Intelligence-IoT

Runtime Environment

Windows 10 64bit

SSVEP

• 27-inch LCD monitor, 60Hz

• Biosemi ActiveTwo

Drowsiness detection

• Empatica E4

Development Environment

Biosemi Labview installation

• https://www.biosemi.com/download.htm

• Version : 8.06

SSVEP

• Python3 installation

  • https://www.python.org/downloads/

• Spyder3 installation

   pip install spyder
  

• PsychoPy3.0.0 installation

  • https://github.com/psychopy/psychopy/releases

Drowsiness detection

• Python3 installation

  • https://www.python.org/downloads/

• JAVA – Android Studio installation

  • https://developer.android.com/studio/?hl=ko

Get Started

• SSVEP

  • Open the Biosemi Labview and setting the option(sampling rate, channel, etc.)

  • Setting the parameter of python

  • Start the Boisemi Labview

  • Execute python

• Drowsiness detection

  • Wrist wear and power on the Empatica E4 device

  • Connection with a PPG measurement program

  • Button control of the PPG measurement program

  • Offline: For storing PPG data

  • Online: Real-time PPG measurement and drowsiness recognition

Overall description of source code

• SSVEP

  • Creating the visual stimulus of SSVEP

  • Acquisition of EEG data of SSVEP

  • Preprocessing the EEG data of SSVEP acquired.

  • Feature Extraction (Common Spatial Pattern, Canonical Correlation Analysis, etc.)

  • Classification (Linear Discriminant Analysis, Support Vector Machine)

• Drowsiness detection

  • Acquisition of user’s PPG data using PPG measuring device (‘Empatica E4’)

  • Real-time communication of acquired PPG data

  • Classifier model training using acquired PPG data (offline)

  • User state classification using PPG data acquired in real time (online)