An EEG-based Approach for Evaluating Audio Notifications under Ambient Sounds

Yi-Chieh Lee, Wen-Chieh Lin, Jung-Tai King, Li-Wei Ko, Yu-Ting Huang, Fu-Yin Cherng.

ACM Conference on Human Factors in Computing Systems (CHI) Honorable Mention Award

MMN (100-220 ms) and P3a (200-320 ms) curves


Audio notifications are an important means of prompting users of electronic products. Although useful in most environments, audio notifications are ineffective in certain situations, especially against particular auditory backgrounds or when the user is distracted. Several studies have used behavioral performance to evaluate audio notifications, but these studies failed to achieve consistent results due to factors including user subjectivity and environmental differences; thus, a new method and more objective indicators are necessary. In this study, we propose an approach based on electroencephalography ( EEG ) to evaluate audio notifications by measuring users’ auditory perceptual responses ( mismatch negativity ) and attention shifting ( P3a ). We demonstrate our approach by applying it to the usability testing of audio notifications in realistic scenarios, such as users performing a major task amid ambient noises. Our results open a new perspective for evaluating the design of the audio notifications.

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