Zunairah Hj Murat

EEG-based Stress Features Using Spectral Centroids Technique and k-Nearest Neighbor Classifier

This paper presents the combination of electroencephalogram (EEG) power spectrum ratio and Spectral Centroids techniques to extract unique features for human stress from EEG signals. The combination of these techniques was able to improve the k-NN (k-Nearest Neighbor) clasifier accuracy to detect and classify human stress from two cognitive states, Close-eye (CE) and Open-eye (OE). The EEG power spectrum in term of Energy Spectral Density (ESD) for each frequency bands (Delta, Theta, Alpha and Beta) was calculated. The ratio of EEG power spectrum and the average value of Spectral Centroids were selected as features to k-Nearest Neighbor (k-NN). The training and testing of the classifier were evaluated at 50:50 ratios and 70:30 ratios. The results showed that the combination of EEG power spectrum and Spectral Centroids techniques with the training and testing of k-NN set at 70:30 able to detect and classify the unique features for human stress at 88.89% accuracy.

Evaluation of human stress using EEG Power Spectrum

This paper presents an evaluation conducted between human stress questionnaires with EEG Power Spectrum of Beta and Alpha band. Cohens Perceived Stress Scale (PSS) was used as stress questionnaires to evaluate human stress. The EEG recording of 13 volunteers were carried out immediately after them answering the stress questionnaires. The scores from the stress questionnaires were calculated and used to figure out its relationship with the ratio of EEG Beta and Alpha band power. The results of the study showed the PSS was negatively correlated with the ratio of EEG Power Spectrum. Besides, the study suggested that it was feasible to use PSS and the ratio of EEG Power Spectrum to determine human stress.

IQ Index using Alpha-Beta correlation of EEG power spectrum density (PSD)

This paper presents a results of a study to investigate the relationship between Intelligence Quotient (IQ) of humans with their Electroencephalogram (EEG) Spectrum Power in term of the correlation of Beta and Alpha band power. The EEG was recorded from 50 subjects with 21 males and 29 females (mean of age = 23.16, SD = 3.8) for two tasks; closed-eyes (doing nothingin relax state) and IQ test. The results showed that 56% of the subjects have Index 2 while 6% as Index 3 with no Index 1 values. These values conclude that subjects with Alpha-Beta Index 3 and Index 2 is correlated with IQ Index 3(High IQ) and IQ Index 2 (Normal IQ) and there is no correlation between Index 1 for both Indexes.

EEG Analysis for Brainwave Balancing Index (BBI)

The purpose of this research is to establish the fundamental brainwave balancing index (BBI) using EEG signals. Brainwave signals from EEG were measured and analyzed using intelligent signal processing techniques and specific algorithm. Consequently, the signals were statistically correlated with established psychoanalysis techniques to produce BBI system. The result shows that the PSD analysis provides reliable BBI with 80% conformity. The fundamental findings (brainwave balancing index and brain dominance) from this research can be served as a simple indicator of one’s thinking leading to great opportunity for positive human potential development.

The Comparison between Listening to Al-Quran and Listening to Classical Music on the Brainwave Signal for the Alpha Band

This research investigates and compares the effects of listening to Al-Quran and classical music on human brain wave using EEG. The EEG signal was recorded for three states, which are before, during and after listening to Al-Quran and classical music. 28 healthy participants were randomly chosen among Universiti Teknologi MARA students with age range 20 to 28 years old. During this experiment, each sample was exposed to Surah Yasin of Al-Quran and Pachelbels Canon D major of classical music. Interview sessions were carried out prior to the EEG signals acquisition. Results in terms of correlation between the left and the right brainwaves show that there are increment of 12.67% during listening to Al-Quran and the increment for classical music stands at 9.96%. This finding indicates that listening to the Al-Quran recitation increases the alpha band more than listening to the classical music. Consequently, listening to Al-Quran in particular can result in a more relaxing and alert condition compared to classical music.

Initial investigation of brainwave synchronization after five sessions of Horizontal Rotation intervention using EEG

This research investigates the effects of five sessions of Horizontal Rotation (HR) on human brainwaves synchronization using EEG. EEG signals were captured from 42 participants before and after undergoing HR using two-channel bipolar connection in a controlled environment. The signals were filtered and classified into the four frequency bands; Delta, Theta, Alpha and Beta. Graphs were plotted and paired T-test analysis was used to demonstrate the correlation between left and right brainwaves before and after HR to verify brainwave synchronization. It was observed that after five sessions of HR, brainwaves were more synchronized for all frequency bands with highest increment of 37% in Delta band while the lowest increment is at 6% for Theta band. Thus, there was evidence that HR could synchronize brainwaves.

The Analysis of EEG Spectrogram Image for Brainwave Balancing Application Using ANN

The purpose of this paper is to analysis EEG spectrogram image using Artificial Neural Network (ANN) for brainwave balancing application. Time-frequency approach or spectrogram image processing technique is used to analyze EEG signals. The Gray Level Co-occurrence Matrix (GLCM) texture feature was extracted from spectrogram image and passed through Principal components analysis (PCA) to reduce the feature dimension. The experimental result shows that ANN was able to analysis EEG spectrogram images with an optimized model in training by varying neurons in the hidden layer, learning rate and momentum.

The preliminary study on the effect of nasyid music and rock music on brainwave signal using EEG

This preliminary study analyzes the effect of nasyid music and rock music on brainwave signal particularly focusing on alpha wave. EEG data were recorded from 30 students from Faculty of Electrical Engineering, UiTM age 18 to 27 years old. Students were interviewed before EEG recording to find out their music preference. Using EEG, the brainwave signal of the sample is captured twice, once before listening to the music and while listening to the music. Consequently, the brainwaves signal is analyzed and the comparison between these two music genres is discussed. The results demonstrate that 60–80% of the samples show improvement in the alpha band after listening to nasyid while only 56–66% improves after listening to rock music. These findings indicate that the alpha power increases when listening to the nasyid music compare to the rock music. Consequently, nasyid music in particular can result in a more relaxing condition compared to the rock music

The Effects of Mobile Phone Usage on Human Brainwave Using EEG

The aim of this research is to investigate any effects of mobile phone usage on human brainwaves using electroencephalograph (EEG) particularly on alpha wave. EEG signals were recorded from thirty samples that make calls from a mobile phone to another party without conversation. The mobile phone is strapped to the right ear. The EEG recording took place before, during and after the mobile phone calls. In addition, samples will be interviewed with questions related to the usage of hand phones prior to EEG recording. The brainwave signals were analyzed using statistical analysis. The EEG result shows that the alpha level of the right side decreases significantly during the calls and further decreases within the period of five minutes after the calls were ended. However, the alpha level of the left side remains consistent throughout the experiment. It follows that the correlation between the left and the right brainwaves signal decreases significantly during the calls and further decreases within the period of five minutes after calls. There is evidence that the usage of mobile phones affect the alpha brainwaves.

Initial investigation of human physical stress level using brainwaves

This paper presents an investigation of a new technique to measure and indicate the level of human physical stress by studying and evaluating the pattern of the brainwaves using Electroencephalogram (EEG). The EEG data is analyzed using an intelligent signal processing techniques in order to indicate the level of the physical stress.