Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment

Ann Gledson; Dommy Asfiandy; Joseph Mellor; Thamer Omer Faraj Ba-Dhfari; Gemma Stringer; Samuel Couth; Alistair Burns; Iracema Leroi; Xiao-Jun Zeng; John Keane; Christopher Neil Bull; Paul Edward Rayson; Alistair Gordon Simpson Sutcliffe; Peter Harvey Sawyer

doi:10.1109/ICHI.2016.22

Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment

Ann Gledson, Dommy Asfiandy, Joseph Mellor, Thamer Omer Faraj Ba-Dhfari, Gemma Stringer, Samuel Couth, Alistair Burns, Iracema Leroi, Xiao-Jun Zeng, John Keane, Christopher Neil Bull, Paul Edward Rayson, Alistair Gordon Simpson Sutcliffe, Peter Harvey Sawyer

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Chapter

Abstract

We present a desktop monitoring application that combines keyboard, mouse, desktop and application-level activities. It has been developed to discover differences in cognitive functioning amongst older computer users indicative of mild cognitive impairment (MCI). Following requirements capture from clinical domain experts, the tool collects all Microsoft Windows events deemed potentially useful for detecting early clinical indicators of dementia, with a view to further analysis to determine the most pertinent. Further requirements capture from potential end-users has resulted in a system that has little impact on users? daily activities and ensures data security from initial recording of events through to data analysis. We describe two experiments: firstly, volunteers were asked to perform a short set of known tasks; the second (ongoing) experiment is a longitudinal study, with the software currently successfully running on participants? computers.

Original language	English
Title of host publication	2016 IEEE International Conference on Healthcare Informatics (ICHI)
Publisher	IEEE
ISBN (Print)	9781509061181
DOIs	https://doi.org/10.1109/ICHI.2016.22
Publication status	Published - 4 Oct 2016

Bibliographical note

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords

dementia
mouse dynamics
keystroke dynamics
data mining
medical informatics

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10.1109/ICHI.2016.22

Aggregating_Mouse_keyboard_and_higher_level_events_Cam_ready
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Gledson, A., Asfiandy, D., Mellor, J., Omer Faraj Ba-Dhfari, T., Stringer, G., Couth, S., Burns, A., Leroi, I., Zeng, X.-J., Keane, J., Bull, C. N., Rayson, P. E., Sutcliffe, A. G. S., & Sawyer, P. H. (2016). Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment. In 2016 IEEE International Conference on Healthcare Informatics (ICHI) IEEE. https://doi.org/10.1109/ICHI.2016.22

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abstract = "We present a desktop monitoring application that combines keyboard, mouse, desktop and application-level activities. It has been developed to discover differences in cognitive functioning amongst older computer users indicative of mild cognitive impairment (MCI). Following requirements capture from clinical domain experts, the tool collects all Microsoft Windows events deemed potentially useful for detecting early clinical indicators of dementia, with a view to further analysis to determine the most pertinent. Further requirements capture from potential end-users has resulted in a system that has little impact on users? daily activities and ensures data security from initial recording of events through to data analysis. We describe two experiments: firstly, volunteers were asked to perform a short set of known tasks; the second (ongoing) experiment is a longitudinal study, with the software currently successfully running on participants? computers.",

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Gledson, A, Asfiandy, D, Mellor, J, Omer Faraj Ba-Dhfari, T, Stringer, G, Couth, S, Burns, A, Leroi, I, Zeng, X-J, Keane, J, Bull, CN, Rayson, PE, Sutcliffe, AGS & Sawyer, PH 2016, Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment. in 2016 IEEE International Conference on Healthcare Informatics (ICHI). IEEE. https://doi.org/10.1109/ICHI.2016.22

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AU - Couth, Samuel

AU - Burns, Alistair

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AU - Zeng, Xiao-Jun

AU - Keane, John

AU - Bull, Christopher Neil

AU - Rayson, Paul Edward

AU - Sutcliffe, Alistair Gordon Simpson

AU - Sawyer, Peter Harvey

N1 - © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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N2 - We present a desktop monitoring application that combines keyboard, mouse, desktop and application-level activities. It has been developed to discover differences in cognitive functioning amongst older computer users indicative of mild cognitive impairment (MCI). Following requirements capture from clinical domain experts, the tool collects all Microsoft Windows events deemed potentially useful for detecting early clinical indicators of dementia, with a view to further analysis to determine the most pertinent. Further requirements capture from potential end-users has resulted in a system that has little impact on users? daily activities and ensures data security from initial recording of events through to data analysis. We describe two experiments: firstly, volunteers were asked to perform a short set of known tasks; the second (ongoing) experiment is a longitudinal study, with the software currently successfully running on participants? computers.

AB - We present a desktop monitoring application that combines keyboard, mouse, desktop and application-level activities. It has been developed to discover differences in cognitive functioning amongst older computer users indicative of mild cognitive impairment (MCI). Following requirements capture from clinical domain experts, the tool collects all Microsoft Windows events deemed potentially useful for detecting early clinical indicators of dementia, with a view to further analysis to determine the most pertinent. Further requirements capture from potential end-users has resulted in a system that has little impact on users? daily activities and ensures data security from initial recording of events through to data analysis. We describe two experiments: firstly, volunteers were asked to perform a short set of known tasks; the second (ongoing) experiment is a longitudinal study, with the software currently successfully running on participants? computers.

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PB - IEEE

ER -

Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment

Abstract

Bibliographical note

Keywords

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