Journal of rehabilitation welfare engineering & assistive technology (재활복지공학회논문지)

Rehabilitation Engineering And Assistive Technology Society of Korea (한국재활복지공학회)
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Indoor Environment Control System based EEG Signal and Internet of Things

EEG 신호 및 사물인터넷 기반 실내 환경 제어 시스템

  • 정해성 (인하대학교 컴퓨터정보공학과) ;
  • 이상민 (인하대학교 전자공학과) ;
  • 권장우 (인하대학교 컴퓨터정보공학과)
  • Received : 2016.11.28
  • Accepted : 2017.01.06
  • Published : 2017.02.28
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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.

EEG 신호는 신체적으로 불편함을 가지고 있는 사용자에게서도 동일하게 발생되는 신호로써 차세대 인터페이스로 각광받고 있다. 본 논문에서는 사용자의 EEG 신호를 이용하여 감성적인 정보처리와 논리적인 정보처리를 보조하는 실내 환경을 제어하는 사물인터넷 시스템을 제안한다. 제안된 시스템은 EEG 측정 장치, EEG 시뮬레이션 소프트웨어, 실내 환경 제어 장치로 구성된다. 실험 데이터로는 편안한 상태에서 발생되는 감성적인 정보처리에 대한 EEG 신호 데이터와 집중 시에 발생되는 논리적인 정보처리에 대한 EEG 신호 데이터를 사용한다. 측정된 신호에서는 ICA 알고리즘이 적용하여 잡음이 제거되고 베타파만을 추출한다. 이후 SVM을 통한 학습 및 테스트 과정을 거치게 된다. 피험자는 EEG 시뮬레이션 소프트웨어를 통해 EEG 신호 정확도 향상 훈련을 거친 결과 평균 82.69%의 정확도를 보였다. EEG 측정 장치로부터 입력되는 EEG 신호는 Serial 통신을 통해 EEG 시뮬레이션 소프트웨어로 전송되며 감성적인 정보처리와 논리적인 정보처리를 분류하여 제어 명령이 생성된다. 이후 생성된 제어 명령은 Zigbee 통신을 통해 실내 환경 제어 장치로 전달되어 감성적인 정보처리일 경우 은은한 조명과 클래식 음악이 출력되고 논리적인 정보처리일 경우 밝은 조명과 함께 학습용 백색소음이 출력된다. 제안한 시스템은 BCI 기반 소프트웨어 및 디바이스 제어에 응용될 수 있어 몸이 불편한 사용자가 자신의 신체적인 한계를 극복하는 것을 가능하게 한다.

Keywords

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