Blanca Florentino-Liaño, Niamh O'Mahony, Antonio Artés-Rodríguez


This work deals with the task of human daily activity recognition using miniature inertial sensors. The proposed method is based on the development of a hierarchical dynamic model, incorporating both inter-activity and intra-activity dynamics, thereby exploiting the inherently dynamic nature of the problem to aid the classification task. The method uses raw acceleration and angular velocity signals, directly recorded by inertial sensors, bypassing commonly used feature extraction and selection techniques and, thus, keeping all information regarding the dynamics of the signals. Classification results show a competitive performance compared to state-of-the-art methods.


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Paper Citation

in Harvard Style

Florentino-Liaño B., O'Mahony N. and Artés-Rodríguez A. (2012). HIERARCHICAL DYNAMIC MODEL FOR HUMAN DAILY ACTIVITY RECOGNITION . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012) ISBN 978-989-8425-89-8, pages 61-68. DOI: 10.5220/0003781900610068

in Bibtex Style

author={Blanca Florentino-Liaño and Niamh O'Mahony and Antonio Artés-Rodríguez},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)},

in EndNote Style

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)
SN - 978-989-8425-89-8
AU - Florentino-Liaño B.
AU - O'Mahony N.
AU - Artés-Rodríguez A.
PY - 2012
SP - 61
EP - 68
DO - 10.5220/0003781900610068