Activities of daily living classification using depth features
Faculty of Health, Engineering and Science
School of Computer and Security Science/Artificial Intelligence and Optimisation Research Group
The increasing elderly population presents a challenge on the resources of carers and assisted living communities. In this paper, we present an algorithm based around the Microsoft Kinect for monitoring activities of daily living. The system analyses the behaviour of occupants to provide carers with valuable observational data, and has the capacity to detect abnormal events in the home.