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Title: Estimation of accelerometer orientation for activity recognition. Author: Friedman A, Hajj Chehade N, Chien C, Pottie G. Journal: Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():2076-9. PubMed ID: 23366329. Abstract: Tri-axial accelerometers have been widely used for human activity recognition and classification. A main challenge in accelerometer-based activity recognition is the system dependence on the orientation of the accelerometer. This paper presents an approach for overcoming this challenge by calibrating the accelerometer orientation using pre-defined activities alongside automated correction algorithms. This method includes manipulation of data via rotation matrices estimated from the pre-defined activities. The system is subsequently tested with real data where sensors were placed in the wrong orientation. A control set of correctly oriented sensors were also placed for validation purposes. We show that our approach improves the accuracy from 38% to 92% for the wrongly oriented sensors, when the control sensors achieve 95%. A GUI was also created in order to make the tool easily available to other researchers.[Abstract] [Full Text] [Related] [New Search]