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Human motion recognition using a wireless wearable system
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Varkey, John Paul. Human motion recognition using a wireless wearable system. Retrieved from https://doi.org/doi:10.7282/T3611014

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TitleHuman motion recognition using a wireless wearable system
NameVarkey, John Paul (author); Pompili, Dario (chair); Gajic, Zoran (internal member); Marsic, Ivan (internal member); Rutgers University; Graduate School - New Brunswick
Date Created2010
Other Date2010-10 (degree)
SubjectElectrical and Computer Engineering, Human activity recognition, Wearable computers, Gyroscopes, Support vector machines, Accelerometers
Extentviii, 43 p. : ill.
DescriptionThe future of human computer interaction systems lies in how intelligently these systems can take into account the user's context, that is, how well the data that they produce characterizes the user's current situation. Context awareness is essential for ubiquitous and wearable computing. Research on recognizing the daily activities of people has progressed steadily, but little focus has been devoted to recognizing activities along with the movements involved in it. For many applications such as rehabilitation, sports medicine, geriatric care, and health/fitness monitoring, the importance of combined recognition of activity and movements within an activity can drive health care outcomes. Motion recognition aims at recognizing the actions of one or more users from a series of observations on the users' actions and environmental conditions. Sensor-based motion recognition integrates the emerging area of wireless sensor networks with novel machine learning techniques to model a wide range of human motions. A novel algorithm is proposed that can be tuned to recognize on-the-fly either range of activities or fine motor movements within a specific activity using wirelessly connected sensor motes (equipped with accelerometers and gyroscopes) attached to different body sites. This thesis describes a novel algorithm for both situations and also presents a case study on optimal feature set from sensor values and various parameter values for the algorithm to detect the fine motor movements within an activity.
NoteM.S.
NoteIncludes bibliographical references
Noteby John Paul Varkey
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/T3611014
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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