Research Trends and Usability Challenges in Behavioral Data-Based Cognitive Function Assessment
The prevalence of dementia, a condition associated with high social costs, is rising alongside the aging population. Early diagnosis of mild cognitive impairment (MCI), a precursor to dementia, is essential for effective intervention. Recent research has focused on diagnosing cognitive function in the elderly by analyzing behavioral data, such as gait and hand movements. Compared to traditional neuropsychological assessment methods, behavioral data-based assessments offer advantages, including reduced fatigue for patients and examiners, faster testing procedures, and more objective evaluation of results. This study reviews 15 research projects from the past five years (2018–2023) that have utilized behavioral data to assess cognitive function. It examines the specific gait and hand movement variables used, the technologies implemented, and user experiences reported in these studies. As these types of assessments require new technologies or environments, we analyzed usability issues that should be considered for accurate cognitive assessment. Based on this analysis, the paper proposes future directions for research in the field of behavioral data-based cognitive function assessment.
Authors
- Hui-Jun Kim (ORCID: https://orcid.org/0009-0003-4496-6720)
- Yoon Jae Jang
- Sung-Hee Kim (ORCID: https://orcid.org/0000-0002-9716-8349)
Institutions
- Dong-Eui University (KR)
Publication Details
- Journal
- Electronics
- Published
- 2024-09-27
- DOI
- https://doi.org/10.3390/electronics13193830
- Citations
- 1
- Primary Topic
- Mental Health Research Topics
- Type
- article
- Field-Weighted Citation Impact
- 0.51
Funders
- Iran Telecommunication Research Center
- Ministry of Science and ICT, South Korea
- Institute for Information and Communications Technology Promotion
- Division of Human Resource Development