Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin Mohd; Ahmad, Siti Anom; Islam, Mohd Shabiul; Escudero, Javier

doi:10.3390/s151129015

Cited by 127 publications

(71 citation statements)

References 85 publications

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“…For our analyses, we used the daubechies-4 (Db4) wavelet, a well-established wavelet basis used heavily in EEG research(Adeli et al, 2003; Al-Qazzaz et al, 2015). In particular, the Db4 wavelet shares similar features with individual spike-wave discharges, and its near symmetry improves the accuracy of time and frequency localization.…”

Section: Experimental Methodsmentioning

confidence: 99%

Absence seizure susceptibility correlates with pre-ictal β oscillations

Sorokin

Paz

Huguenard

2016

Journal of Physiology-Paris

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Absence seizures are generalized, cortico-thalamo-cortical (CTC) high power electroenecephalographic (EEG) or electrocorticographic (ECoG) events that initiate and terminate suddenly. ECoG recordings of absence seizures in animal models of genetic absence epilepsy show a sudden spike-wave-discharge (SWD) onset that rapidly emerges from normal ECoG activity. However, given that absence seizures occur most often during periods of drowsiness or quiet wakefulness, we wondered whether SWD onset correlates with pre-ictal changes in network activity. To address this, we analyzed ECoG recordings of both spontaneous and induced SWDs in rats with genetic absence epilepsy. We discovered that the duration and intensity of spontaneous SWDs positively correlate with pre-ictal 20–40 Hz (β) spectral power and negatively correlate with 4-7 Hz (Ø) power. In addition, the output of thalamocortical neurons decreases within the same preictal window of time. In separate experiments we found that the propensity for SWD induction was correlated with pre-ictal β power. These results argue that CTC networks undergo a pre-seizure state transition, possibly due to a functional reorganization of cortical microcircuits, which leads to the generation of absence seizures.

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Section: Experimental Methodsmentioning

confidence: 99%

Absence seizure susceptibility correlates with pre-ictal β oscillations

Sorokin

Paz

Huguenard

2016

Journal of Physiology-Paris

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“…It lies on the concept of mother wavelet (MWT), which is a function used to decompose and describe the analyzed data. The Symlets ('sym7') was the MWT used, due its high similarities and compatibilities with the EEG data on all scalp regions [39].…”

Section: Wavelets (Feat_wac Feat_wdc)mentioning

confidence: 99%

Multimodal Approach for Emotion Recognition Based on Simulated Flight Experiments

Roza

Postolache

2019

Sensors

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The present work tries to fill part of the gap regarding the pilots' emotions and their bio-reactions during some flight procedures such as, takeoff, climbing, cruising, descent, initial approach, final approach and landing. A sensing architecture and a set of experiments were developed, associating it to several simulated flights (N f lights = 13) using the Microsoft Flight Simulator Steam Edition (FSX-SE). The approach was carried out with eight beginner users on the flight simulator (N pilots = 8). It is shown that it is possible to recognize emotions from different pilots in flight, combining their present and previous emotions. The cardiac system based on Heart Rate (HR), Galvanic Skin Response (GSR) and Electroencephalography (EEG), were used to extract emotions, as well as the intensities of emotions detected from the pilot face. We also considered five main emotions: happy, sad, angry, surprise and scared. The emotion recognition is based on Artificial Neural Networks and Deep Learning techniques. The Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) were the main methods used to measure the quality of the regression output models. The tests of the produced output models showed that the lowest recognition errors were reached when all data were considered or when the GSR datasets were omitted from the model training. It also showed that the emotion surprised was the easiest to recognize, having a mean RMSE of 0.13 and mean MAE of 0.01; while the emotion sad was the hardest to recognize, having a mean RMSE of 0.82 and mean MAE of 0.08. When we considered only the higher emotion intensities by time, the most matches accuracies were between 55% and 100%.

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“…In 2015, Noor Kamal, Mohd Ali, Ahmad, Shabiul Islam and Escudero proposed selection of mother wavelet functions for multi-channel EEG signal analysis during a working memory task [62]. A comparative study to select the efficient mother wavelet basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory task recorded through electro-encephalography was performed.…”

Section: Regularitymentioning

confidence: 99%

Selection of Wavelet Basis Function for Image Compression – A Review

Sunkara¹

2019

ELCVIA

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Wavelets are being suggested as a platform for various tasks in image processing. The advantage of wavelets lie in its time frequency resolution. The use of different basis functions in the form of different wavelets made the wavelet analysis a destination for many applications. The performance of a particular technique depends on the wavelet coefficients arrived after applying the wavelet transform. The coefficients for a specific input signal depends on the basis functions used in the wavelet transform. Hence, in this paper toward this end, different basis functions and their features are presented. As many image comprssion algorithms base on wavelet transform, selection of basis function for image compression should be taken with care. In this paper, the factors influencing the performance of image compression are presented. In addition to this, a broad review of wavelets in image processing applications and selection of basis function for different image processing tasks are presented.

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Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

Cited by 127 publications

References 85 publications

Absence seizure susceptibility correlates with pre-ictal β oscillations

Absence seizure susceptibility correlates with pre-ictal β oscillations

Multimodal Approach for Emotion Recognition Based on Simulated Flight Experiments

Selection of Wavelet Basis Function for Image Compression – A Review

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