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Monitoring dementia with automatic eye movements analysis

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Monitoring dementia with automatic eye movements analysis. / Zhang, Yanxia; Wilcockson, Thomas; Kim, Kwang In; Crawford, Trevor Jeremy; Gellersen, Hans-Werner Georg; Sawyer, Peter Harvey.

Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II. ed. / Ireneusz Czarnowski; Alfonso Mateos Caballero; Robert J. Howlett; Lakhmi C. Jain. Springer, 2016. p. 299-309 (Smart Innovation, Systems and Technologies; Vol. 57).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Zhang, Y, Wilcockson, T, Kim, KI, Crawford, TJ, Gellersen, H-WG & Sawyer, PH 2016, Monitoring dementia with automatic eye movements analysis. in I Czarnowski, AM Caballero, RJ Howlett & LC Jain (eds), Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II. Smart Innovation, Systems and Technologies, vol. 57, Springer, pp. 299-309, 8th KES International Conference on Intelligent Decision Technologies (KES-IDT), Puerto de la Cruz, Spain, 15/06/16. https://doi.org/10.1007/978-3-319-39627-9_26

APA

Zhang, Y., Wilcockson, T., Kim, K. I., Crawford, T. J., Gellersen, H-W. G., & Sawyer, P. H. (2016). Monitoring dementia with automatic eye movements analysis. In I. Czarnowski, A. M. Caballero, R. J. Howlett, & L. C. Jain (Eds.), Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II (pp. 299-309). (Smart Innovation, Systems and Technologies; Vol. 57). Springer. https://doi.org/10.1007/978-3-319-39627-9_26

Vancouver

Zhang Y, Wilcockson T, Kim KI, Crawford TJ, Gellersen H-WG, Sawyer PH. Monitoring dementia with automatic eye movements analysis. In Czarnowski I, Caballero AM, Howlett RJ, Jain LC, editors, Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II. Springer. 2016. p. 299-309. (Smart Innovation, Systems and Technologies). https://doi.org/10.1007/978-3-319-39627-9_26

Author

Zhang, Yanxia ; Wilcockson, Thomas ; Kim, Kwang In ; Crawford, Trevor Jeremy ; Gellersen, Hans-Werner Georg ; Sawyer, Peter Harvey. / Monitoring dementia with automatic eye movements analysis. Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II. editor / Ireneusz Czarnowski ; Alfonso Mateos Caballero ; Robert J. Howlett ; Lakhmi C. Jain. Springer, 2016. pp. 299-309 (Smart Innovation, Systems and Technologies).

Bibtex

@inproceedings{c6b1f71893f749328bb7302c82797d30,
title = "Monitoring dementia with automatic eye movements analysis",
abstract = "Eye movement patterns are found to reveal human cognitive and mental states that can not be easily measured by other biological signals. With the rapid development of eye tracking technologies, there are growing interests in analysing gaze data to infer information about people{\textquoteright} cognitive states, tasks and activities performed in naturalistic environments. In this paper, we investigate the link between eye movements and cognitive function. We conducted experiments to record subject{\textquoteright}s eye movements during video watching. By using computational methods, we identified eye movement features that are correlated to people{\textquoteright}s cognitive health measures obtained through the standard cognitive tests. Our results show that it is possible to infer people{\textquoteright}s cognitive function by analysing natural gaze behaviour. This work contributes an initial understanding of monitoring cognitive deterioration and dementia with automatic eye movement analysis.",
keywords = "Machine learning, Eye movements analysis, Health monitoring, Dementia, Cognitive function, COGNITIVE IMPAIRMENT, ALZHEIMERS-DISEASE, INHIBITORY CONTROL, MEMORY",
author = "Yanxia Zhang and Thomas Wilcockson and Kim, {Kwang In} and Crawford, {Trevor Jeremy} and Gellersen, {Hans-Werner Georg} and Sawyer, {Peter Harvey}",
year = "2016",
month = jun,
day = "18",
doi = "10.1007/978-3-319-39627-9_26",
language = "English",
isbn = "9783319396262",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer",
pages = "299--309",
editor = "Ireneusz Czarnowski and Caballero, {Alfonso Mateos} and Howlett, {Robert J.} and Jain, {Lakhmi C.}",
booktitle = "Intelligent Decision Technologies 2016",
note = "8th KES International Conference on Intelligent Decision Technologies (KES-IDT) ; Conference date: 15-06-2016 Through 17-06-2016",

}

RIS

TY - GEN

T1 - Monitoring dementia with automatic eye movements analysis

AU - Zhang, Yanxia

AU - Wilcockson, Thomas

AU - Kim, Kwang In

AU - Crawford, Trevor Jeremy

AU - Gellersen, Hans-Werner Georg

AU - Sawyer, Peter Harvey

PY - 2016/6/18

Y1 - 2016/6/18

N2 - Eye movement patterns are found to reveal human cognitive and mental states that can not be easily measured by other biological signals. With the rapid development of eye tracking technologies, there are growing interests in analysing gaze data to infer information about people’ cognitive states, tasks and activities performed in naturalistic environments. In this paper, we investigate the link between eye movements and cognitive function. We conducted experiments to record subject’s eye movements during video watching. By using computational methods, we identified eye movement features that are correlated to people’s cognitive health measures obtained through the standard cognitive tests. Our results show that it is possible to infer people’s cognitive function by analysing natural gaze behaviour. This work contributes an initial understanding of monitoring cognitive deterioration and dementia with automatic eye movement analysis.

AB - Eye movement patterns are found to reveal human cognitive and mental states that can not be easily measured by other biological signals. With the rapid development of eye tracking technologies, there are growing interests in analysing gaze data to infer information about people’ cognitive states, tasks and activities performed in naturalistic environments. In this paper, we investigate the link between eye movements and cognitive function. We conducted experiments to record subject’s eye movements during video watching. By using computational methods, we identified eye movement features that are correlated to people’s cognitive health measures obtained through the standard cognitive tests. Our results show that it is possible to infer people’s cognitive function by analysing natural gaze behaviour. This work contributes an initial understanding of monitoring cognitive deterioration and dementia with automatic eye movement analysis.

KW - Machine learning

KW - Eye movements analysis

KW - Health monitoring

KW - Dementia

KW - Cognitive function

KW - COGNITIVE IMPAIRMENT

KW - ALZHEIMERS-DISEASE

KW - INHIBITORY CONTROL

KW - MEMORY

U2 - 10.1007/978-3-319-39627-9_26

DO - 10.1007/978-3-319-39627-9_26

M3 - Conference contribution/Paper

SN - 9783319396262

T3 - Smart Innovation, Systems and Technologies

SP - 299

EP - 309

BT - Intelligent Decision Technologies 2016

A2 - Czarnowski, Ireneusz

A2 - Caballero, Alfonso Mateos

A2 - Howlett, Robert J.

A2 - Jain, Lakhmi C.

PB - Springer

T2 - 8th KES International Conference on Intelligent Decision Technologies (KES-IDT)

Y2 - 15 June 2016 through 17 June 2016

ER -