Frailty Onset Predictions Using Sleep Analysis
Résumé
The importance of sleep analysis lies in the preventive detection of health problems. Several types of research and scientific studies have shown that memory problems and cognitive problems are the direct results of poor quality sleep. Cognitive frailty is not the only frailty influenced by the lack or poor quality of sleep. Frailty can be defined as a lack of physiological reserves that no longer allow us to respond to needs or too stressful situations (illness, hospitalization, fall, etc.). In this article, we will present a part of our research work that aims to have a collaborative data analysis approach for the detection of entry into a state of fragility that will lead to becoming a resident in a nursing home, by using two different machine learning methods; supervised and non-supervised classification. We will use as inputs several sleep data.