{"title":"Hidden Markov Model for early prediction of the elderly’s dependency evolution in ambient assisted living","authors":"Rim Jouini, Chiraz Houaidia, Leila Azouz Saidane","doi":"10.1007/s12243-023-00964-9","DOIUrl":null,"url":null,"abstract":"<div><p>The integration of information and communication technologies (ICT) can be of great utility in monitoring and evaluating the elderly’s health condition and its behavior in performing Activities of Daily Living (ADL) in the perspective to avoid, as long as possible, the delays of recourse to health care institutions (e.g., nursing homes and hospitals). In this research, we propose a predictive model for detecting behavioral and health-related changes in a patient who is monitored continuously in an assisted living environment. We focus on keeping track of the dependency level evolution and detecting the loss of autonomy for an elderly person using a Hidden Markov Model based approach. In this predictive process, we were interested in including the correlation between cardiovascular history and hypertension as it is considered the primary risk factor for cardiovascular diseases, stroke, kidney failure and many other diseases. Our simulation was applied to an empirical dataset that concerned 3046 elderly persons monitored over 9 years. The results show that our model accurately evaluates person’s dependency, follows his autonomy evolution over time and thus predicts moments of important changes.</p></div>","PeriodicalId":50761,"journal":{"name":"Annals of Telecommunications","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Telecommunications","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s12243-023-00964-9","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 1
Abstract
The integration of information and communication technologies (ICT) can be of great utility in monitoring and evaluating the elderly’s health condition and its behavior in performing Activities of Daily Living (ADL) in the perspective to avoid, as long as possible, the delays of recourse to health care institutions (e.g., nursing homes and hospitals). In this research, we propose a predictive model for detecting behavioral and health-related changes in a patient who is monitored continuously in an assisted living environment. We focus on keeping track of the dependency level evolution and detecting the loss of autonomy for an elderly person using a Hidden Markov Model based approach. In this predictive process, we were interested in including the correlation between cardiovascular history and hypertension as it is considered the primary risk factor for cardiovascular diseases, stroke, kidney failure and many other diseases. Our simulation was applied to an empirical dataset that concerned 3046 elderly persons monitored over 9 years. The results show that our model accurately evaluates person’s dependency, follows his autonomy evolution over time and thus predicts moments of important changes.
期刊介绍:
Annals of Telecommunications is an international journal publishing original peer-reviewed papers in the field of telecommunications. It covers all the essential branches of modern telecommunications, ranging from digital communications to communication networks and the internet, to software, protocols and services, uses and economics. This large spectrum of topics accounts for the rapid convergence through telecommunications of the underlying technologies in computers, communications, content management towards the emergence of the information and knowledge society. As a consequence, the Journal provides a medium for exchanging research results and technological achievements accomplished by the European and international scientific community from academia and industry.