| 1. |
- Björkner, Eva, et al.
(författare)
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Voice acoustic parameters for detecting signs of early cognitive impairment
- 2017
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Ingår i: PEVOC (PanEuropean Voice Conference) 12, August 30th - September 1st 2017, Ghent, Belgium.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Aiding the detection of very early cognitive impairment in Alzheimer's disease (AD) and assessing the disease progression are essential foundations for effective psychological assessment, diagnosis and planning. Efficient tools for routine dementia screening in primary health care, particularly non-invasive and cost-effective methods, are desirable. The aim of this study is to find out if voice acoustic analysis can be a useful tool for detecting signs of early cognitive impairment.
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| 2. |
- Fraser, Kathleen, 1984, et al.
(författare)
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An analysis of eye-movements during reading for the detection of mild cognitive impairment
- 2017
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Ingår i: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. September 9-11, 2017 Copenhagen, Denmark / Editors Martha Palmer, Rebecca Hwa, Sebastian Riedel. - : Association for Computational Linguistics. - 9781945626838
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Konferensbidrag (refereegranskat)abstract
- We present a machine learning analysis of eye-tracking data for the detection of mild cognitive impairment, a decline in cognitive abilities that is associated with an increased risk of developing dementia. We compare two experimental configurations (reading aloud versus reading silently), as well as two methods of combining information from the two trials (concatenation and merging). Additionally, we annotate the words being read with information about their frequency and syntactic category, and use these annotations to generate new features. Ultimately, we are able to distinguish between participants with and without cognitive impairment with up to 86% accuracy.
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| 3. |
- Kokkinakis, Dimitrios, 1965, et al.
(författare)
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A Swedish Cookie-Theft Corpus
- 2018
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Ingår i: LREC 2018, 11th edition of the Language Resources and Evaluation Conference, 7-12 May 2018, Miyazaki (Japan) / Editors: Nicoletta Calzolari (Conference chair), Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Takenobu Tokunaga. - : European Language Resources Association. - 9791095546009
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Konferensbidrag (refereegranskat)abstract
- Language disturbances can be a diagnostic marker for neurodegenerative diseases, such as Alzheimer’s disease, at earlier stages, and connected speech analysis provides a non-invasive and easy-to-assess measure for determining aspects of the severity of language impairment. In this paper we focus on the development of a corpus consisting of audio recordings of picture descriptions of the Cookie-theft, produced by Swedish speakers, and accompanying transcriptions. The speech elicitation procedure provides an established method of obtaining highly constrained samples of connected speech that can allow us to study the intricate interactions between various linguistic levels and cognition. We chose the Cookie-theft picture since it is a standardized test that has been used in various studies in the past, and therefore comparisons can be made based on previous results. This type of picture description task might be useful for detecting subtle language deficits in patients with subjective and mild cognitive impairment. The resulting corpus is a new, rich and multi-faceted resource for the investigation of linguistic characteristics of connected speech and a unique data set that provides a rich resource for (future) research and experimentation in many areas, and of language impairment in particular. The information in the corpus can also be combined and correlated with other collected data about the speakers, such as neuropsychological tests, imaging and brain physiology markers and cerebrospinal fluid markers.
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| 4. |
- Kokkinakis, Dimitrios, 1965, et al.
(författare)
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Data Collection from Persons with Mild Forms of Cognitive Impairment and Healthy Controls - Infrastructure for Classification and Prediction of Dementia
- 2017
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Ingår i: Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden. - Linköping : Linköping University Electronic Press, Linköpings universitet. - 1650-3686 .- 1650-3740. - 9789176856017
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Konferensbidrag (refereegranskat)abstract
- 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’s 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.
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| 5. |
- Kokkinakis, Dimitrios, 1965, et al.
(författare)
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Data Resource Acquisition from People at Various Stages of Cognitive Decline – Design and Exploration Considerations
- 2016
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Ingår i: The Seventh International Workshop on Health Text Mining and Information Analysis (Louhi). November 5, 2016, Austin, Texas, USA.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we are introducing work in progress towards the development of an infrastructure (i.e., design, methodology, creation and description) of linguistic and extra-linguistic data samples acquired from people diagnosed with subjective or mild cognitive impairment and healthy, age-matched controls. The data we are currently collecting consists of various types of modalities; i.e. audio-recorded spoken language samples; transcripts of the audio recordings (text) and eye tracking measurements. The integration of the extra-linguistic information with the linguistic phenotypes and measurements elicited from audio and text, will be used to extract, evaluate and model features to be used in machine learning experiments. In these experiments, classification models that will be trained, that will be able to learn from the whole or a subset of the data to make predictions on new data in order to test how well a differentiation between the aforementioned groups can be made. Features will be also correlated with measured outcomes from e.g. language-related scores, such as word fluency, in order to investigate whether there are relationships between various variables.
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| 6. |
- Kokkinakis, Dimitrios, 1965, et al.
(författare)
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Specifications and Methodology for Language-Related Data Acquisition and Analysis in the Domain of Dementia Diagnostics
- 2016
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Ingår i: The Sixth Swedish Language Technology Conference (SLTC) Umeå University, 17-18 November, 2016.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper outlines the initial stages of a project that aims to build and use a corpus with data samples acquired from people diagnosed with subjective or mild cognitive impairment and healthy, age-matched controls. The data we are currently collecting consists of audio-recorded spoken language samples; transcripts of the audio recordings and eye tracking measurements. From these data we plan to extract, evaluate and model features to be used for learning classification models in order to test how well a differentiation between the aforementioned subject groups can be made. Features will be also correlated with outcomes from e.g. other language-related scores, such as word fluency, in order to investigate whether there are relationships between various variables.
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