scholarly journals Q-EEG map of parietal and frontal lobes out of brain waves recording during dental hypnosis practice

2021 ◽  
Vol 33 (3) ◽  
pp. 258
Author(s):  
Gilang Yubiliana ◽  
Raka Putra ◽  
Andri Abdurrochman
Keyword(s):  
Brain Mapping ◽  
Quantitative Research ◽  
Parietal Lobe ◽  
Dental Anxiety ◽  
Frontal Lobes ◽  
Recording Device ◽  
Topographic Map ◽  
Quantitative Electroencephalography ◽  
Brain Wave ◽  
Brain Waves

Introduction: A patient with fear and anxiety is a common case to deal with for a dentist, therefore, dental hypnosis has been widely used to ease this situation. In a hypnotized state, the human brain may easily accept any suggestion. This is projected in the brain waves. Electroencephalograph (EEG) is a brain wave recording device, reflecting several states of consciousness. Beta for conscious, alpha and theta for subconscious, and delta for sleep. Dental hypnosis puts down beta waves to alpha or theta. Quantitative Electroencephalography (Q-EEG) or brain mapping is a comprehensive analysis of (Electroencephalography, EEG) in a colored topographic map, reflecting the brain's electrical activity. The objective of this article was reporting the parietal and frontal lobes activity during dental hypnosis based on the Q-EEG mapping. Methods: The research applied a quantitative research method using observatory study. The sample was taken with an accidental sampling method, with inclusion criteria, patients with dental anxiety and exclusion criteria was patients with special need and high level of dental anxiety. Data of the EEG records was taken in January-March 2018, and processed after in Pramita laboratorium Bandung. Results: Parietal lobe affected more during the inducement than temporal lobe. During dental hypnosis, the hypnotic markers (theta and alpha states) observed from the EEG were found to be more reactive. Conclusion: Dental hypnosis effects can be observed easily using Quantitative Electroencephalography method. Dental hypnosis affects brainwaves and brain mapping which indicate relaxations of brain waves especially on parietal lobes.

scholarly journals Analysis of Recognition Processes by Measurement of Brain Waves and Temperature Distributions

1992 ◽  
Vol 4 (1) ◽  
pp. 63-69
Author(s):  
Hideto Ide ◽  
◽  
Masafumi Uchida
Keyword(s):  
Temperature Distribution ◽  
Temperature Measurement ◽  
Parietal Lobe ◽  
Statistic Analysis ◽  
Frequency Range ◽  
Brain Wave ◽  
Brain Waves ◽  
The Past ◽  
Temperature Distributions ◽  
General Method

In the past, in study of the evoked brain wave, the averaging was the most general method for analysis of signal components in brain wave. Specially, the averaging was applied for several evoked brain waves on the process of recognition to the stimulation, i.e. P300. However, any information for the averaging. The averaging is difficult to evaluate the evoked brain wave because of it's characteristics. In this study, it was the purpose to reveal the frequency range, the latency and the acyive parts of brain by following two method. 1) frequency and statistic analysis of evoked brain wave 2) measurement of temperature distribution on the surface of the head. The experiment for the measurement of the evoked brain wave was applied to fifteen men whose age were from 22 to 25. After frequency and statistic analysis, and waves were obtained at about 300ms latency. This result is as same as the averaging's result. From the temperature measurement, it was considered that the recognition to the stimulation was performed at the parietal lobe.

TIMELESS BUILDINGS AND THE HUMAN BRAIN: The Effect of Spiritual Spaces on Human Brain Waves

2014 ◽  
Vol 8 (1) ◽  
pp. 133
Author(s):  
Sally M. Essawy ◽  
Basil Kamel ◽  
Mohamed S. Elsawy
Keyword(s):  
Human Brain ◽  
Case Studies ◽  
Spiritual Experience ◽  
Brain Wave ◽  
Human Comfort ◽  
Beliefs And Practices ◽  
Brain Waves ◽  
Space Design ◽  
State Of Mind ◽  
The Brain

Some buildings hold certain qualities of space design similar to those originated from nature in harmony with its surroundings. These buildings, mostly associated with religious beliefs and practices, allow for human comfort and a unique state of mind. This paper aims to verify such effect on the human brain. It concentrates on measuring brain waves when the user is located in several spots (coordinates) in some of these buildings. Several experiments are conducted on selected case studies to identify whether certain buildings affect the brain wave frequencies of their users or not. These are measured in terms of Brain Wave Frequency Charts through EEG Device. The changes identified on the brain were then translated into a brain diagram that reflects the spiritual experience all through the trip inside the selected buildings. This could then be used in architecture to enhance such unique quality.

Functional Architecture of Eye Position Gain Fields in Visual Association Cortex of Behaving Monkey

2003 ◽  
Vol 90 (2) ◽  
pp. 1279-1294 ◽  
Author(s):  
Ralph M. Siegel ◽  
Milena Raffi ◽  
Raymond E. Phinney ◽  
Jessica A. Turner ◽  
Gábor Jandó
Keyword(s):  
Cortical Neurons ◽  
Visual Information ◽  
Parietal Lobe ◽  
Association Cortex ◽  
Eye Position ◽  
Visual Response ◽  
Topographic Map ◽  
Functional Architecture ◽  
Visual Association Cortex ◽  
Area 7A

In the behaving monkey, inferior parietal lobe cortical neurons combine visual information with eye position signals. However, an organized topographic map of these neurons' properties has never been demonstrated. Intrinsic optical imaging revealed a functional architecture for the effect of eye position on the visual response to radial optic flow. The map was distributed across two subdivisions of the inferior parietal lobule, area 7a and the dorsal prelunate area, DP. Area 7a contains a representation of the lower eye position gain fields while area DP represents the upper eye position gain fields. Horizontal eye position is represented orthogonal to the vertical eye position across the medial lateral extents of the cortices. Similar topographies were found in three hemispheres of two monkeys; the horizontal and vertical gain field representations were not isotropic with a greater modulation found with the vertical. Monte Carlo methods demonstrated the significance of the maps, and they were verified in part using multiunit recordings. The novel topographic organization of this association cortex area provides a substrate for constructing representations of surrounding space for perception and the guidance of motor behaviors.

OBSERVATION OF THE EFFECTS OF PLAYING GAMES WITH THE HUMAN BRAIN WAVES

2015 ◽  
Vol 77 (7) ◽  
Author(s):  
Mahfuzah Mustafa ◽  
Rul Azreen Mustafar ◽  
Rosdiyana Samad ◽  
Nor Rul Hasma Abdullah ◽  
Norizam Sulaiman
Keyword(s):  
Human Brain ◽  
Threshold Value ◽  
Band Pass Filter ◽  
Beta Band ◽  
Brain Wave ◽  
Pass Filter ◽  
Brain Waves ◽  
Power Spectral ◽  
Mind State ◽  
Band Pass

The purpose of this paper is to observe the human brain waves when a person playing video games. The game proposed is Counter Strike (CS) 1.6. There are 30 samples of human brain wave will be collected. The EEG signal will be recorded before playing a game and after playing a game. The threshold value is used to filter the data collected to acquire clean brain waves. Then, extraction of sub-band Alpha and Beta is done by Band-pass filter. Power Spectral Density (PSD) is performed in analysing the brain waves to acquire peak amplitude of the Alpha and Beta sub-band frequencies. The pattern of Alpha and Beta is carried out by using the histogram to observe the relationship between games and mind state of humanity. It is observed that the Beta-band increase and Alpha-band decrease after the samples playing game.  

scholarly journals Alvin Lucier's Music for Solo Performer: Experimental music beyond sonification

2014 ◽  
Vol 19 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Volker Straebel ◽  
Wilm Thoben
Keyword(s):  
Performance Practice ◽  
Central Place ◽  
Experimental Music ◽  
Electronic Equipment ◽  
Brain Wave ◽  
Brain Waves ◽  
Percussion Instruments ◽  
History Of ◽  
The Brain

Alvin Lucier's Music for Solo Performer (1965), often referred to as the ‘brain wave piece’, has become a key work of experimental music. Its setup, in which the brain waves of a solo performer are made to excite percussion instruments, has given the work a central place in the discourse on artistic sonification. However, only a small number of the authors making reference to the work seem to have studied the score, and even fewer have given thought to the score's implications for performance practice and aesthetic reflection. This paper pays detailed attention to these yet overlooked aspects, drawing on accounts of early performances as well as the authors’ participation in a 2012 performance led by the composer. We also trace the history of live-electronic equipment used for Music for Solo Performer and discuss the work's reception in sonification research.

scholarly journals Electroencephalographic study of auditory system while listening to Ohm chanting

2020 ◽  
Vol 11 (1) ◽  
pp. 75-79
Author(s):  
Sasithorn Sachdev ◽  
Phakkharawat Sittiprapaporn
Keyword(s):  
Conventional Medicine ◽  
Well Being ◽  
World Health ◽  
Brain Wave ◽  
Brain Waves ◽  
Good State ◽  
Spiritual Well Being ◽  
Rest Time ◽  
Electroencephalographic Study ◽  
Health Organization

Background: World Health Organization defined that we must have Physical, Mental, Social and Spiritual Well-Being. The methods of building a healthy body and develop a strong immune are food, exercising, walking, running, yoga, swimming, Tai Shi Shuan and all types of sports. In spiritual well-being, the implementations are practice the dharma, compassionate prayer and meditation. These will make our mental status always in good state, greed, anger and infatuation will be decreased. Aims and Objective: This study aimed to investigate the effect of listening to Om chanting on human brain waves. Materials and Methods: The samples were twelve healthy Thai citizens with the age ranged between twenty-five and sixty years old. All participants listened to Ohm chanting for thirty minutes, with rest time in between. During the experiment, the participants were asked to open their eyes. In addition, their brain wave activities were recorded before, during and after listening to the Ohm chanting by the Electroencephalogram (EEG) at precise intervals. All data were tabulated to find mean and standard deviation. The changes in brain waves and subjective changes were also compared by applying paired t-test. People listening to Ohm chanting had subjective changes through electroencephalographic (EEG) fluctuations. Results: The exposed participants displayed statistically significant increases in delta and theta brainwaves at 0.05 after listening to Ohm chanting. This study revealed that participants were trained with the listening to Ohm chanting causing probably the stress level went down. There was an increase in delta and theta brainwaves while listening to Ohm chanting. Conclusion: The result might be nominated for health promotion to be used in conjunction with conventional medicine.

scholarly journals Deep Learning on Game Addiction Detection Based on Electroencephalogram

2021 ◽  
Vol 5 (3) ◽  
pp. 963
Author(s):  
Lalu Arfi Maulana Pangistu ◽  
Ahmad Azhari
Keyword(s):  
Brain Activity ◽  
Late Adolescence ◽  
Wave Activity ◽  
Test Results ◽  
Brain Wave ◽  
Brain Waves ◽  
Game Addiction ◽  
Brain Wave Activity ◽  
Electroencephalogram Eeg ◽  
The Brain

Playing games for too long can be addictive. Based on a recent study by Brand et al, adolescents are considered more vulnerable than adults to game addiction. The activity of playing games produces a wave in the brain, namely beta waves where the person is in a focused state. Brain wave activity can be measured and captured using an Electroencephalogram (EEG). Recording brain wave activity naturally requires a prominent and constant brain activity such as when concentrating while playing a game. This study aims to detect game addiction in late adolescence by applying Convolutional Neural Network (CNN). Recording of brain waves was carried out three times for each respondent with a stimulus to play three different games, namely games included in the easy, medium, and hard categories with a consecutive taking time of 10 minutes, 15 minutes, and 30 minutes. Data acquisition results are feature extraction using Fast Fourier Transform to get the average signal for each respondent. Based on the research conducted, obtained an accuracy of 86% with a loss of 0.2771 where the smaller the loss value, the better the CNN model built. The test results on the model produce an overall accuracy of 88% with misclassification in 1 data. The CNN model built is good enough for the detection of game addiction in late adolescence. 

scholarly journals Boosting Brain Waves Improves Memory

2021 ◽  
Vol 9 ◽  
Author(s):  
Richard J. Addante ◽  
Mairy Yousif ◽  
Rosemarie Valencia ◽  
Constance Greenwood ◽  
Raechel Marino
Keyword(s):  
Wave Pattern ◽  
Brain Wave ◽  
Brain Waves ◽  
Wave Patterns ◽  
The Brain ◽  
With Memory

Have you ever wanted to improve your memory? Or have you struggled to remember what you studied? Memory uses special patterns of activity in the brain. This experiment tested a new way to create brain wave patterns that help with memory. We wanted to see if we could improve memory by using lights and sounds that teach the brain waves to be in sync. People wore special goggles that made flashes of light and headphones that made beeping noises. This trained the brain through a process called entrainment. The entrainment put the brain in sync at a specific brain wave pattern called theta. People whose brains were trained to be in theta had better memory compared to people whose brains did not get trained. We learned that entrainment is a cool new way to make memory better.

scholarly journals Introduction to the identification of brain waves based on their frequency

2018 ◽  
Vol 210 ◽  
pp. 05012 ◽  
Author(s):  
Zuzana Koudelková ◽  
Martin Strmiska
Keyword(s):  
Brain Activity ◽  
Computer Interface ◽  
Brain Wave ◽  
Non Invasive ◽  
Brain Waves ◽  
Analytical Reasoning ◽  
Brain Signals ◽  
Electroencephalogram Eeg ◽  
The Brain ◽  
Research Type

A Brain Computer Interface (BCI) enables to get electrical signals from the brain. In this paper, the research type of BCI was non-invasive, which capture the brain signals using electroencephalogram (EEG). EEG senses the signals from the surface of the head, where one of the important criteria is the brain wave frequency. This paper provides the measurement of EEG using the Emotiv EPOC headset and applications developed by Emotiv System. Two types of the measurements were taken to describe brain waves by their frequency. The first type of the measurements was based on logical and analytical reasoning, which was captured during solving mathematical exercise. The second type was based on relax mind during listening three types of relaxing music. The results of the measurements were displayed as a visualization of a brain activity.

Design and Implementation of Wheelchair Controller Based Electroencephalogram Signal using Microcontroller

2016 ◽  
Vol 6 (6) ◽  
pp. 2878
Author(s):  
M. I. Arzak ◽  
U. Sunarya ◽  
S. Hadiyoso
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Maximum Load ◽  
Dc Motor ◽  
Maximum Speed ◽  
Process Data ◽  
Brain Wave ◽  
Fuzzy Method ◽  
Brain Waves ◽  
Level Data

<p>Wheelchair is a medical device that can help patients, especially for persons with physical disabilities. In this research has designed a wheelchair that can be controlled using brain wave. Mind wave device is used as a sensor to capture brain waves. Fuzzy method is used to process data from mind wave. In the design was used a modified wheelchair (original wheelchair modified with addition dc motor that can be control using microcontroller ). After processing data from mindwave using fuzzy method, then microcontroller ordered dc motor to rotate.The dc motor connected to gear of wheelchair using chain. So when the dc motor rotated the wheelchair rotated as well.  Controlling of DC motor used PID control method. Input encoder was used as feedback for PID control at each wheel.From the experimental results concentration level data of the human brain waves can be used to adjust the rate of speed of the wheelchair. The level accuracy of respons Fuzzy method ton system obtained by devide total true respons data with total tested data and the result is 85.71 %.  Wheelchairs can run at a maximum speed of 31.5 cm/s when the battery voltage is more than 24.05V. Moreover, the maximum load of wheelchair is 110 kg.</p>

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