Standard
Monitoring dementia with automatic eye movements analysis. /
Zhang, Yanxia; Wilcockson, Thomas
; Kim, Kwang In et al.
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/ISSN › Conference contribution/Paper › peer-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 HWG, 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). doi: 10.1007/978-3-319-39627-9_26
Author
Zhang, Yanxia ; Wilcockson, Thomas
; Kim, Kwang In et al. /
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 -
