The University of Tokyo / System Innovation, Graduate School of Engineering
Research related with EEG intelligent home control applications
The purpose of Research:Neurophysiological studies has offered us a foundation so we can find some correlation between EEG and human consciousness and actions. Based on this technology, EEG as a means of control are constantly improved and developed, and EEG helmet devices are emerging on the market. For possible use in smart home control products based on, this study of EEG helmets carried EEG acquisition and processing, this research focuses on the software signal processing, classification algorithms, and hardware to minimize the number of electrode contacts. Process of Research: 1.Search and revise various existing recognization models, and establish our own emotion model. 2.Using software offered by Emotiv to extract to original features of EEG signals. Artificially we mark each signal fragments with appropriate labels. 3.Search the papers and publishments about algorithms related to EEG recognition and the progress of the latest research. Make sure we understand the algorithms and decide the appropriate algorithm to use. 4. We tried to establish the model which links the EEG signal and the motivation marks. We designed the experiment through machine learning algorithms, during this process we adjusted models and algorithms, evaluated accuracy and adequacy of the model. 5.Finally, we decided the appropriate relation model. 6.Publish the result and write the graduate paper. Research Result: Graduate paper for my Bachelor's degree in Engineering