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

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 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 ON THE “TRANSFORMING ACTION” OF THE BRAIN SHOWN IN THE BRAIN WAVE

1957 ◽  
Vol 7 ◽  
pp. 181-189 ◽  
Author(s):  
KENSUKE SATO ◽  
KEIICHI MIMURA ◽  
TOSHIYUKI OZAKI ◽  
YOSHIAKI YAMAMOTO ◽  
SHIGERU MASUYA ◽  
...  
Keyword(s):  
Brain Wave ◽  
The Brain

scholarly journals Honeybee Brain Oscillations Are Generated by Microtubules. The Concept of a Brain Central Oscillator

2021 ◽  
Vol 14 ◽  
Author(s):  
Brenda C. Gutierrez ◽  
Marcelo R. Pita Almenar ◽  
Luciano J. Martínez ◽  
Manuel Siñeriz Louis ◽  
Virginia H. Albarracín ◽  
...  
Keyword(s):  
Field Potential ◽  
Oscillatory Activity ◽  
Mammalian Brain ◽  
Insect Brain ◽  
Patch Clamp Technique ◽  
Brain Wave ◽  
Signaling Mechanism ◽  
Brain Wave Activity ◽  
The Brain ◽  
Honeybee Brain

Microtubules (MTs) are important structures of the cytoskeleton in neurons. Mammalian brain MTs act as biomolecular transistors that generate highly synchronous electrical oscillations. However, their role in brain function is largely unknown. To gain insight into the MT electrical oscillatory activity of the brain, we turned to the honeybee (Apis mellifera) as a useful model to isolate brains and MTs. The patch clamp technique was applied to MT sheets of purified honeybee brain MTs. High resistance seal patches showed electrical oscillations that linearly depended on the holding potential between ± 200 mV and had an average conductance in the order of ~9 nS. To place these oscillations in the context of the brain, we also explored local field potential (LFP) recordings from the Triton X-permeabilized whole honeybee brain unmasking spontaneous oscillations after but not before tissue permeabilization. Frequency domain spectral analysis of time records indicated at least two major peaks at approximately ~38 Hz and ~93 Hz in both preparations. The present data provide evidence that MT electrical oscillations are a novel signaling mechanism implicated in brain wave activity observed in the insect brain.

scholarly journals ARM Controller and EEG based Drowsiness Tracking and Controlling during Driving

2018 ◽  
Vol 6 (3) ◽  
pp. 127
Author(s):  
B. Naresh ◽  
S. Rambabu ◽  
D. Khalandar Basha
Keyword(s):  
Brain Activity ◽  
Traffic Signals ◽  
Electrical Signal ◽  
Emotional States ◽  
Brain Wave ◽  
Computer Interfaces ◽  
Medium Level ◽  
And Control ◽  
To Receive ◽  
The Brain

<span>This paper discussed about EEG-Based Drowsiness Tracking during Distracted Driving based on Brain computer interfaces (BCI). BCIs are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity commands through controller device in real time. With these signals from brain in mat lab signals spectrum analyzed and estimates driver concentration and meditation conditions. If there is any nearest vehicles to this vehicle a voice alert given to driver for alert. And driver going to sleep gives voice alert for driver using voice chip. And give the information about traffic signal indication using RFID. The patterns of interaction between these neurons are represented as thoughts and emotional states. According to the human feelings, this pattern will be changing which in turn produce different electrical waves. A muscle contraction will also generate a unique electrical signal. All these electrical waves will be sensed by the brain wave sensor and it will convert the data into packets and transmit through Bluetooth medium. Level analyzer unit (LAU) is used to receive the raw data from brain wave sensor and it is used to extract and process the signal using Mat lab platform. The nearest vehicles information is information is taken through ultrasonic sensors and gives voice alert. And traffic signals condition is detected through RF technology.</span>

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