Kwon, Lee-Nam Yang, Dong-Hun Hwang, Myung-Gwon Lim, Soo-Jin Kim, Young-Kuk Kim, Jae-Gyum Cho, Kwang-Hee Chun, Hong-Woo Park, Kun-Woo 2024-01-19T13:03:26Z 2024-01-19T13:03:26Z 2022-04-03 2021-12 1661-7827 https://pubs.kist.re.kr/handle/201004/115953 With the global trend toward an aging population, the increasing number of dementia patients and elderly living alone has emerged as a serious social issue in South Korea. The assessment of activities of daily living (ADL) is essential for diagnosing dementia. However, since the assessment is based on the ADL questionnaire, it relies on subjective judgment and lacks objectivity. Seven healthy seniors and six with early-stage dementia participated in the study to obtain ADL data. The derived ADL features were generated by smart home sensors. Statistical methods and machine learning techniques were employed to develop a model for auto-classifying the normal controls and early-stage dementia patients. The proposed approach verified the developed model as an objective ADL evaluation tool for the diagnosis of dementia. A random forest algorithm was used to compare a personalized model and a non-personalized model. The comparison result verified that the accuracy (91.20%) of the personalized model was higher than that (84.54%) of the non-personalized model. This indicates that the cognitive ability-based personalization showed encouraging performance in the classification of normal control and early-stage dementia and it is expected that the findings of this study will serve as important basic data for the objective diagnosis of dementia. English MDPI Automated Classification of Normal Control and Early-Stage Dementia Based on Activities of Daily Living (ADL) Data Acquired from Smart Home Environment Article 10.3390/ijerph182413235 1 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, v.18, no.24 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 18 24 Y scie ssci scopus 000738612100001 2-s2.0-85121108038 Environmental Sciences Public, Environmental & Occupational Health Environmental Sciences & Ecology Public, Environmental & Occupational Health Article MILD COGNITIVE IMPAIRMENT INSTRUMENTAL ACTIVITIES ALZHEIMERS-DISEASE PRACTICE GUIDELINE MCI PROGRESSION activities of daily living aging population early-stage dementia instrumental ADL machine learning personalization