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Updated: Mar 6, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Adaptive systems for cognitive impairments: a systematic review of current trends and future directions
Noor Alakkas1,2, Sajjad Mahmood1,3
1Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Purpose:
Cognitive impairment is a common disorder that affects individuals across different age groups and cognitive abilities, posing a significant challenge for software designers and developers of inclusive and accessible information and communication technology (ICT). Adaptive systems emerged as a solution for providing ICT solutions that provide personalised sessions tailored to the user's cognitive abilities. This review aims to investigate the current state of adaptive systems designed for users with cognitive impairments and identify prevailing trends, gaps, and future research directions in the field.
Method:
A systematic literature review (SLR) was conducted following PRISMA guidelines. A total of 71 primary studies were selected after applying the inclusion/exclusion criteria and quality assessment.
Results:
Our results indicate that recent studies are focusing on developing educational web-based applications for children with mild neurodevelopmental disorders, utilising user-centred approaches and model-driven models during the design process, while following Web Content Accessibility Guidelines. Depending on explicit data collection from users, primarily providing graphical design and behavioural adaptation elements, using rule-based techniques, with a lack of utilisation of feedback loop techniques. The evaluation of given systems often lacked a large number of participants from the target population.
Conclusion:
The findings of this review offer insights for researchers, developers, and designers of adaptive systems for users with cognitive impairments, outlining essential design considerations and underexplored areas. This aids the development of effective and inclusive adaptive systems for users with cognitive impairments.
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