TY - GEN
T1 - Synchronization of Vertical Electrooculography Sensor (EOGV) Data on Eye Image Data as Blink Data Validator
AU - Zaini, Ahmad
AU - Suprapto, Yoyon Kusnendar
AU - Yuniarno, Eko Mulyanto
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/17
Y1 - 2020/11/17
N2 - This paper presents research on synchronizing the data of the Electrooculography (EOG) sensor with eye image data when someone blinks. In this study, we carry out the validation of the vertical blink data synchronization from the EOGV sensor to the blinking eye image. The research uses two modalities to get data validity, whether someone blinks or not. There is ambiguity in the two modalities that have different data rates, and both might also have different false data that should not be recognized as signals or blinking eyelid data the same. Data modality matching and data interpolation are implemented to get complete data following the data duration and to get the pair of both modalities. We use linear regression to obtain a formulation of the synchronous relationship between the EOG blinking data sequence and the number of blinking eyelid image frame data.
AB - This paper presents research on synchronizing the data of the Electrooculography (EOG) sensor with eye image data when someone blinks. In this study, we carry out the validation of the vertical blink data synchronization from the EOGV sensor to the blinking eye image. The research uses two modalities to get data validity, whether someone blinks or not. There is ambiguity in the two modalities that have different data rates, and both might also have different false data that should not be recognized as signals or blinking eyelid data the same. Data modality matching and data interpolation are implemented to get complete data following the data duration and to get the pair of both modalities. We use linear regression to obtain a formulation of the synchronous relationship between the EOG blinking data sequence and the number of blinking eyelid image frame data.
KW - Blinking eyelid
KW - Drowsy
KW - EOGV
UR - https://www.scopus.com/pages/publications/85099642744
U2 - 10.1109/CENIM51130.2020.9297880
DO - 10.1109/CENIM51130.2020.9297880
M3 - Conference contribution
AN - SCOPUS:85099642744
T3 - CENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020
SP - 180
EP - 184
BT - CENIM 2020 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020
Y2 - 17 November 2020 through 18 November 2020
ER -