22-05-2012, 12:58 PM
BRAIN MACHINE INTERFACE
BRAIN MACHINE.ppt (Size: 1,018 KB / Downloads: 66)
INTRODUCTION
A Brain-Machine Interface (BMI) is an attempt to mesh our minds with machines. It is a communication channel from a human's brain to a computer.
BMIs are intended for enabling both the severely motor disabled as well as the healthy people to operate electrical devices and applications through conscious mental activity.
HISTORY
The history of BMI starts with Hans Berger's discovery of the electrical activity of human brain and the development of EEG (1924).
The first wireless intracortial brain-computer interface was build by Philip Kennedy and his colleagues by implanting neurotrophic cone electrodes into monkey brains (1970).
One of the first persons who benefit from all the years of BMI research is Matt Nagle. In 2004 an electrode array was implanted into his brain to restore functionalities he had lost due to paralysis.
BMI DETAILS
Main Principle
“Main principle behind this interface is the bioelectrical activity of muscles an nerves, Neurons work in complex logic and produce thought and signals that control our bodies ,who’s measurement is together Called EEG
BMI Approaches
An ideal BMI could detect the user’s wishes and commands directly. However, this is not possible with today’s technology. Therefore, BMI researches have used the knowledge they have had of the human brain and the EEG in order to design a BMI. There are basically two different approaches that have been used. The first one called a pattern recognition approach is based on cognitive mental tasks. The second one called an operant conditioning approach is based on the self-regulation of the EEG response.
IMPLANT DEVICE
The EEG is recorded with electrodes, which are placed on the scalp. Electrodes are small plates, which conduct electricity. They provide the electrical contact between the skin and EEG recording apparatus by transforming the ionic current on the skin to the electrical current in the wires.
SIGNAL PROCESSING & EXTERNAL DEVICE
Signal Processing Section
Electrodes interface directly to the non-inverting op-amp inputs on each channel. At this section amplification, initial filtering of EEG signal and possible artifact removal takes place. Also A/D conversion is made, i.e. the analog EEG signal is digitized. The voltage gain improves the signal-to-noise ratio (SNR) by reducing the relevance of electrical noise incurred in later stages. Processed signals are time division multiplexed and sampled. Further Steps for Signal Processing are spike detection, signal analysis