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.

Comments

Post a Comment

Popular posts from this blog

Geography of Thoughts

Image
The cerebral cortex is split into two hemispheres that often have very different functions. For instance, most language functions lie primarily in the left hemisphere, while the right hemisphere controls many abstract and spatial reasoning skills. Also, most motor and sensory signals to and from the brain cross hemispheres, meaning that the right brain senses and controls the left side of the body and vice versa. The brain can be further divided into separate regions specialized for different functions. For example, occipital regions at the very back of the head are largely devoted to processing of visual information. Areas in the temporal regions, roughly along the sides and lower areas of the cortex are involved in memory, pattern matching, and language processing and auditory processing. Still other areas of the cortex are devoted to diverse functions such as spatial representation and processing, attention orienting, arithmetic, voluntary muscle movement, planning, reas...
Read more

Band Pass filter Design

Image
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...
Read more

EEG dataset for 64 channels

       This dataset was created and contributed to PhysioNet by the developers of the BCI2000 instrumentation system, which they used in making these recordings. Subjects performed different motor/imagery tasks while 64-channel EEG was recorded using the BCI2000 system. Each subject performed 14 experimental runs: two one-minute baseline runs (one with eyes open, one with eyes closed), and three two-minute runs of each of the four following tasks: 1. A target appears on either the left or the right side of the screen. The subject opens and closes the corresponding fist until the target disappears. Then the subject relaxes. 2. A target appears on either the left or the right side of the screen. The subject imagines opening and closing the corresponding fist until the target disappears. Then the subject relaxes. 3. A target appears on either the top or the bottom of the screen. The subject opens and closes either fists (if the target is on top) or both f...
Read more