Date of Original Version

2007

Type

Conference Proceeding

Rights Management

© ACM, (2007). This is the author’s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the Proceedings of the 20th annual ACM symposium on User interface software and technology {978-1-59593-679 (2007)}http://doi.acm.org/10.1145/1294211.1294237

Abstract or Description

In this paper, we present a methodology for recognizing seated postures using data from pressure sensors installed on a chair. Information about seated postures could be used to help avoid adverse effects of sitting for long periods of time, or to predict a user’s activities as input to a humancomputer interface. Our approach to posture recognition avoids the use of expensive hardware and complex prediction algorithms while providing recognition for users, for whom the classifier is not trained, using a near-optimal sensor placement strategy. We evaluated the performance of our technology in a series of empirical evaluations including (1) cross-validation experiments (classification accuracy of 87% for ten postures), and (2) a physical deployment of our system (78% classification accuracy).

Comments

© ACM, (2007). This is the author’s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the Proceedings of the 20th annual ACM symposium on User interface software and technology {978-1-59593-679 (2007)}http://doi.acm.org/10.1145/1294211.1294237

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