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http://dx.doi.org/10.21288/resko.2017.11.1.45

Indoor Environment Control System based EEG Signal and Internet of Things  

Jeong, Haesung (인하대학교 컴퓨터정보공학과)
Lee, Sangmin (인하대학교 전자공학과)
Kwon, Jangwoo (인하대학교 컴퓨터정보공학과)
Publication Information
Journal of rehabilitation welfare engineering & assistive technology / v.11, no.1, 2017 , pp. 45-52 More about this Journal
Abstract
EEG signals that are the same as those that have the same disabled people. So, the EEG signals are becoming the next generation. In this paper, we propose an internet of things system that controls the indoor environment using EEG signal. The proposed system consists EEG measurement device, EEG simulation software and indoor environment control device. We use data as EEG signal data on emotional imagination condition in a comfortable state and logical imagination condition in concentrated state. The noise of measured signal is removed by the ICA algorithm and beta waves are extracted from it. then, it goes through learning and test process using SVM. The subjects were trained to improve the EEG signal accuracy through the EEG simulation software and the average accuracy were 87.69%. The EEG signal from the EEG measurement device is transmitted to the EEG simulation software through the serial communication. then the control command is generated by classifying emotional imagination condition and logical imagination condition. The generated control command is transmitted to the indoor environment control device through the Zigbee communication. In case of the emotional imagination condition, the soft lighting and classical music are outputted. In the logical imagination condition, the learning white noise and bright lighting are outputted. The proposed system can be applied to software and device control based BCI.
Keywords
Internet of Things; EEG; BCI Sensor; Control;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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