![](/images/graphics-bg.png)
Daily Living Movement Recognition for Pedestrian Dead Reckoning Applications
Joint Authors
Martinelli, Alessio
Del Re, Enrico
Morosi, Simone
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-19
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Telecommunications Engineering
Abstract EN
Nowadays, activity recognition is a central topic in numerous applications such as patient and sport activity monitoring, surveillance, and navigation.
By focusing on the latter, in particular Pedestrian Dead Reckoning navigation systems, activity recognition is generally exploited to get landmarks on the map of the buildings in order to permit the calibration of the navigation routines.
The present work aims to provide a contribution to the definition of a more effective movement recognition for Pedestrian Dead Reckoning applications.
The signal acquired by a belt-mounted triaxial accelerometer is considered as the input to the movement segmentation procedure which exploits Continuous Wavelet Transform to detect and segment cyclic movements such as walking.
Furthermore, the segmented movements are provided to a supervised learning classifier in order to distinguish between activities such as walking and walking downstairs and upstairs.
In particular, four supervised learning classification families are tested: decision tree, Support Vector Machine, k -nearest neighbour, and Ensemble Learner.
Finally, the accuracy of the considered classification models is evaluated and the relative confusion matrices are presented.
American Psychological Association (APA)
Martinelli, Alessio& Morosi, Simone& Del Re, Enrico. 2016. Daily Living Movement Recognition for Pedestrian Dead Reckoning Applications. Mobile Information Systems،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1111586
Modern Language Association (MLA)
Martinelli, Alessio…[et al.]. Daily Living Movement Recognition for Pedestrian Dead Reckoning Applications. Mobile Information Systems No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1111586
American Medical Association (AMA)
Martinelli, Alessio& Morosi, Simone& Del Re, Enrico. Daily Living Movement Recognition for Pedestrian Dead Reckoning Applications. Mobile Information Systems. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1111586
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1111586