Good-walk recognition using Android smartphone accelerometer with application on senior patients
Yu, Wenbo
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https://hdl.handle.net/2142/90611
Description
Title
Good-walk recognition using Android smartphone accelerometer with application on senior patients
Author(s)
Yu, Wenbo
Issue Date
2016-04-21
Director of Research (if dissertation) or Advisor (if thesis)
Schatz, Bruce R.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
bioinformatics
walk recognition
activity recognition
smartphone
accelerometer
senior patient
Abstract
Good walk from one's everyday activities can be used towards chronic disease diagnosis. Smartphones have become increasingly popular among people across ages. Properties including light weight, computationally powerful make smartphones ideal platforms for activity tracking and analysis. This work focuses on good walk recognition using smartphone accelerometer readings. The algorithms are validated with activity data collected from a large pool of healthy college students and senior patients. Softwares are implemented for walk recognition and pulmonary function evaluations, and are integrated to a pipeline as part of a sequence of activity data analysis.
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