Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Chest-Mounted Inertial Measurement Unit for Pedestrian Motion Classification Using Continuous Hidden Markov Model
KTH, School of Electrical Engineering (EES), Signal Processing.
KTH, School of Electrical Engineering (EES), Sound and Image Processing (Closed 130101).
KTH, School of Electrical Engineering (EES), Sound and Image Processing (Closed 130101).
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0002-2718-0262
2012 (English)In: 2012 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), IEEE , 2012, 991-995 p.Conference paper, Oral presentation only (Refereed)
Abstract [en]

This paper presents a method for pedestrian motionclassification based on MEMS inertial measurement unit (IMU)mounted on the chest. The choice of mounting the IMU on thechest provides the potential application of the current study incamera-aided inertial navigation for positioning and personalassistance. In the present work, five categories of the pedestrianmotion including standing, walking, running, going upstairs,and going down the stairs are considered in the classificationprocedure. As the classification method, the continuous hiddenMarkov model (HMM) is used in which the output densityfunctions are assumed to be Gaussian mixture models (GMMs).The correct recognition rates based on the experimental resultsare about 95%.

Place, publisher, year, edition, pages
IEEE , 2012. 991-995 p.
Series
IEEE Instrumentation and Measurement Technology Conference, ISSN 1091-5281
Keyword [en]
Accelerometers, Feature extraction, Gyroscopes, Hidden Markov models, Humans, Legged locomotion, Sensors
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-93961DOI: 10.1109/I2MTC.2012.6229380ISI: 000309449100187Scopus ID: 2-s2.0-84864265177OAI: oai:DiVA.org:kth-93961DiVA: diva2:524623
Conference
2012 IEEE International Instrumentation and Measurement Technology Conference I2MTC, May 13-16, 2012, Graz, Austria
Funder
ICT - The Next Generation
Note

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

QC 20120823

Available from: 2012-08-23 Created: 2012-05-03 Last updated: 2013-09-30Bibliographically approved

Open Access in DiVA

fulltext(1358 kB)1002 downloads
File information
File name FULLTEXT01.pdfFile size 1358 kBChecksum SHA-512
e18a28a39a9533ce5546bd9ed70501603345e27a34b4de19db3fe52d52c8df94126509a4d582552e9a21e3415873360ed1f290d77df00fd8fa30b136ab71a06c
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusIEEEXplore

Authority records BETA

Händel, Peter

Search in DiVA

By author/editor
Panahandeh, GhazalehMohammadiha, NasserLeijon, ArneHändel, Peter
By organisation
Signal ProcessingSound and Image Processing (Closed 130101)
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 1002 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 342 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf