2004 | OriginalPaper | Chapter
Recognizing Workshop Activity Using Body Worn Microphones and Accelerometers
Authors : Paul Lukowicz, Jamie A Ward, Holger Junker, Mathias Stäger, Gerhard Tröster, Amin Atrash, Thad Starner
Published in: Pervasive Computing
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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The paper presents a technique to automatically track the progress of maintenance or assembly tasks using body worn sensors. The technique is based on a novel way of combining data from accelerometers with simple frequency matching sound classification. This includes the intensity analysis of signals from microphones at different body locations to correlate environmental sounds with user activity.To evaluate our method we apply it to activities in a wood shop. On a simulated assembly task our system can successfully segment and identify most shop activities in a continuous data stream with zero false positives and 84.4% accuracy.