Cognitive state prediction using an em algorithm applied to Gamma distributed data

Ali Yousefi, Angelique C. Paulk, Thilo Deckersbach, Darin D. Dougherty, Emad N. Eskandar, Alik S. Widge, Uri T. Eden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Behavioral tests are widely used to quantify features of cognitive processing. For a large class of behavioral signals, the observed variables are non-Gaussian and dynamic; classical estimation algorithms are ill-suited to modeling such data. In this research, we propose a mathematical framework to predict a cognitive state variable related to behavioral signals, which are best modeled using a Gamma distribution. The proposed algorithm combines a Gamma Smoother and EM algorithm in the prediction process. The algorithm is applied to reaction time recorded from subjects performing a Multi-Source Interference Task (MSIT) to dynamically quantify their cognitive flexibility through the course of the experiment.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7819-7824
Number of pages6
Volume2015-November
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period8/25/158/29/15

Fingerprint

Reaction Time
Data structures
Processing
Research
Experiments
Behavior Rating Scale

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Yousefi, A., Paulk, A. C., Deckersbach, T., Dougherty, D. D., Eskandar, E. N., Widge, A. S., & Eden, U. T. (2015). Cognitive state prediction using an em algorithm applied to Gamma distributed data. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 (Vol. 2015-November, pp. 7819-7824). [7320205] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7320205

Cognitive state prediction using an em algorithm applied to Gamma distributed data. / Yousefi, Ali; Paulk, Angelique C.; Deckersbach, Thilo; Dougherty, Darin D.; Eskandar, Emad N.; Widge, Alik S.; Eden, Uri T.

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. p. 7819-7824 7320205.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yousefi, A, Paulk, AC, Deckersbach, T, Dougherty, DD, Eskandar, EN, Widge, AS & Eden, UT 2015, Cognitive state prediction using an em algorithm applied to Gamma distributed data. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. vol. 2015-November, 7320205, Institute of Electrical and Electronics Engineers Inc., pp. 7819-7824, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, 8/25/15. https://doi.org/10.1109/EMBC.2015.7320205
Yousefi A, Paulk AC, Deckersbach T, Dougherty DD, Eskandar EN, Widge AS et al. Cognitive state prediction using an em algorithm applied to Gamma distributed data. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Vol. 2015-November. Institute of Electrical and Electronics Engineers Inc. 2015. p. 7819-7824. 7320205 https://doi.org/10.1109/EMBC.2015.7320205
Yousefi, Ali ; Paulk, Angelique C. ; Deckersbach, Thilo ; Dougherty, Darin D. ; Eskandar, Emad N. ; Widge, Alik S. ; Eden, Uri T. / Cognitive state prediction using an em algorithm applied to Gamma distributed data. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. pp. 7819-7824
@inproceedings{3ab1f179dc1e47a1b6a92a420715ffae,
title = "Cognitive state prediction using an em algorithm applied to Gamma distributed data",
abstract = "Behavioral tests are widely used to quantify features of cognitive processing. For a large class of behavioral signals, the observed variables are non-Gaussian and dynamic; classical estimation algorithms are ill-suited to modeling such data. In this research, we propose a mathematical framework to predict a cognitive state variable related to behavioral signals, which are best modeled using a Gamma distribution. The proposed algorithm combines a Gamma Smoother and EM algorithm in the prediction process. The algorithm is applied to reaction time recorded from subjects performing a Multi-Source Interference Task (MSIT) to dynamically quantify their cognitive flexibility through the course of the experiment.",
author = "Ali Yousefi and Paulk, {Angelique C.} and Thilo Deckersbach and Dougherty, {Darin D.} and Eskandar, {Emad N.} and Widge, {Alik S.} and Eden, {Uri T.}",
year = "2015",
month = "11",
day = "4",
doi = "10.1109/EMBC.2015.7320205",
language = "English (US)",
volume = "2015-November",
pages = "7819--7824",
booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Cognitive state prediction using an em algorithm applied to Gamma distributed data

AU - Yousefi, Ali

AU - Paulk, Angelique C.

AU - Deckersbach, Thilo

AU - Dougherty, Darin D.

AU - Eskandar, Emad N.

AU - Widge, Alik S.

AU - Eden, Uri T.

PY - 2015/11/4

Y1 - 2015/11/4

N2 - Behavioral tests are widely used to quantify features of cognitive processing. For a large class of behavioral signals, the observed variables are non-Gaussian and dynamic; classical estimation algorithms are ill-suited to modeling such data. In this research, we propose a mathematical framework to predict a cognitive state variable related to behavioral signals, which are best modeled using a Gamma distribution. The proposed algorithm combines a Gamma Smoother and EM algorithm in the prediction process. The algorithm is applied to reaction time recorded from subjects performing a Multi-Source Interference Task (MSIT) to dynamically quantify their cognitive flexibility through the course of the experiment.

AB - Behavioral tests are widely used to quantify features of cognitive processing. For a large class of behavioral signals, the observed variables are non-Gaussian and dynamic; classical estimation algorithms are ill-suited to modeling such data. In this research, we propose a mathematical framework to predict a cognitive state variable related to behavioral signals, which are best modeled using a Gamma distribution. The proposed algorithm combines a Gamma Smoother and EM algorithm in the prediction process. The algorithm is applied to reaction time recorded from subjects performing a Multi-Source Interference Task (MSIT) to dynamically quantify their cognitive flexibility through the course of the experiment.

UR - http://www.scopus.com/inward/record.url?scp=84953299061&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84953299061&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2015.7320205

DO - 10.1109/EMBC.2015.7320205

M3 - Conference contribution

C2 - 26738105

AN - SCOPUS:84953299061

VL - 2015-November

SP - 7819

EP - 7824

BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -