Research Trends and Usability Challenges in Behavioral Data-Based Cognitive Function Assessment
Year: 2024
Type: article
Abstract: 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.
Source: Electronics
Authors: Yoon Jang, Hui-Jun Kim, Sung-Hee Kim
Institution: Dong-Eui University
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,728
Awards: G4246929629, G518669462, G6949731491
OpenAlex ID: W4402918536
