Non-parametric modeling apparatus and method for...

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Biological or biochemical

Reexamination Certificate

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C600S300000

Reexamination Certificate

active

07818131

ABSTRACT:
The activity state classification method of the present invention employs a kernel-based modeling technique, and more specifically a set of similarity-based models, which have been created using example data, to process an input observation or set of input observations, each comprising a set of sensor readings or “features” derived there from or other data, to predict the activity state of a person from whom the sensor data was obtained. A model is created for each class of activity. The input data is processed by each model and the resulting predictions are combined to yield a final prediction of which state of activity is represented by the input data.

REFERENCES:
patent: 7539597 (2009-05-01), Wegerich et al.
patent: 2004/0152957 (2004-08-01), Stivoric et al.
patent: 2005/0246314 (2005-11-01), Eder
patent: 2006/0018516 (2006-01-01), Masoud et al.
Lester et al. “A Hybrid Discriminative/Generative Approach for Modeling Human Activities” www.seattle.intel-research.net/pubs.php JCAI 2005. pp. 1-7.

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