Electroencephalography (EEG) has attracted much attention because it allows to monitor user states in real time and is applicable to applications for improvement of multimedia user experience. The repeatability of EEG-based perceptual response analysis is critical for the reliability of such applications, which has not been sufficiently addressed in previous studies. In this paper, we evaluate the repeatability of EEG-based image quality assessment. We repeatedly perform the same experiment for three successive days. Then, we design a classification system that discriminates the quality of images based on EEG, whose performance is examined across the data collected in different days. We reveal that the repeatability of image quality evaluation using EEG decreases as time goes and the memory effect intensifies the loss of repeatability.
|Title of host publication||Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||4|
|Publication status||Published - 2019 Jan 16|
|Event||2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan|
Duration: 2018 Oct 7 → 2018 Oct 10
|Name||Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018|
|Conference||2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018|
|Period||18/10/7 → 18/10/10|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the “ICT Consilience Creative Program” (IITP-2018-2017-0-01015) supervised by the IITP (Institute for Information & communications Technology Promotion).
© 2018 IEEE.
All Science Journal Classification (ASJC) codes
- Information Systems
- Information Systems and Management
- Health Informatics
- Artificial Intelligence
- Computer Networks and Communications
- Human-Computer Interaction