Abstract
dc:description.abstractA 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.
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Electrical and Computer Engineering
- Department dc:contributor.department
- Electrical and Computer Engineering
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2006
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Jolly, Vineet Kumar
- Chairs dc:contributor.committeechair
-
- Jones, Mark T.
- Martin, Thomas L.
- Committee member dc:contributor.committeemember
-
- Plassmann, Paul E.
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Dc Identifier Other
- etd-09282006-021229
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/35219