Activity and location recognition using wearable sensors

Abstract
Using measured acceleration and angular velocity data gathered through inexpensive, wearable sensors, this dead-reckoning method can determine a user's location, detect transitions between preselected locations, and recognize and classify sitting, standing, and walking behaviors. Experiments demonstrate the proposed method's effectiveness.

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