Authors
Paul Lukowicz, Jamie A Ward, Holger Junker, Mathias Stäger, Gerhard Tröster, Amin Atrash, Thad Starner
Publication date
2004
Conference
Pervasive Computing: Second International Conference, PERVASIVE 2004, Linz/Vienna, Austria, April 21-23, 2004. Proceedings 2
Pages
18-32
Publisher
Springer Berlin Heidelberg
Description
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.
Total citations
Scholar articles
P Lukowicz, JA Ward, H Junker, M Stäger, G Tröster… - … Conference, PERVASIVE 2004, Linz/Vienna, Austria …, 2004