Towards a social and context-aware multi-sensor fall detection and risk assessment platform
We propose a new extensible and adaptable cloud-based fall detection framework. An ontology-based approach is used to model the situation of patient and caregivers. The captured information from the sensors is combined with contextual information. Existing fall detection systems can easily be integrated to improve accuracy. Different combinations of fall detection systems and sensors can be used.
context-aware fall detection fall risk assessment ontology semantic