Mental workload as personal data: designing a cognitive activity tracker

Tools

Wilson, Max L., Sharon, Natalia, Maior, Horia A., Midha, Serena, Craven, Michael P. and Sharples, Sarah (2018) Mental workload as personal data: designing a cognitive activity tracker. In: 3rd Symposium on Computing and Mental Health, 22nd April 2018, Montreal, Canada. (In Press)

Full text not available from this repository.

Abstract

Research continues to correlate physical signals with mental activity, as opposed to physical activity, with physiological sensors. Further, with the proliferation of wearable technology, it seems imminent that our smart watches can soon keep track of our mental activity as well as our physical activity. Our research is working towards accurately measuring Mental Workload ‘in the wild’ using physiological sensors. While we work towards that goal, however, we have begun to explore the design aspects of representing personal cognitive data to users; analogous to a step counter for physical activity. We present the results of diary studies, focus groups, and prototyping exercises to identify design considerations for future cognitive activity trackers.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/912657
Additional Information: The symposium is part of ACM CHI Conference on Human Factors in Computing Systems (CHI 2018), Montreal, Canada, 21-26 April 2018.
Keywords: Mental Workload; personal data; activity monitoring
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
University of Nottingham, UK > Faculty of Science > School of Computer Science
Related URLs:
URLURL Type
http://mentalhealth.media.mit.edu/UNSPECIFIED
https://chi2018.acm.org/UNSPECIFIED
Depositing User: Wilson, Max
Date Deposited: 26 Mar 2018 09:40
Last Modified: 04 May 2020 19:33
URI: https://eprints.nottingham.ac.uk/id/eprint/50630

Actions (Archive Staff Only)

Edit View Edit View