Type of Document	Master's Thesis
Author	Jolly, Vineet Kumar
Author's Email Address	vkjolly@vt.edu
URN	etd-09282006-021229
Title	Activity Recognition using Singular Value Decomposition
Degree	Master of Science
Department	Electrical and Computer Engineering
Advisory Committee	Advisor Name Title Dr. Mark Jones Committee Co-Chair Dr. Tom Martin Committee Co-Chair Dr. Paul Plassmann Committee Member
Keywords	svd activity recognition e-textiles
Date of Defense	2006-08-08
Availability	unrestricted
Abstract A wearable device that accurately records a user’s daily activities is of substantial value. It can be used to enhance medical monitoring by maintaining a diary that lists what a person was doing and for how long. The design of a wearable system to record context such as activity recognition is influenced by a combination of variables. A flexible yet systematic approach for building a software classification environment according to a set of variables is described. The integral part of the software design is the use of a unique robust classifier that uses principal component analysis (PCA) through singular value decomposition (SVD) to perform real-time activity recognition. The thesis describes the different facets of the SVD- based approach and how the classifier inputs can be modified to better differentiate between activities. This thesis presents the design and implementation of a classification environment used to perform activity detection for a wearable e-textile system.
Files	Filename       Size       Approximate Download Time (Hours:Minutes:Seconds)     28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access    IRB_s05-690_Approval.pdf 50.74 Kb 00:00:14 00:00:07 00:00:06 00:00:03 < 00:00:01   JollyThesis.pdf 958.44 Kb 00:04:26 00:02:16 00:01:59 00:00:59 00:00:05

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