The research activity on Ambient Assisted Living (AAL) is focused on the applications for solutions targeted to elderly or partially impaired people. As an example, the exploitation of RGBD streams analysis algorithms is used to track people moving in indoor environments and recognize possibly dangerous situations, such as falls.
This activity is extended to behavioral analysis, with the aim of automatically detect physical problems and impairments in the movements of elderly people. At the same time, contactless detection is one of the new frontiers of technological innovation in the field of healthcare, enabling unobtrusive measurements of biomedical parameters. At ICT Lab several studies were developed in order extract the heart rate from video signals, achieving performance comparable to classical approaches exploiting wearable systems.
A methodology for fall detection that relies on a pair of smart shoes, equipped with force sensors and a tri-axial accelerometer, able to detect a fall and notify it to a supervising system was also studied. The instrumented footwear enables the analysis of the subject’s motion and foot orientation, recognizing abnormal configurations.
