Body sensor networks for human activity recognition

Girija CHETTY, Matthew White

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

24 Citations (Scopus)


Body Sensor Networks aim to capture the state of the user and its environment by utilizing from information heterogeneous sensors, and allow continuous monitoring of numerous physiological signals, where these sensors are attached to the subject's body. This can be immensely useful in activity recognition for identity verification, health and ageing and sport and exercise monitoring applications. In this paper, the application of body sensor networks for automatic and intelligent daily activity monitoring for elderly people, using wireless body sensors and smartphone inertial sensors has been reported. The scheme uses information theory-based feature ranking algorithms and classifiers based on random forests, ensemble learning and lazy learning. Extensive experiments using different publicly available datasets of human activity show that the proposed approach can assist in the development of intelligent and automatic real time human activity monitoring technology for eHealth application scenarios for elderly, disabled and people with special needs.

Original languageEnglish
Title of host publicationProceedings Signal Processing and Information Networks (SPIN 2016)
EditorsM. K. Dutta, J. K. Rai P. Banerjee
Place of PublicationUnited States of America
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781467391979
ISBN (Print)9781467391979
Publication statusPublished - 2016
Event3rd International Conference on Signal Processing and Information Networks (SPIN 2016) - Delhi, Delhi, India
Duration: 11 Feb 201612 Feb 2016

Publication series

Name3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016


Conference3rd International Conference on Signal Processing and Information Networks (SPIN 2016)
Abbreviated titleSPIN 2016


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