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Robust, Low-cost, Non-intrusive Sensing and Recognition of Seated Postures (2007)

By: Bilge Mutlu, Andreas Krause, Jodi Forlizzi, Carlos Guestrin, and Jessica Hodgins

Abstract: 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 seated activities for a human-computer interface. Our system design displays accurate near-real-time classification performance on data from subjects on which the posture recognition system was trained by using a set of carefully designed, subject-invariant signal features. By using a near-optimal sensor placement strategy, we keep the number of required sensors low thereby reducing cost and computational complexity. We evaluated the performance of our technology using a series of empirical methods including (1) cross-validation (classification accuracy of 87 ten postures using data from 31 sensors), and (2) a physical deployment of our system (78 data from 19 sensors).

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Bilge Mutlu, Andreas Krause, Jodi Forlizzi, Carlos Guestrin, and Jessica Hodgins (2007). "Robust, Low-cost, Non-intrusive Sensing and Recognition of Seated Postures." ACM Symposium on User Interface Software and Technology (UIST). pdf   talk        
BibTeX citation

@inproceedings{Mutlu+Krause+Forlizzi+Guestrin+Hodgins:uist07chair,
AUTHOR = {Bilge Mutlu and Andreas Krause and Jodi Forlizzi and Carlos Guestrin and Jessica Hodgins},
TITLE = {Robust, Low-cost, Non-intrusive Sensing and Recognition of Seated Postures},
BOOKTITLE = {ACM Symposium on User Interface Software and Technology (UIST)},
month = {October},
YEAR = {2007},
wwwfilebase = {uist2007-mutlu-krause-forlizzi-guestrin-hodgins},
wwwtopic = {Observation Selection},
}



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