Options
An exploratory study integrating deep learning in digital clock drawing test on consumer platforms for enhanced detection of mild cognitive impairment
Loading...
Type
Conference paper
Citation
Kuok, B. Z. W., Koh, M. H. S., & Lim, K. Y. T. (2024). An exploratory study integrating deep learning in digital clock drawing test on consumer platforms for enhanced detection of mild cognitive impairment. In C. Stephanidis, M. Antona, S. Ntoa, & G. Salvendy (Eds.), HCI International 2024 Posters: 26th International Conference on Human-Computer Interaction (pp. 175–181). Springer. https://doi.org/10.1007/978-3-031-61947-2_20
Abstract
Dementia is set to become a major global health challenge. Studies show that there is a significant surge in cases of adults above 40 living with dementia. This alarming increase is due to various factors and early detection of dementia can allow for proper treatment to be administered.
There exist various screening methods, but all come with shortcomings, particularly, subjectivity in hand-scored tests. Digitalisation of the tools mitigates this concern but can bring about newer concerns such as feasibility.
The clock drawing test is a simple pen and paper test, to differentiate normal individuals from those with cognitive impairment, such as dementia. Our project aims to enhance the use of the clock drawing test, via digitalising it and equipping it with machine learning capabilities.
We aim to offer an increased potential for early detection of cognitive impairment, to overall, improve the state of dementia detection already in practice.
Date Issued
2024
ISBN
9783031619465 (print)
9783031619472 (online)
Publisher
Springer
Series
Communications in Computer and Information Science, vol. 2115