22-06-2013, 02:45 PM
BRAIN CONTROLLED ARTIFICIAL LEGS
BRAIN CONTROLLED ARTIFICIAL.doc (Size: 960 KB / Downloads: 42)
ABSTRACT:
This paper describes a brain con-trolled robotic leg which is designed to per-form the normal operations of a human leg. After implanting this leg in a human, the leg can be controlled with the help of user’s brain signals alone. This leg behaves similar to a normal human leg and it can perform operation like walking, running, climbing stairs etc. The entire system is controlled with the help of advanced mi-crocontrollers and digital signal proces-sors. The signals are taken out from the human brain with the help of electroence-phalography technique. The person can perform operations like walking, running etc just by their thought. This system will be very much suitable for those who lost their legs in accidents and the proposed system is hundred percent feasible in the real time environment with the currently available technology.
Introduction:
A brain-computer interface (BCI), sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a human or animal brain and an external device. In this definition, the word brain means the brain or nervous system of an organic life form rather than the mind. Computer means any processing or computational device, from simple circuits to the complex microprocessors and microcontrollers.
An interesting question for the de-velopment of a BCI is how to handle two learning systems: The machine should learn to discriminate between different patterns of brain activity as accurate as possible and the user of the BCI should learn to perform different mental tasks in order to produce distinct brain signals. BCI research makes high demands on the sys-tem and software used. Parameter extrac-tion, pattern recognition and classification are the main tasks to be performed in a brain signals. In this paper it is assumed that the user of this system has one leg which is functioning fully and the system is designed accordingly. This system can be extended for both the legs and it is not limited to the basic operation of human legs such as walking, running, climbing stairs etc. It can also perform operations like cycling, hopping etc
Brain Waves
Electrical activity emanating from the brain is displayed in the form of brainwaves. There are four categories of these brainwaves ranging from the most activity to the least activity. When the brain is aroused and actively engaged in mental activities, it generates beta waves. These beta waves are of rela-tively low amplitude, and are the fastest of the four different brainwaves. The fre-quency of beta waves ranges from 15 to 40 cycles a second.
Amplifier:
The output signal from the electrode cap will be in the range of mV and µV. So, these signals will not be suitable for signal processing. Hence these signals are fed to an amplifier. Each electrode is connected to one input of a differential amplifier (one amplifier per pair of electrodes); a common system ref-erence electrode is connected to the other in-put of each differential amplifier. These am-plifiers amplify the voltage between the active electrode and the reference (typically 1,000–100,000 times, or 60–100 dB of voltage gain).
Analog to Digital Converter:
The output signals from the amplifier are analog in nature. They also contain some unwanted signals. Hence the output signals are filtered using high pass and low pass filters. The high-pass filter typically filters out slow artifact whereas the low-pass filter filters out high-frequency artifacts. After the signal is filtered they cannot be directly fed to a digital signal processors and microcontroller unit as they are in analog form. Hence these signals are sent to an Analog to Digital converter to convert the incoming analog signals in to digital signals.
Signal Processor:
Using the output signal from the A/D converter, parameter extraction, pattern classi-fication and pattern identification are done. Then the signals are fed to a Fast Fourier Transform Unit. This is done to simplify the calculations. An FFT algorithm computes the result in O (N log N) operations instead of O (N2) operations. The output signals from the signal processor are fed to a Microcontroller unit.
Conclusion:
Forty years ago, the technology was so basic. Newton said. “Leg sockets were made out of wood, offering the equivalent of a door hinge at the knee”. But with the recent advancement in the technology, Brain Controlled Artificial leg can be made as a reality. The performance of the proposed system will be better than the existing artificial legs as the user has full control over the Brain Controlled Artificial Legs. Hence it behaves like a normal human leg.