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Design of Bio Signal Sensors and Signal Conditioning Circuits
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Many physiological disorders such as Amyotrophic Lateral Sclerosis (ALS) or injuries such as high-level spinal cord injury can disrupt the communication path between the brain and the body. People with severe motor disabilities may lose all voluntary muscle control. The disabled people with the above mentioned problems are forced to accept a reduced quality of life which may result in dependence on caretakers. To deal with these problems, sophisticated design of equipments for data acquisition and signal processing of bio potentials are required. An interface which communicates between a man and machine can solve this problem to a great extent. The proposed research presents an advanced man-machine interface by designing sensors that acquire EEG, EOG and EMG signals from brain, eyes and muscles respectively.
This paper describes a design and development of a method that acquires eyeball and eye blink signals .Then the acquired signals are used in controlling assistive/interfaced devices to help subjects who are partially paralyzed patients. Thus the application lies in the fact that the model developed is not limited to the degree of paralysis which has occurred. The design developed is checked for its validity and is found to be 90% accurate. The experimentation was done on partially paralyzed subjects as their eyeball movement and the eye blink were found to be normal. These eye movements and brainwave signal acquisition of data can be used to control a number of interactive devices such as a robot, a GUI or the movement of wheel chair.
This paper describes a design and development of a method that acquires eyeball and eye blink signals .Then the acquired signals are used in controlling assistive/interfaced devices to help subjects who are partially paralyzed patients. Thus the application lies in the fact that the model developed is not limited to the degree of paralysis which has occurred. The design developed is checked for its validity and is found to be 90% accurate. The experimentation was done on partially paralyzed subjects as their eyeball movement and the eye blink were found to be normal. These eye movements and brainwave signal acquisition of data can be used to control a number of interactive devices such as a robot, a GUI or the movement of wheel chair.
Keywords
EOG, EEG, EMG, Bio Signals, Data Acquisition, BIOPAC.
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