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



                                     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.




Ÿ       Yi-Chieh Lee, Wen-Chieh Lin, Jung-Tai King, Li-Wei Ko, Yu-Ting Huang, and Fu-Yin Cherng, “An EEG-based
Approach for Evaluating Audio Notifications under Ambient Sounds
”, ACM Conference on Human Factors in
Computing Systems 2014 (CHI). This paper received CHI2014 Honorable Mention Award.


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