal and alcoholic subjects. The cu...Figure 9.3 Typical P3a and P3b subcomponents of a P300 ERP signal viewed at ...Figure 9.4 Block diagram of the ICA‐based algorithm proposed in [43]. Three ...Figure 9.5 Synthetic ERP templates including a number of delayed Gaussian an...Figure 9.6 The results of the ERP detection algorithm [47]. The scatter plot...Figure 9.7 The average P3a and P3b for a schizophrenic patient (a) and (b) r...Figure 9.8 Construction of an ERP signal using a WN. The nodes in the hidden...Figure 9.9 Dynamic variations of ERP signals. (a) First stimulus and (b) twe...Figure 9.10 Estimated ERPs by applying KF and PF, (a) and (b) ERP latency ov...Figure 9.11 Estimated (a) amplitude and (b) latency of P3a (bold line) and P...Figure 9.12 The chirplets extracted from a simulated EEG‐type waveform [75]....
10 Chapter 10Figure 10.1 The magnetic field B at each electrode is calculated with respec...Figure 10.2 The magnetic field B at each electrode is calculated with respec...Figure 10.3 The steps in using MRI data to build up a head model. (a) Origin...Figure 10.4 Localization results for (a) the schizophrenic patients and (b) ...Figure 10.5 Flow diagram of inverse methods used for EEG source localization...Figure 10.6 The locations of the P3a and P3b sources for five patients in a ...Figure 10.7 The locations of the P3a and P3b sources for five healthy indivi...Figure 10.8 Localization plot for one source uncorrelated with other sources...Figure 10.9 Percentage of successful localizations for various SNRs for the ...Figure 10.10 Percentage of successful localizations for various SNRs for the...Figure 10.11 Localization plot for P3a, circles, o, and P3b, squares, □, for...Figure 10.12 Localization plot for the P3a, circles, o, and P3b, squares, □,...Figure 10.13 Topographies or power profiles of real MEG data obtained using ...
11 Chapter 11Figure 11.1 Two segments of EEG signals each from a patient suffering: (a) g...Figure 11.2 The CNN architecture proposed in [48]. The first layer (Conv2D) ...Figure 11.3 (a) A sample of IED recorded using intracranial foramen ovale el...Figure 11.4 The main three different neonate seizure patterns. (a) Low ampli...Figure 11.5 Eight seconds of EEG signals from eight out of 16 scalp electrod...Figure 11.6 The four independent components obtained by applying BSS to the ...Figure 11.7 The smoothed λ1 evolution over time for two intracranial electro...Figure 11.8 Smoothed λ1 evolution over time for two independent components I...Figure 11.9 (a) A segment of eight seconds of EEG signals (with zero mean) f...Figure 11.10 (a) Intracranial EEG analysis: three‐point smoothed λ1 evolutio...Figure 11.11 Smoothed λ1 evolution for a focal seizure estimated from the in...Figure 11.12 (a) Smoothed λ1 evolution of four intracranial electrodes for a...Figure 11.13 The schematic for the proposed LRCN seizure prediction algorith...Figure 11.14 Foramen ovale holes where the subdural electrodes are inserted ...Figure 11.15 Basal (left) and lateral (right) X‐ray images showing the inser...Figure 11.16 A segment of concurrent multichannel data. The first 22 signals...Figure 11.17 The scoring histogram provided by an expert in epilepsy.Figure 11.18 Classification accuracy of the ensemble classifier with respect...Figure 11.19 The ratio of detected IEDs (from the scalp EEG), to the total n...Figure 11.20 Detected scalp‐invisible IEDs with true positive on the top and...Figure 11.21 Examples of single‐channel reconstructed intracranial signals f...Figure 11.22 Topology of the DNN for mapping scalp to iEEGs. X is the scalp ...Figure 11.23 A schematic comparison between the proposed method (left) and a...Figure 11.24 Estimation of iEEG for two IED segments and a non‐IED segment (...Figure 11.25 A segment of EEG signals affected by the scanner ballistocardio...Figure 11.26 Schematic diagram of the topographic map correlation procedure....
12 Chapter 12Figure 12.1 Exemplar EEG signals recorded during drowsiness.Figure 12.2 During Stage III sleep, 26 s of brain waves were recorded.Figure 12.3 Twenty‐six seconds of brain waves recorded during the REM state....Figure 12.4 A typical concentration of melatonin in a healthy adult man (ext...Figure 12.5 Typical waveforms for (a) spindles and (b) K‐complexes, adopted ...Figure 12.6 Time–frequency energy map of 20 seconds epochs of sleep EEG in d...Figure 12.7 Block diagram of the sleep scoring system proposed in [34].Figure 12.8 The scoring result of the proposed system in [34] (bottom) compa...Figure 12.9 I × K matrix X is converted to tensor
13 Chapter 13Figure 13.1 Inter‐hemisphere coherency of beta, alpha, and theta rhythms; to...Figure 13.2 Inter‐hemisphere phase synchronization of beta, alpha, and theta...Figure 13.3 Tracking variability of P3a and P3b before and during fatigue; t...Figure 13.4 Comparison of three methods (spatial PCA, exact match and mismat...Figure 13.5 (a) Single‐trial ERPs (40 trials related to the infrequent tones...Figure 13.6 Selection of reference signals for P3a and P3b. In each row, the...Figure 13.7 Scalp projections of P3a (top row) and P3b (bottom row) in four ...Figure 13.8 Forty single‐trial ERPs and their average from the Cz channel be...Figure 13.9 Forty single‐trial ERPs and their average from the Cz channel du...Figure 13.10 The ERP achieved by averaging 40 EEG trials before and during t...Figure 13.11 The estimated scalp projections of P3a (top row) and P3b (botto...Figure 13.12 The estimated scalp projections of P3a (top row) and P3b (botto...Figure 13.13 Theta phase synchronization of F3–F4: (a) before stimulus and (...Figure 13.14 Alpha phase synchronization of C3–C4: (a) before stimulus and (...Figure 13.15 Beta phase synchronization of F3–F4: (a) before stimulus and (b...Figure 13.16 Two‐stage PCANet block diagram proposed in [55].
14 Chapter 14Figure 14.1 The limbic system and the location of the amygdala.Figure 14.2 The generators of respiration‐related anxiety potentials are in ...Figure 14.3 Valence–arousal space showing high and low positive and negative...Figure 14.4 Emotion neural circuitry regions involved in emotion regulation....Figure 14.5 Direct and indirect pathways to the amygdala.Figure 14.6 Time course of an EPN and its corresponding topography images [9...Figure 14.7 Time course of the late positive potential; grand‐averaged ERP w...Figure 14.8 Olfactory bulb.Figure 14.9 Group comparison between anterior and posterior P300 amplitudes ...Figure 14.10 Negative and positive magnitudes of activity for the main regio...
15 Chapter 15Figure 15.1 Distribution of the MEG sensors into left central (LC), anterior...Figure 15.2 Block diagram of the spectral coherency, c(f), measure.Figure 15.3 (a) A 10 second segment of one EMG channel and (b) its correspon...Figure 15.4 Reference selection using the k‐means algorithm.Figure 15.5 Spectral coherency levels without (left) and with (right) region...Figure 15.6 ERPs recorded using the Cz electrode for (a) healthy and (b) AD ...Figure 15.7 Mean GC magnitudes across subjects for all links in control, AD–...Figure 15.8 Results of the multitask diffusion adaptation method in [5] for ...Figure 15.9 Ten brain regions used to estimate