Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems
- Cite this paper as:
- Pansiot J., Stoyanov D., McIlwraith D., Lo B.P., Yang G.Z. (2007) Ambient and Wearable Sensor Fusion for Activity Recognition in Healthcare Monitoring Systems. In: Leonhardt S., Falck T., Mähönen P. (eds) 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007). IFMBE Proceedings, vol 13. Springer, Berlin, Heidelberg
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.
Keywordsblob sensor wearable sensor sensor fusion activity recognition
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