Demographics in Western countries are changing radically. People live longer (though not necessarily healthier) lives; the average age of our population grows higher, while the size of the working population diminishes; and family structures change due to young professionals moving away from their home towns. All these shifts have major consequences for the cost and the organisation of elderly care. Elderly people prefer to live in their own home for as long as possible, but they need a lot of care and help to do so.
The SALIG++ project partners developed a modular, heterogeneous system, consisting of non-instrusive hardware such as a smart TV, wrist-worn smartphone, 3D cameras and embedded sensors, combined with posture recognition software, text-to-speech applications and learning algorithms to detect Activities of Daily Life. The SALIG++ systems supports bidirectional awareness and interaction: the 3D cameras and TV can be used to be virtually ‘present’ in the home of the elderly. This allows family members and caretakers to have close, personal interaction with their parent/client, even at a distance.
Almende was most actively involved in the “Awareness and Well-Being Support Applications” work package. This WP involves using various sensors and cameras to track elderly people indoors and to recognize activities (cooking, cleaning, sleeping) and events (fall detection). 3D-modeling was used to visualize these detected activities to caretakers.
The project generated valuable insights on the detection of Activities of Daily Life, which have been re-used in other projects in healthcare. It also presented the new challenge of extracting valuable patterns from sources which are as unobtrusive as possible, to ease the burden of installation and the threshold for user adoption.