Abstract
Early detection of cognitive decline is of utmost importance, as research suggests that certain risk factors can be modified to slow down or even prevent the onset of Alzheimer’s disease. However, traditional cognitive assessments require a significant amount of time and resources, which can burden both the participants and the clinicians administering the tests. This study developed a new digital cognitive assessment tool called MahjongBrain that incorporates Mahjong elements into eight digital games to improve engagement and interest among older adults during the assessment process. After presenting the software framework, assessment content, and system implementation, we conduct the usability test on 5 participants (mean age 65 years old, 20% women) in Anhui, China. The results demonstrate that the MahjongBrain is user-friendly for older adults, with the majority of participants reporting positive attitudes towards it (mean system usability scale score: 74). Furthermore, we introduce three novel digital measures which could be utilized by machine learning methods to detect subtle changes in cognitive function, including a) the scores and time to completion for each test within each cognitive domain, b) the time-stamped coordinates from the finger tracking, and c) the position of the screen as the participant is playing the games. These initial findings indicate the innovation and transformation of MahjongBrain in cognitive assessment, although further usability and validation tests are needed.
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Acknowledgment
This work was partially supported by the Wing Tat Lee Fund, the Anhui Provincial Key Technologies R&D Program (No. 2022h11020015).
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Yang, J. et al. (2023). Designing and Evaluating MahjongBrain: A Digital Cognitive Assessment Tool Through Gamification. In: Gao, Q., Zhou, J., Duffy, V.G., Antona, M., Stephanidis, C. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14055. Springer, Cham. https://doi.org/10.1007/978-3-031-48041-6_19
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