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Ambient and wearable sensor fusion for activity recognition in healthcare monitoring systems

Pansiot, J; Stoyanov, D; McIlwraith, D; Lo, BPL; Yang, GZ; (2007) Ambient and wearable sensor fusion for activity recognition in healthcare monitoring systems. In: Leonhardt, S and Falck, T and Mahonen, P, (eds.) 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007). (pp. 208 - 212). SPRINGER

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Abstract

The use of wearable sensors for home monitoring provides an effective means of inferring a patient's level of activity. However, wearable sensors have intrinsic ambiguities that prevent certain activities to be recognized accurately. The purpose of this paper is to introduce a robust framework for enhanced activity recognition by integrating an ear-worn activity recognition (e-AR) sensor with ambient blob-based vision sensors. Accelerometer information from the e-AR is fused with features extracted from the vision sensor by using a Gaussian Mixture Model Bayes classifier. The experimental results showed a significant improvement of the classification accuracy compared to the use of the e-AR sensor alone.

Type: Proceedings paper
Title: Ambient and wearable sensor fusion for activity recognition in healthcare monitoring systems
Event: 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007)
Location: RWTH Aachen Univ, Aachen, GERMANY
Dates: 2007-03-26 - 2007-03-28
ISBN-13: 978-3-540-70993-0
Keywords: blob sensor, wearable sensor, sensor fusion, activity recognition
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1321715
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