NDLI: Daily movement recognition for Dead Reckoning applications

Content Provider	IEEE Xplore Digital Library
Author	Martinelli, A. Morosi, S. Del Re, E.
Copyright Year	2015
Description	Author affiliation: Dept. of Inf. Eng., Univ. of Florence, Florence, Italy (Martinelli, A.; Morosi, S.; Del Re, E.)
Abstract	In the last years, Activity Recognition (AR) has drawn the attention of many researchers in several fields such as user mobility identification and monitoring of patients and of daily activities. In the context of Dead Reckoning (DR) navigation systems, AR has been used so far to get landmarks on the map of the buldings and permit the calibration of the considered routines. The present work aims at providing a contribution to the definition of a more effective recognition of movement in the DR applications. To this aim we describe the implementation of a Movement Segmentation procedure which permits to distinguish between posture change movements, such as lying down and standing up, and cyclic movements such as walking, walking downstairs and upstair. As it is known, these movements which are very similar and prone to critical recognition analysis, can often be misleaded; therefore, they are considered as inputs of a supervised learning technique which allows their classification. Particularly, the acceleration data are acquired from a Motion Node sensor that is worn on front right-hip and four supervised learning classification families, namely the Decision Tree (DT), the Support Vector Machine (SVM), the K-Nearest Neighbor (KNN) and the Ensamble Learner (EL), are tested. The accuracy of the considered classification models is evaluated; particularly, the confusion matrices are presented which shed light on the collection of the movements that are more likely to be mixed up.
Starting Page	1
Ending Page	8
File Size	1409530
Page Count	8
File Format	PDF
e-ISBN	9781467384025
DOI	10.1109/IPIN.2015.7346769
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-13
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Accelerometers Support vector machines Dead reckoning Supervised learning Feature extraction Acceleration
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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