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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems
verfasst von : Julien Pansiot, Danail Stoyanov, Douglas McIlwraith, Benny P.L. Lo, G. Z. Yang
Erschienen in: 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007)
Verlag: Springer Berlin Heidelberg
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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.