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BCI Scenarios

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BCIs can be used in the following six scenarios (see the Figure bellow, adapted from [1] BCIs can  replace  natural CNS output that has been lost as a result of injury or disease. Examples include communication (through a spelling system and voice synthesis) and motorized wheelchair control.   BCIs can  restore  lost natural CNS output. Examples include functional electrical stimulation of muscles in a paralyzed person and stimulation of peripheral nerves to restore bladder function. BCIs can  enhance  natural CNS output. Examples include monitoring brain activity during prolonged demanding tasks such as driving a car and detecting lapses of attention, which alerts the person and restores attention.   BCIs can  supplement  natural CNS output. Examples include providing a third (robotic) arm to a person and providing a selection function for people using a joystick. BCIs can...

Brain

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    Brain lies in the cranium of skull. The human brain has wrinkled surface and appears as a large, soggy, pinkish grey walnut. Adult brain, on average, weights two per cent of their body weight, growing from the quarter of its size at the time of birth.  the reaches between 75 and 80 percent of adult size at the size of 6 years. Human brain composed of about 30 billion neurons. It weights about 15- 17% of cardiac output. It also receives about 20% of the oxygen consumed by the body. The left hemisphere of the brain controls the right side of the body and vice-versa. Regions of the brain:  Fore-brain: It  consist of three parts Olfactory lobe, Cerebrum, Hypothalamus The cerebrum is the largest part of the human brain. the cerebral cortex is roughly 80% of total brain mass. the Cerebrum is the most complex and specialized  part of the brain. It consists of two cerebral hemispheres. The  cerebr...

Nervous System

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The human nervous system consist of three functional subsystems, the central nervous system, functional nervous, system, and autonomous nervous system. brain and  spinal cord make Central Nervous System(CNS). The Peripheral Nervous System includes all the nerve pathways of the body outside the brain and spinal cord. These pathways are divided into two parts. These are the sensory pathways and motor pathways . Sensory pathways transmit information to CNS(Central Nervous System) . the motor pathways transmit commands from the CNS.   The motor pathways are partitioned into  somatic nervous system which relay to commands to skeletal muscles and Automatic nervous that stimulates the glads and other muscles of the body. In addition there is a neuroendocrine  system which is a network of endocrine glands  whose hormone production controlled by  CNS.   Neuron is the structural and fictional part of the  nervous system . It is the largest ...

Power Spectrum Density for different time

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  Bellow graphs taken for selecting which time is better for the study PSD of EEG signal.   In the Fig 4.17 EEG data of channel taken for 1s. This data pass through the band pass filter for separating different frequency bands. For calculating the power spectrum density of each band we need to calculate the mean of all amplitudes present in the frequency band. In the delta band,  from the observations data it is seen that the amplitude of channel 6 is high as comparing the other channel. This channel present on the frontal lobe of the brain. For the channel seven amplitude man of frequency band suddenly deceasing. The position of this electrode is the right hemisphere of the brain. For this observation frontal part of right hemisphere is dominant, however it is seen that the subject doing the left side work. Generally the right hemisphere of the brain sees the work of the left side and vice versa. Next channel 8 amplitude mean is high which is placed on central l...

Band Pass filter Design

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It is designed by giving higher cut of frequency and lower cut of frequencies. We record EEG signal externally by using Electrodes. Because of that Skin noise, skull noise, disturbance noise, power line noise etc noise present in EEG signal. For removing the higher cut off and lower cut of frequency from the signal band pass filter is used. We want the signal frequency up to 30 Hz because the beta band frequencies is up to that frequency. Design the Band pass Butterworth filter in the matlab by using the code Algorithm: i) First take eeg input data ii) Pot that data iii) Mention the sampling frequency iv) Calculate the normalize frequency by using formula fnormal = cut of frequency (Fs/2) v) Then design the butter of the filter in that we put the order of filter, normalize frequency , curve type, for this we take two vectors. vi) Then filter the data using Filtfilt . it performs zero-phase digital filtering by processing t...

Experiments

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For study the FFT of periodic and EEG signal program is written in the matlab by using the signal processing function FFT. The FFT of periodic signal shows the different for the sine, square, triangular, swatooth signals. FFT of EEG signal shows that the frequency components present in that signal. The algorithm of this periodic signal program is given bellow. Algorithm For the periodic signal i) Create a periodic signal using signal processing functions. ii) Mention the sampling frequency iii) Give the amplitude and frequency of the periodic signal iv) Pot that signal v) Take the FFT of the input signal vi) Plot the half of the sampling frequency components for the x axis. vii) Plot the FFT of the signal frequency verses amplitude. For the EEG signal i) First read EEG input data from the .xls file. ii) Give the sampling frequency given when recording the EEG signal. iii) Plot the EEG signal. iv) Take the FFT of the EEG signal. v) Plot the half of the sampling ...

Plan of experiment

Study of brain computer interfacing using fourier transform starting from the study FFT of Periodic signal such as sine, square, triangular, swatooth. For the study FFT start from the basic periodic signal is good work. When study of periodic signal is understood completely then start the Fourier transform of the EEG signal. The Fourier transform of EEG signal is important for the detecting the actual frequency components from the signal. After that the separating frequency spectrum bands from EEG signal design the band pass filters for each band. Next step of the study is calculate the amplitude mean of the each frequency spectrum band of the EEG signal, from that we can detect which channel of the brain in dominant. However we can detect which part of the brain is in currently working state. To prove this result analyses the EEG signal of different task given for the subject using the different electrode montage.