Please use this identifier to cite or link to this item:
Personal motion analysis using mobile cloud computing platform
|Muramatsu Nathan r.pdf||Version for non-UH users. Copying/Printing is not permitted||3.23 MB||Adobe PDF||View/Open|
|Muramatsu Nathan uh.pdf||Version for UH users||3.25 MB||Adobe PDF||View/Open|
|dc.contributor.author||Muramatsu, Nathan Kenji|
|dc.description||M.S. University of Hawaii at Manoa 2013.|
|dc.description||Includes bibliographical references.|
|dc.description.abstract||With the increase of mobile accelerometers being used to measure physical activity, there has been an increase of interest in smart phone accelerometers. In this paper the Android smart phone's accelerometer is used to see if it can determine a person's activities. Android smart phones and their built in accelerometers were used to collect running and walking data of several volunteers. The smart phones were placed on different parts of the volunteer's person. Furthermore, these smart phones were placed in either an upside down or right side up orientation. The data was then transmitted to a cloud based system in order to store the data for later analysis. This paper discusses how the data will be analyzed using the Fourier transform. The data was analyzed for frequency and power and passed through a simple detector. Based upon the results of these analyses the accelerometers from the Android's smart phone can differentiate running and walking power as well as show if there is repetitive motion.|
|dc.publisher||[Honolulu] : [University of Hawaii at Manoa], [May 2013]|
|dc.relation||Theses for the degree of Master of Science (University of Hawaii at Manoa). Electrical Engineering.|
|dc.title||Personal motion analysis using mobile cloud computing platform|
|Appears in Collections:||
M.S. - Electrical Engineering|
Please email email@example.com if you need this content in ADA-compliant format.
Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.