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Transition-Aware Human Activity Recognition Using Smartphones

Autor
Reyes, J.; Oneto, L.; Sama, A.; Parra, X.; Anguita, D.
Tipus d'activitat
Article en revista
Revista
Neurocomputing
Data de publicació
2016-01-01
Volum
171
Pàgina inicial
754
Pàgina final
754
DOI
https://doi.org/10.1016/j.neucom.2015.07.085 Obrir en finestra nova
Projecte finançador
Advanced Wide Band Gap Semiconductor Devices for Rational Use of Energy (RUE)
Repositori
http://hdl.handle.net/2117/79600 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0925231215010930 Obrir en finestra nova
Resum
This work presents the Transition-Aware Human Activity Recognition (TAHAR) system architecture for the recognition of physical activities using smartphones. It targets real-time classification with a collection of inertial sensors while addressing issues regarding the occurrence of transitions between activities and unknown activities to the learning algorithm. We propose two implementations of the architecture which differ in their prediction technique as they deal with transitions either by di...
Citació
Reyes, J., Oneto, L., Sama, A., Ghio, A., Parra, X., Anguita, D. Transition-aware human activity recognition using smartphones. "Neurocomputing", 08 Agost 2015.
Paraules clau
Activity Recognition, Machine learning, Smartphones, Support Vector Machines, Transitions
Grup de recerca
CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma

Participants

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