Title

Activities of daily living classification using depth features

Document Type

Conference Proceeding

Faculty

Faculty of Health, Engineering and Science

School

School of Computer and Security Science/Artificial Intelligence and Optimisation Research Group

RAS ID

16559

Comments

This article was originally published as: Da Luz, L. J., Masek, M. , & Lam, C. P. (2013). Activities of daily living classification using depth features. Proceedings of IEEE Tencon. Xi'an, China. IEEE. Original article available here

Abstract

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.

DOI

10.1109/TENCON.2013.6718892

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