Pilot experiences on independent living in high age via non-invasive multisensory data analytics

This work describes the self-management support experience of the Patients with Dementia (PwD) at home by delivering a technology integrated model of assistance to the Informal Caregivers (ICs). Based on the conducted pilot tests the authors analyse, if non-invasive sensing technologies, are able to support the assistance management of the ICs, by delivering reliable information about deviations on usual behavioural patterns of PwD. The work presents the basic results of using Recurrent Neural Networks (RNN) in behaviour classification and anomaly detection at home.