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Energy efficient smartphone-based activity recognition using fixed-point arithmetic

Autor
Anguita, D.; Ghio, A.; Oneto, L.; Parra, X.; Reyes, J.
Tipus d'activitat
Article en revista
Revista
Journal of universal computer science
Data de publicació
2013
Volum
19
Número
9
Pàgina inicial
1295
Pàgina final
1314
Repositori
http://hdl.handle.net/2117/20437 Obrir en finestra nova
URL
http://www.jucs.org/jucs_19_9/energy_efficient_smartphone_based/jucs_19_09_1295_1314_anguita.pdf Obrir en finestra nova
Resum
In this paper we propose a novel energy efficient approach for the recognition of human activities using smartphones as wearable sensing devices, targeting assisted living applications such as remote patient activity monitoring for the disabled and the elderly. The method exploits fixed-point arithmetic to propose a modified multiclass Support Vector Machine (SVM) learning algorithm, allowing to better pre- serve the smartphone battery lifetime with respect to the conventional floating-point bas...
Citació
Anguita, D. [et al.]. Energy efficient smartphone-based activity recognition using fixed-point arithmetic. "Journal of universal computer science", 2013, vol. 19, núm. 9, p. 1295-1314.
Paraules clau
Activity recognition Assisted healthcare Energy efficiency Fixed-point arithmetic Remote monitoring Smartphones SVM
Grup de recerca
CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma
GREC - Grup de Recerca en Enginyeria del Coneixement

Participants

  • Anguita, Davide  (autor)
  • Ghio, Alessandro  (autor)
  • Oneto, Luca  (autor)
  • Llanas Parra, Francesc Xavier  (autor)
  • Reyes Ortiz, Jorge Luis  (autor)

Arxius