Online motion recognition using an accelerometer in a mobile device

Authors:
D. Fuentes;L. Gonzalez-Abril;C. Angulo;J. A. Ortega
Affiliations:
Computer Languages and Systems Dept., University of Seville, 41012 Seville, Spain;Applied Economics I Dept., University of Seville, 41018 Seville, Spain;Technical Research Centre for Dependency Care and Autonomous Living - CETpD., Universitat Politécnica de Catalunya, 08034 Vilanova i la Geltru, Spain;Computer Languages and Systems Dept., University of Seville, 41012 Seville, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 8
Cited 2

Dual unification of bi-class support vector machine formulations

Pattern Recognition
Conditional models for contextual human motion recognition

Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Combining Smart Tags and Body Fixed Sensors for Disabled People Assistance

KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Distribution-Based Dimensionality Reduction Applied to Articulated Motion Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Person recognition using facial video information: A state of the art

Journal of Visual Languages and Computing
User Daily Activity Classification from Accelerometry Using Feature Selection and SVM

IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Human motion recognition using support vector machines

Computer Vision and Image Understanding
A hybrid motion classification approach for EMG-based human-robot interfaces using Bayesian and neural networks

IEEE Transactions on Robotics - Special issue on rehabilitation robotics

Ubiquitous inference of mobility state of human custodian in people-centric context sensing

Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Elderly activities recognition and classification for applications in assisted living

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.05

Visualization

Abstract

This paper introduces a new method to implement a motion recognition process using a mobile phone fitted with an accelerometer. The data collected from the accelerometer are interpreted by means of a statistical study and machine learning algorithms in order to obtain a classification function. Then, that function is implemented in a mobile phone and online experiments are carried out. Experimental results show that this approach can be used to effectively recognize different human activities with a high-level accuracy.