Wrist tracking for ubiquitous human-machine interface

Ubiquitous mobile tracking is a challenging problem especially due to the limitations posed by low-quality sensors available. The noise and bias present in the accelerometers, gyroscopes and magnetometers introduce exponential drift and hence double integration method is insufficient. Sophisticated...

Full description

Saved in:
Bibliographic Details
Main Author: Tio, Prajogo
Other Authors: Jun Luo
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/71874
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-71874
record_format dspace
spelling sg-ntu-dr.10356-718742023-03-03T20:58:39Z Wrist tracking for ubiquitous human-machine interface Tio, Prajogo Jun Luo School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Ubiquitous mobile tracking is a challenging problem especially due to the limitations posed by low-quality sensors available. The noise and bias present in the accelerometers, gyroscopes and magnetometers introduce exponential drift and hence double integration method is insufficient. Sophisticated algorithms have been developed to deal with the challenge, however most of them require expensive offline computations or support from specially installed infrastructure. In this report, we describe a robust system for online mobile tracking with satisfactory accuracy using only a pair of smartphone-watch, called Sound of Motion (SoM). A novel technique of inferring motion state from differential arrival time of sound signal serves as an enabling technology. Three sub-components, namely sound ranging, orientation tracker, and position tracker are discussed in detail. Subsequently, the tracking results of SoM are presented and analysed. Finally, various applications of this system as an input primitive and future improvements are explored. Bachelor of Engineering (Computer Science) 2017-05-19T06:49:32Z 2017-05-19T06:49:32Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/71874 en Nanyang Technological University 36 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Tio, Prajogo
Wrist tracking for ubiquitous human-machine interface
description Ubiquitous mobile tracking is a challenging problem especially due to the limitations posed by low-quality sensors available. The noise and bias present in the accelerometers, gyroscopes and magnetometers introduce exponential drift and hence double integration method is insufficient. Sophisticated algorithms have been developed to deal with the challenge, however most of them require expensive offline computations or support from specially installed infrastructure. In this report, we describe a robust system for online mobile tracking with satisfactory accuracy using only a pair of smartphone-watch, called Sound of Motion (SoM). A novel technique of inferring motion state from differential arrival time of sound signal serves as an enabling technology. Three sub-components, namely sound ranging, orientation tracker, and position tracker are discussed in detail. Subsequently, the tracking results of SoM are presented and analysed. Finally, various applications of this system as an input primitive and future improvements are explored.
author2 Jun Luo
author_facet Jun Luo
Tio, Prajogo
format Final Year Project
author Tio, Prajogo
author_sort Tio, Prajogo
title Wrist tracking for ubiquitous human-machine interface
title_short Wrist tracking for ubiquitous human-machine interface
title_full Wrist tracking for ubiquitous human-machine interface
title_fullStr Wrist tracking for ubiquitous human-machine interface
title_full_unstemmed Wrist tracking for ubiquitous human-machine interface
title_sort wrist tracking for ubiquitous human-machine interface
publishDate 2017
url http://hdl.handle.net/10356/71874
_version_ 1759853583232139264