A Dataset for classification of road and types using EOG smart glasses

Citation Author(s):
Rafał
Doniec
Silesian University of Technology
Natalia
Piaseczna
Silesian University of Technology
Frédéric
Li
University of Lübeck
Submitted by:
Natalia Piaseczna
Last updated:
Sun, 09/04/2022 - 06:00
DOI:
10.21227/4yte-5s06
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Abstract 

For the data acquisition we used JINS MEME smart glasses -- a device furnished with three-point EOG and six-axis inertial measurement unit (IMU) with an accelerometer and a gyroscope. The sampling frequency of the acquired signals is 100 Hz. The data are transmitted to a computer via Bluetooth or USB and can be exported to CSV file.

Data were acquired under real road conditions from 30 healthy subjects, including twenty experienced drivers and ten students attending a driving school. 16 males and 14 females with average age = 38 +-17 participated in the study.

All data were labeled during the drive and then divided the into four groups regarding the type of the road:

  1. highway (autostrada),
  2. city road (ruch miasto),
  3. undeveloped area (miasto niezabudowane),
  4. housing estate (ruch osiedle),

The labeling process was performed manually by simply putting a marker when the particular type of road started and ended.

Instructions: 

Each .csv contains ten columns:

  1. ACC_X
  2. ACC_Y
  3. ACC_Z
  4. GYRO_X
  5. GYRO_Y
  6. GYRO_Z
  7. EOG_L
  8. EOG_R
  9. EOG_H
  10. EOG_V