MATEC Web Conf.
Volume 75, 20162016 International Conference on Measurement Instrumentation and Electronics (ICMIE 2016)
|Number of page(s)||4|
|Published online||01 September 2016|
Design of EEG Signal Acquisition System Using Arduino MEGA1280 and EEGAnalyzer
1 Electrical Engineering Dept, Gunadarma University, Jakarta - Indonesia
2 Informatics Engineering Dept, Gunadarma University, Jakarta - Indonesia
3 Informations System Dept, Gunadarma University, Jakarta - Indonesia
This study integrates the hardware circuit design and software development to achieve a 16 channels Electroencephalogram (EEG) system for Brain Computer Interface (BCI) applications. Signals obtained should be strong enough amplitude that is usually expressed in units of millivolts and reasonably clean of noise that appears when the data acquisition process. The process of data acquisition consists of two stages are the acquisition of the original EEG signal can be done by the active electrode with an instrumentation amplifier or a preamplifier and processing the signal to get better signals with improved signal quality by removing noise using filters with IC OPAMP. The design of a preamplifier with high common-mode rejection ratio and high signal-to-noise ratio is very important. Moreover, the friction between the electrode pads and the skin as well as the design of dual power supply. Designs used single-power AC-coupled circuit, which effectively reduces the DC bias and improves the error caused by the effects of part errors. At the same time, the digital way is applied to design the adjustable amplification and filter function, which can design for different EEG frequency bands. The next step, those EEG signals received by the microcontroller through a port Analog to Digital Converter (ADC) that integrated and converted into digital signals and stored in the RAM of microcontroller which simultaneously at 16 ports in accordance with the minimal number of points of data collection on the human scalp. Implementation results have shown the series of acquisitions to work properly so that it can be displayed EEG signals via software EEGAnalyzer.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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