The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 25, 2009

Filed:

Apr. 27, 2007
Applicants:

Daniela Brunner, Bronx, NY (US);

Vijay Gondhalekar, New York, NY (US);

Emer Leahy, Bedford, NY (US);

David Larose, Pittsburgh, PA (US);

William P. Ross, Saranac Lake, NY (US);

Inventors:

Daniela Brunner, Bronx, NY (US);

Vijay Gondhalekar, New York, NY (US);

Emer Leahy, Bedford, NY (US);

David LaRose, Pittsburgh, PA (US);

William P. Ross, Saranac Lake, NY (US);

Assignees:

Psychogenics, Inc., Tarrytown, NY (US);

Carnegie Mellon University, Pittsburgh, PA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 19/00 (2006.01);
U.S. Cl.
CPC ...
Abstract

A system and method used to assess animal behavior includes a module having sensors that collects a variety of physical and biological data from a test subject. Interpretation of the data is provided to assess the test subjects behavior, neurology, biochemistry and physiology. The module is useful in observing the effects of a drug on the test animal and providing information on the drug's signature. Another advantage is the module's portability that allows it to be used in standard laboratory cages. This portability allows the animal to be tested in its own habitat, that can reduce any erroneous data due to stressing the animal when removed to a test cage. Additionally, the module's design allows for parallel data collection and interpretation from several laboratory animals undergoing different experiments. Multi-dimensional modeling of the test subject based the system's interpretation of the data allows pattern recognition of the drug signature, and predictive drug analysis.


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