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Activity and gesture recognition from body-worn acceleration sensors is an important application in body area sensor networks. The key to any such recognition task are discriminative and variation tolerant features. Furthermore good features may reduce the energy requirements of the sensor network as well as increase the robustness of the activity recognition. We propose a feature extraction method...
This paper describes a new method for continuous activity recognition based on fusion of string-matched activity templates. The underlying segmentation and spotting approach is carried out on several symbol streams in parallel. These streams represent motion trajectories of body limbs in Cartesian space, acquired from body-worn inertial sensors. First results of our method in a highly complex real-world...
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