Article | Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden | Data Collection from Persons with Mild Forms of Cognitive Impairment and Healthy Controls - Infrastructure for Classification and Prediction of Dementia
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Title:
Data Collection from Persons with Mild Forms of Cognitive Impairment and Healthy Controls - Infrastructure for Classification and Prediction of Dementia
Author:
Dimitrios Kokkinakis: Department of Swedish, University of Gothenburg, Sweden Kristina Lundholm Fors Lundholm Fors: Department of Swedish, University of Gothenburg, Sweden Eva Björkner: Department of Swedish, University of Gothenburg, Sweden Arto Nordlund: Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Sweden
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Full text (pdf)
Year:
2017
Conference:
Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden
Issue:
131
Article no.:
020
Pages:
172-182
No. of pages:
11
Publication type:
Abstract and Fulltext
Published:
2017-05-08
ISBN:
978-91-7685-601-7
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press, Linköpings universitet


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Cognitive and mental deterioration, such as difficulties with memory and language, are some of the typical phenotypes for most neurodegenerative diseases including Alzheimer’s disease and other dementia forms. This paper describes the first phases of a project that aims at collecting various types of cognitive data, acquired from human subjects in order to study relationships among linguistic and extra-linguistic observations. The project‚Äôs aim is to identify, extract, process, correlate, evaluate, and disseminate various linguistic phenotypes and measurements and thus contribute with complementary knowledge in early diagnosis, monitor progression, or predict individuals at risk. In the near future, automatic analysis of these data will be used to extract various types of features for training, testing and evaluating automatic classifiers that could be used to differentiate individuals with mild symptoms of cognitive impairment from healthy, age-matched controls and identify possible indicators for the early detection of mild forms of cognitive impairment. Features will be extracted from audio recordings (speech signal), the transcription of the audio signals (text) and the raw eye-tracking data.

Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden

Author:
Dimitrios Kokkinakis, Kristina Lundholm Fors Lundholm Fors, Eva Björkner, Arto Nordlund
Title:
Data Collection from Persons with Mild Forms of Cognitive Impairment and Healthy Controls - Infrastructure for Classification and Prediction of Dementia
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Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden

Author:
Dimitrios Kokkinakis, Kristina Lundholm Fors Lundholm Fors, Eva Björkner, Arto Nordlund
Title:
Data Collection from Persons with Mild Forms of Cognitive Impairment and Healthy Controls - Infrastructure for Classification and Prediction of Dementia
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