Human motion modeling and evaluation using wearable sensor devices

dc.contributor.advisorLu, Jiang
dc.contributor.committeeMemberSha, Kewei
dc.contributor.committeeMemberUnwala, Ishaq
dc.creatorKelagote, Nitish Nagendrappa
dc.creator.orcid0000-0002-1836-8933
dc.date.accessioned2018-03-13T22:14:02Z
dc.date.available2018-03-13T22:14:02Z
dc.date.created2017-12
dc.date.issued2017-12-05
dc.date.submittedDecember 2017
dc.date.updated2018-03-13T22:14:02Z
dc.description.abstractWearable sensors devices are getting integrated into our daily life. Giving precise and accurate data on individual's exercises and practices are one of the most important tasks in extensive computing. These sensor devices provide a range of applications for development like entertainment, medical, security and tactical scenarios. Even though current research provides a variety of techniques for recognizing gesture movement, there are still key aspects that need to be addressed for recognizing human activities. In this research, we propose a technique that has not only provide a gesture movement recognition but also calculate the accuracy percentage with which the patient or subject is going to do the gesture movement with respect to the accurate model. In this process, we first receive the raw sensor data that are subjected to the preprocessing and feature extraction techniques prior sending these data to calculate the accuracy percentage. The final data that are obtained by passing through activity detection algorithm and accuracy calculation technique is then transferred to the cloud, where physiotherapist or specialist will analyze these data and provide the required feedback to the patient or subject.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657.1/826
dc.language.isoen
dc.subject.lcshWearable computers
dc.titleHuman motion modeling and evaluation using wearable sensor devices
dc.typeThesis
dc.type.materialtext
thesis.degree.grantorUniversity of Houston - Clear Lake
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
KELAGOTE-MASTERSTHESIS-2017.pdf
Size:
1.92 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
4.45 KB
Format:
Plain Text
Description:
No Thumbnail Available
Name:
LICENSE.txt
Size:
1.86 KB
Format:
Plain Text
Description: