Linguistic and extra-linguistic parameters for early detection of cognitive impairment
With an increasing aging pyramid the number of people with cognitive dysfunctions, such as various types of dementia, has grown at a high rate. However, years before the clinical onset symptoms of dementia, patients exhibit serious deficits in their oral and written communication and visual short-term memory, signs that can be measured and serve as a complement to medical evidence to discriminate the performance of healthy (elderly) controls or even predict poor cognitive health in late life. The aim of the project (2016-2019) is to apply and explore automatic linguistic analysis to language samples produced by persons at various stages of cognitive decline in order to identify important linguistic markers that can be used as a complementary, early diagnostic, prognostic or screening tool. Language, or rather linguistic performance in this context, are various forms of spoken or written language production and comprehension, e.g. transcripts of audio-recorded utterances; accessible language-based interaction through the web or measures from an eye tracking device. A correct and timely diagnosis of neurodegenerative brain disorders, such as Alzheimer’s disease, and differentiation of various types of dementia is of great importance to clinicians. The project intends to perform research in the areas of Natural Language Processing (NLP) that will allow us to broaden opportunities for multidisciplinary research activities between researchers from humanities, computer sciences and medicine.
The aim of the project is to adapt, develop and test methods that in isolation have shown promising outcomes on tasks related to the project’s focus; i.e. (early) detection of dementia, differentiating between various dementia types and controls and also increase our understanding of the cognitive processes that underlie written text and certain forms of spoken language production. Unlike previous models, based solely on a certain aspect of language abilities (i.e. on written or spoken language alone), the project is comprehensive and more likely to provide new insights in the area of dementia detection and improve practices applied so far. The project will build on the success stories of the past and focus on the interplay between various types of technologies that hold the potential to provide reliable estimates for the detection of cognitive decline. The project emphasizes its interdisciplinary nature, by bringing together researchers from humanities (computational linguistics/language technology), computer science and medicine, and foresees the development of a comprehensive set of novel analytic approaches not explored jointly in the past. Discovering evidence about linguistic performance and identifying whether the addition of new ways for investigating, combining and evaluating measurement and other parameters for improvement of established models can advance our understanding of: i) the boundaries between normal aging and dementia; ii) its effects on linguistic performance extrapolated from various sources and iii) whether effects of cognitive decline can be seen across (daily) language production. NLP in health care has recently started to receive increasing attention worldwide by addressing questions where "language", in a wide sense, seems to have a lot to offer. New ideas and application of methods from computational linguistics and NLP to real-world problems in health are welcome and we look forward to a close collaboration with prof. Graeme Hirst and his colleagues, whose novel research in the area of detecting AD, and other forms of cognitive decline is leading in finding new ways for tackling such degenerative conditions.