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Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine

Anguita, Davide ; Ghio, Alessandro ; Oneto, Luca ; Parra, Xavier ; Reyes-Ortiz, Jorge L.

Ambient Assisted Living and Home Care, 2012, p.216-223 [Periódico revisado por pares]

Berlin, Heidelberg: Springer Berlin Heidelberg

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Título:
Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine
Autor: Anguita, Davide ; Ghio, Alessandro ; Oneto, Luca ; Parra, Xavier ; Reyes-Ortiz, Jorge L.
Assuntos: Activity Recognition ; Aplicacions ; Computació centrada en humans ; Enginyeria de la telecomunicació ; Hardware-Friendly ; Human activity recognition ; Human-centered computing ; Informàtica ; Intel·ligència artificial ; Processament del senyal ; Reconeixement de formes ; Reconeixement de formes (Informàtica) ; Smartphones ; SVM ; Telèfons intel·ligents ; Àrees temàtiques de la UPC
É parte de: Ambient Assisted Living and Home Care, 2012, p.216-223
Descrição: Activity-Based Computing [1] aims to capture the state of the user and its environment by exploiting heterogeneous sensors in order to provide adaptation to exogenous computing resources. When these sensors are attached to the subject’s body, they permit continuous monitoring of numerous physiological signals. This has appealing use in healthcare applications, e.g. the exploitation of Ambient Intelligence (AmI) in daily activity monitoring for elderly people. In this paper, we present a system for human physical Activity Recognition (AR) using smartphone inertial sensors. As these mobile phones are limited in terms of energy and computing power, we propose a novel hardware-friendly approach for multiclass classification. This method adapts the standard Support Vector Machine (SVM) and exploits fixed-point arithmetic for computational cost reduction. A comparison with the traditional SVM shows a significant improvement in terms of computational costs while maintaining similar accuracy, which can contribute to develop more sustainable systems for AmI.
Títulos relacionados: Lecture Notes in Computer Science
Editor: Berlin, Heidelberg: Springer Berlin Heidelberg
Idioma: Inglês

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Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine

Anguita, Davide ; Ghio, Alessandro ; Oneto, Luca ; Parra, Xavier ; Reyes-Ortiz, Jorge L.

Berlin, Heidelberg: Springer Berlin Heidelberg

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