Search Results - (( using eeg method algorithm ) OR ( simulation optimization method algorithm ))

Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
Get full text
Get full text
Get full text

Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

“…Results The method was tested with both simulated and real EEG data of 11 participants. …”
Get full text
Get full text

Feature Selection using Angle Modulated Simulated Kalman Filter for Peak Classification of EEG Signals by Asrul, Adam, Zuwairie, Ibrahim, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Marizan, Mubin, Ismail, Saad

“…Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. …”
Get full text
Get full text
Get full text

The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
Get full text
Get full text

Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M., Saad, I.

“…Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. …”
Get full text
Get full text
Get full text

A Time-Domain Subspace Technique for Estimating Visual Evoked Potential Latencies by Yusoff, Mohd Zuki, Kamel, Nidal

“…Further, GSA has been compared with a third-order correlation (TOC) method, using both realistic simulation and real patient data gathered in a hospital. …”
Get full text
Get full text
Get full text

A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise by Yusoff, Mohd Zuki, Hussin, Fawnizu Azmadi

“…SNR values can be as low as -10 dB in real clinical environments. The simulation results produced by the post-modified SSA2 algorithm, show a higher degree of consistencies in detecting the VEP's P100, P200, and P300 peaks, in comparisons to the pre-modified SSA1 method. …”
Get full text
Get full text
Get full text

Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…Future studies are envisioned to investigate EEG markers of pain in other clinical states, aiming to generalize the use of EEG as an objective method of pain assessment. …”
Get full text
Get full text
Get full text

Eeg-Based Person Identification Using Multi-Levelwavelet Decomposition With Multi-Objective Flower Pollination Algorithm by Yahya Alyasseri, Zaid Abdi Alkareem

“…The proposed method is tested using two standard EEG datasets, namely, Kiern’s and Motor Movement/Imagery.…”
Get full text
Get full text

Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm by Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.

“…The EEG signal is most useful for clinical diagnosis and in biomedical research. …”
Get full text

Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

“…High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.…”
Get full text
Get full text

Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

“…High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.…”
Get full text
Get full text
Get full text

Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

“…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
Get full text

EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

“…Since MEMD method is a data-driven method which meets the criteria to be applied for EEG processing, therefore this method was employed to extract EEG epileptic spike features. …”
Get full text
Get full text

BRAIN ACTIVITIES FOR MOTOR MOVEMENT by ., WAFAA ELSAYED ELBASTY

“…The research covers the procedure of designing the BCI algorithm and this consists of three stages firstly recording EEG brain signals, secondly EEG signals pre-processing, Last stage is EEG signals classification. …”
Get full text
Get full text

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

“…The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. …”
Get full text
Get full text

Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

“…For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. …”
Get full text
Get full text

Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

“…For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. …”
Get full text
Get full text

EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

“…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
Get full text
Get full text

EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

“…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
Get full text
Get full text