Ros Shilawani S. Abdul Kadir

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 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

Comparison between the Left and the Right Brainwaves for Delta and Theta Frequency Band after Horizontal Rotation Intervention

This paper investigates the difference between the left and the right brainwaves for delta and theta frequency band after horizontal rotation (HR) intervention using electroencephalography (EEG). The EEG signals were captured from the samples before and after under-going HR. The artifact of the EEG signals was removed automatically by means of a program designed to eliminate data above 100 micro volts. Then the Power Spectral Density (PSD) was applied to the artifact removed data and comparison was carried out to determine the better method and the effects of HR intervention. MATLAB and Paired T-test analysis from SPSS was used and graphs were plotted to show the correlation between the left and right brainwave before and after HR involvement. In conclusion, by applying PSD to the artifact removed signals, results improved significantly. It also shows that the correlation of the left and the right brainwaves had improved for delta and theta frequency bands after HR.

Development of Brainwave Balancing Index Using EEG

In this research, Wireless EEG equipment via Bluetooth technology named g-Mobilab was used to measure the brainwave signals in the right and left frontal area of the brain. The recorded EEG signals were channelled into an automatic artifact removal analysis whereby signals above values of 100 micro-volts were removed by means of a program using Matlab. Consequently, Power Spectral Density techniques and specific algorithm were employed to further enhance the EEG signals. The correlation between the left and the right brainwaves were achieved using paired T test from SPSS. The results, which are brainwave balancing index (BBI) and brainwave dominance, were presented via Graphic User Interface (GUI). The outcome shows that BBI system could be established using EEG signals. These findings (brainwave dominance and BBI) could be used as a straightforward indicator of ones ability to think and work leading to vast opportunity for constructive human potential advancement.

Analysis of brainwave dominant after horizontal rotation (HR) intervention using EEG for Theta and Delta frequency bands

This paper presents analysis of brainwave dominant after horizontal rotation (HR) intervention using EEG. It was conducted by interviewed all samples. Then, EEG signals were captured from the samples before and after under-going three sessions of HR. Basically, brainwave has four frequency bands which are Alpha, Beta, Theta and Delta. However, this paper will only focus on theta and delta. Paired T-test analysis was used and graphs were plotted to show the correlation between the left and right brainwave before and after HR intervention to verify brainwave dominant. It was observed that, after HR for all three sessions most of brainwaves were balanced but still some of brainwaves signals show unbalanced condition.

Preliminary Study: The Comparison between Hands-Free and Handheld 3G Mobile Phone on Alpha Brainwave

This paper presents a preliminary study on the comparison between hands-free and handheld 3G mobile phone on alpha brainwave signal for thirty samples. The resting alpha brainwave activities were recorded using EEG for three stages which are before, during and after calls. The data analysis involved correlation between left and right brainwaves signals using SPSS (Statistical Package for the Social Sciences) version 20.0. From the result, the correlations of alpha left and alpha right for hands-free shows an increment 0.64%. This indicates that while using hands-free there is a minor positive effect to the alpha value. However, while using handheld, the correlation shows a decrement of 0.51 during call stage. This decrement shows a negative effect on the brainwave balancing although the samples were exposed for a short period of time. From this finding, there is evidence that using hands-free is slightly better in terms of reducing the effect of mobile phone on brainwave signals.

Analysis of correlation between body mass index (BMI) and brain wave using EEG for Alpha and Beta frequency band

This research focuses on the correlation between body mass index (BMI) and brainwave activity measured using EEG, concentrating on Alpha and Beta waves. BMI is a measurement of body fat based on height and weight. Using BMI as reference, all 63 samples were given interviewed and then categorized into 3 groups before undergoing EEG recording. The groups are underweight (index ≪20), ideal weight (index 20–24) and overweight (index ≫24). The brainwaves data were analyzed using paired T test from SPSS software. It was observed that there were higher correlations between BMI and brainwave pattern for overweight category as compared to the other two. Generally, it can also be concluded that ideal weight participants have less stress than the others do.