Mental workload as personal data: designing a cognitive activity tracker

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 acti...

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Main Authors: Wilson, Max L., Sharon, Natalia, Maior, Horia A., Midha, Serena, Craven, Michael P., Sharples, Sarah
Format: Conference or Workshop Item
Published: 2018
Subjects:
Online Access:https://eprints.nottingham.ac.uk/50630/
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author Wilson, Max L.
Sharon, Natalia
Maior, Horia A.
Midha, Serena
Craven, Michael P.
Sharples, Sarah
author_facet Wilson, Max L.
Sharon, Natalia
Maior, Horia A.
Midha, Serena
Craven, Michael P.
Sharples, Sarah
author_sort Wilson, Max L.
building Nottingham Research Data Repository
collection Online Access
description 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.
first_indexed 2025-11-14T20:17:35Z
format Conference or Workshop Item
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institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T20:17:35Z
publishDate 2018
recordtype eprints
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spelling nottingham-506302020-05-04T19:33:06Z https://eprints.nottingham.ac.uk/50630/ Mental workload as personal data: designing a cognitive activity tracker Wilson, Max L. Sharon, Natalia Maior, Horia A. Midha, Serena Craven, Michael P. Sharples, Sarah 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. 2018-02-20 Conference or Workshop Item PeerReviewed 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) Mental Workload; personal data; activity monitoring
spellingShingle Mental Workload; personal data; activity monitoring
Wilson, Max L.
Sharon, Natalia
Maior, Horia A.
Midha, Serena
Craven, Michael P.
Sharples, Sarah
Mental workload as personal data: designing a cognitive activity tracker
title Mental workload as personal data: designing a cognitive activity tracker
title_full Mental workload as personal data: designing a cognitive activity tracker
title_fullStr Mental workload as personal data: designing a cognitive activity tracker
title_full_unstemmed Mental workload as personal data: designing a cognitive activity tracker
title_short Mental workload as personal data: designing a cognitive activity tracker
title_sort mental workload as personal data: designing a cognitive activity tracker
topic Mental Workload; personal data; activity monitoring
url https://eprints.nottingham.ac.uk/50630/