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IoT based Brainwave Speed Controlled ROBOT using Intel Galileo


Affiliations
1 Department of ECE, Charusat University, Changa, India
2 Department of CSE, Charusat University, Changa, India
     

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The development of brainwave-controlled mobile robots received a great deal of attention because they can support to bring mobility back to people with devastating neuromuscular disruption and thus improve their quality of life. It focuses on conceptualization and designing of complex systems in order to harness the power of mind in the form of brainwaves. In this paper, I presented a comprehensive up-to-date review of the complete systems, key techniques, and evaluation issues of brainwave-controlled robots. The proposed robot is fully automated and controlled using Beta wave (human brain attention) of MindWave sensor which is detected from brain signal. Simulation of practical and theoretical ElectroEncephalonGraphy technology is given in the paper.


Keywords

ElectroEncephalonGraphy (EEG), EEG Biosensor, NeuroSky® MindWave Mobile, Thinkgear Chip, RAW Data, Gamma, Beta, Alpha, Rapid-Eye-Movement(REM), Intel® Galileo Gen-2, Mind-Machine Interface (MMI).
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  • IoT based Brainwave Speed Controlled ROBOT using Intel Galileo

Abstract Views: 170  |  PDF Views: 3

Authors

Aalap Patel
Department of ECE, Charusat University, Changa, India
Hitesh Patel
Department of CSE, Charusat University, Changa, India
Jignesh  Patoliya
Department of CSE, Charusat University, Changa, India

Abstract


The development of brainwave-controlled mobile robots received a great deal of attention because they can support to bring mobility back to people with devastating neuromuscular disruption and thus improve their quality of life. It focuses on conceptualization and designing of complex systems in order to harness the power of mind in the form of brainwaves. In this paper, I presented a comprehensive up-to-date review of the complete systems, key techniques, and evaluation issues of brainwave-controlled robots. The proposed robot is fully automated and controlled using Beta wave (human brain attention) of MindWave sensor which is detected from brain signal. Simulation of practical and theoretical ElectroEncephalonGraphy technology is given in the paper.


Keywords


ElectroEncephalonGraphy (EEG), EEG Biosensor, NeuroSky® MindWave Mobile, Thinkgear Chip, RAW Data, Gamma, Beta, Alpha, Rapid-Eye-Movement(REM), Intel® Galileo Gen-2, Mind-Machine Interface (MMI).