ADL Detection for the Active Ageing of Elderly People

The correct identification of Activities of Daily Living (ADL) is a fundamental task to implement an effective remote monitoring of weak users with particular regards to elderlies. In this paper a comparison of the performances of two different algorithms for the classification of ADL, developed by the authors, is presented. The first algorithm exploits a threshold mechanism while the other one is based on Principal Component Analysis (PCA). The threshold based algorithm provides reasonable performances in performing classifications between different ADL. Moreover the threshold definition mechanism implemented is flexible and adaptable to several different application contexts due to the use of Receiver Operating Characteristic (ROC) theory which allows to properly define thresholds values on the basis of constraints on the system sensibility and specificity. Advantage of the PCA approach resides in the possibility to improve the system specificity in classifying different kind of ADL and a reduction of the classification problem complexity. The developed strategy allows for ADL classification with sensibility and specificity features in line with real applications in Ambient Assisted Living (AAL) context.