{'fraction_non_alphanumeric': 0.016538037486218304, 'fraction_numerical': 0.0, 'mean_word_length': 5.439716312056738, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
On the Repeatability of EEG-Based Image Quality Assessment

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.