E-Mail Address & Phone Number of the Faculty Guide :Non
Project Information
Project Title:Brain Machine Interface for mind controlled Wheelchair
Hardware & Software Used:
Hardware: MCP 2210 USB to SPI Converter,ADS1299 Analog to digital converter,tps73230 Voltage Regulator and pasive filter with Resister and capacitor
Software: Labview 2011.
What challenge/problem are you trying to solve through your application: Mind Controlled Device for Phicaly Challanged PEople
How does your application solves the above mentioned challenge/problem: Its Design is very Compect and use very powerfull Labview software tool to implement it.
Description of Project:
Brain machine interface provides a communication channel between the human brain and an
external device. Brain interfaces will provide rehabilitation to patients with neurodegenerative
diseases like amyotrophic lateral sclerosis, brain stem stroke, quadriplegics and spinal cord
injury; such patients loose all communication pathways except for their sensory and cognitive
functions. One of the possible rehabilitation methods for these patients is to provide
a brain machine interface (BMI) for communication, using the electrical activity of
the brain detected by scalp EEG electrodes. In this project, a simple BMI system based on EEG
signal and visual feedback for controlling wheelchair robot and other devices has been proposed.
The ability of an individual to control his EEG through the visual feedback enables him to
control devices. The EEG signal will be recorded from few voluntary healthy subjects using the
noninvasive scalp electrodes placed over the frontal, parietal, motor cortex, temporal and
occipital areas. The obtained EEG signals were segmented and then processed using an elliptic
filter. Using spectral analysis, the alpha, beta and gamma band frequency spectrum features are
obtained for each EEG signals. The extracted features are then associated to different control
signals and a neural network model using back propagation algorithm will be developed. The
proposed method can be used to translate the visual feedback signals into control signals and
used to control the movement of a robot wheelchair
