Measuring the Influences of Musical Parameters on Cognitive and Behavioral Responses to Audio Notifications Using EEG and Large-scale Online Studies

Fu Yin Cherng, Yi Chen Lee, Jung Tai King, Wen-Chieh Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Prior studies have evaluated various designs for audio notifications. However, calls for more in-depth research on how such notifications work, especially at the level of users’ cognitive states, have gone unanswered; and studies evaluating audio notifications with large numbers of participants in multiple environments have been rare. This study conducted an electroencephalography study (N=20) and an online study (N=967) to enhance understandings of how three musical parameters – melody (simple, complex), pitch (high, low), and tempo (fast, slow) – influenced users’ cognition and behaviors. There are eight different notifications with different combinations of these parameters. The online study analyzed the effects of user-specific and environmental information on users’ behaviors while they listened to these notifications. The results revealed that tempo and pitch have the main effect on the speed and strength (accuracy) of users’ cognition and behaviors. The users’ characteristics and environments influenced the effects of these musical parameters.

Original languageEnglish
Title of host publicationCHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages1-12
Number of pages12
ISBN (Electronic)9781450359702
DOIs
StatePublished - 4 May 2019
Event2019 CHI Conference on Human Factors in Computing Systems, CHI 2019 - Glasgow, United Kingdom
Duration: 4 May 20199 May 2019

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2019 CHI Conference on Human Factors in Computing Systems, CHI 2019
Country/TerritoryUnited Kingdom
CityGlasgow
Period4/05/199/05/19

Keywords

  • Audio notifications
  • Brain-computer interface
  • Neuroergonomics

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