Fall & ADL detection methodologies for AAL

Abstract

The monitoring of falls and Activities of Daily Living (ADL) is a fundamental task to implement a rigorous remote monitoring of weak users with particular regards to elderlies. Actually, unintentional falls cause a lot of hospitalizations and could produce serious consequences due to long-lie happenings. ADL monitoring by using poor invasive and easy to use devices would really change the way of achieving awareness on the user status thus reducing times for the implementation of emergency actions. In this paper authors present two different methodologies for falls and ADLs detection. The proposed methodologies allows for ADL classification with sensibility and specificity features in line with real applications in AAL context.