Good-walk recognition using Android smartphone accelerometer with application on senior patients

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2016

Author dc:creator

• Yu, Wenbo

Contributors dc:contributor

• Schatz, Bruce R.

• bioinformatics
• walk recognition
• activity recognition
• smartphone
• accelerometer
• senior patient

Statement dc:rights

• Copyright 2016 Wenbo Yu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/90611

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/90611