A supporting system for quick dementia screening using PIR motion sensor in smart home
Ting-Ying Li, Chao-Lin Wu, Yi-Wei Chien, Li‐Chen Fu, Chi-Chun Chou, Chun-Chen Chou, I-An Chen · 2017
Because of the worldwide aging population, more and more elders suffer from dementia. Nowadays, it is inconvenient and time-consuming for doctors to diagnose whether elders who live independently have dementia because lots of diagnostic questions on a checklist must be asked first, and part of them even require a long-term observation. In order to help doctors and make this diagnostic process easier, we proposed a supporting system that can quickly screen the elders and estimate the likelihood of them having dementia based on a behavioral test in 2 to 4 hours. During the behavioral test, the elders only need to perform some activities selected from so-called Instrumental Activities of Daily Living (IADL) in a smart home environment, and a machine learning algorithm is adopted to carry out the classification based on our proposed features extracted from motion sensors deployed in the smart home environment. Our system supports the classification of two classes, Dementia and Non-Dementia, and its average precision and recall are both up to 98.3%. Besides, the value of Area Under the ROC Curve (AUC) is 0.851.