ON THE FREQUENCY ANALYSIS OF THE BRAIN-WAVE AND ITS STATISTICAL INTERPRETATION

1952 ◽  
Vol 6 (1) ◽  
pp. 1-38
Author(s):  
K. Suhara
Keyword(s):  
Frequency Analysis ◽  
Statistical Interpretation ◽  
Brain Wave ◽  
The Brain

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.

scholarly journals The research of controlling the robot arm by using the brain wave

2007 ◽  
Vol 19 (Supplement) ◽  
pp. 86-86
Author(s):  
Shinsuke Inoue ◽  
Akiyama Yoko ◽  
Yoshinobu Izumi ◽  
Shigehiro Nishijima
Keyword(s):  
Robot Arm ◽  
Brain Wave ◽  
The Brain

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.

Identification of Disease Symptoms Using Taste Disorders in Electroencephalogram Signal

2020 ◽  
Vol 17 (5) ◽  
pp. 2051-2056
Author(s):  
Kalyana Sundaram Chandran ◽  
T. Kiruba Angeline
Keyword(s):  
Neural Control ◽  
Brain Computer Interface ◽  
Processing Technique ◽  
Computer Interface ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Brain Wave ◽  
Disease Symptoms ◽  
Taste Disorders ◽  
The Brain

A Brain Computer Interface (BCI) is the one which converts the activity of the brain signals into useful and understandable signal. Brain computer interface is also called as Neural-Control Interface (NCI), Direct Neural Interface (DCI) or Brain Interface Machine (BMI). Electroencephalogram (EEG) based brain computer interfaces (BCI) is the technique used to measure the activity of the brain. Electroencephalography (EEG) is a brain wave monitoring and diagnosis. It is the measurement of electrical activity of the brain from the scalp. Taste sensations are important for our body to digest food. Identification of disease symptoms is based on the inhibition of different types of taste and by testing them to find the normality and abnormality of taste. The information is used in detection of disorder such as Parkinson’s disease etc. It is a source of reimbursement for better clinical diagnosis. Our brain continuously produces electrical signals when it operates. Those signals are measured with the equipment called Neurosky Mindwave Mobile headset. It is used to collect the real time brain signal samples. Neurosky is the equipment used in proposed work. Here the pre-processing technique is executed with median filtering. Feature extraction and classification is done with Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM). It increases the performance accuracy. The SVM classification accuracy achieved by this work is 90%. The sensitivity achieved is higher and the specificity is about 80%. We can able to predict the taste disorders using this methodology.

scholarly journals Influences of several kinds of anesthetic upon the brain wave of cats

1954 ◽  
Vol 50 (4) ◽  
pp. 443-456,en29
Author(s):  
Masami MURAMATSU
Keyword(s):  
Brain Wave ◽  
The Brain

scholarly journals A better way to define and describe Morlet wavelets for time-frequency analysis

2018 ◽  
Author(s):  
Michael X Cohen
Keyword(s):  
Frequency Analysis ◽  
Time Series Data ◽  
Sine Wave ◽  
Stationary Time Series ◽  
Series Data ◽  
Time Frequency Analysis ◽  
Temporal Precision ◽  
Time Frequency ◽  
Number Of Cycles ◽  
The Brain

AbstractMorlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal precision and frequency precision. It is typically defined as the “number of cycles,” but this parameter is opaque, and often leads to uncertainty and suboptimal analysis choices, as well as being difficult to interpret and evaluate. The purpose of this paper is to present alternative formulations of Morlet wavelets in time and in frequency that allow parameterizing the wavelets directly in terms of the desired temporal and spectral smoothing (as full-width at half-maximum). This formulation provides clarity on an important data analysis parameter, and should facilitate proper analyses, reporting, and interpretation of results. MATLAB code is provided.

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