An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model

Motion capture systems or MoCap systems are used for game development and in the field of sports for the assessment and digitalization of human movement. Furthermore, MoCap systems are also used in the medical and therapeutic field for the analysis of human movement patterns. As examples gait analys...

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Main Authors:	Kitzig Andreas, Demmer Julia, Bolten Tobias, Naroska Edwin, Stockmanns Gudrun, Viga Reinhard, Grabmaier Anton
Format:	Article
Language:	English
Published:	De Gruyter 2018-09-01
Series:	Current Directions in Biomedical Engineering
Subjects:	biosignal processing model driven development biomechanical modelling motion pattern database averaging motion pattern data
Online Access:	https://doi.org/10.1515/cdbme-2018-0093

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spelling	doaj-a640622dd622453d98195ce349089be92021-09-06T19:19:26ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042018-09-014138939310.1515/cdbme-2018-0093cdbme-2018-0093An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical modelKitzig Andreas0Demmer Julia1Bolten Tobias2Naroska Edwin3Stockmanns Gudrun4Viga Reinhard5Grabmaier Anton6Niederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science, Ambient Intelligence Laboratory,Krefeld, GermanyNiederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science, Ambient Intelligence Laboratory,Krefeld, GermanyNiederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science, Ambient Intelligence Laboratory,Krefeld, GermanyNiederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science, Ambient Intelligence Laboratory,Krefeld, GermanyNiederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science, Ambient Intelligence Laboratory,Krefeld, GermanyUniversity of Duisburg- Essen, Department of Electronic Components and Circuits,,Duisburg, GermanyUniversity of Duisburg- Essen, Department of Electronic Components and Circuits,,Duisburg, GermanyMotion capture systems or MoCap systems are used for game development and in the field of sports for the assessment and digitalization of human movement. Furthermore, MoCap systems are also used in the medical and therapeutic field for the analysis of human movement patterns. As examples gait analysis or examination of the musculoskeletal system and its function should be mentioned. Most application relate to a specific person and their movement or to the comparison of movements of different people. Within the scope of this paper an averaged motion sequence is supposed to be generated from MoCap data in order to be able to use it in the field of biomechanical modeling and simulation. For the averaging of individual movement sequences of different persons a Hidden Markov Model (HMM) based approach is presented.https://doi.org/10.1515/cdbme-2018-0093biosignal processingmodel driven developmentbiomechanical modellingmotion pattern databaseaveraging motion pattern data
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Kitzig Andreas Demmer Julia Bolten Tobias Naroska Edwin Stockmanns Gudrun Viga Reinhard Grabmaier Anton
spellingShingle	Kitzig Andreas Demmer Julia Bolten Tobias Naroska Edwin Stockmanns Gudrun Viga Reinhard Grabmaier Anton An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model Current Directions in Biomedical Engineering biosignal processing model driven development biomechanical modelling motion pattern database averaging motion pattern data
author_facet	Kitzig Andreas Demmer Julia Bolten Tobias Naroska Edwin Stockmanns Gudrun Viga Reinhard Grabmaier Anton
author_sort	Kitzig Andreas
title	An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model
title_short	An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model
title_full	An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model
title_fullStr	An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model
title_full_unstemmed	An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model
title_sort	hmm-based averaging approach for creating mean motion data from a full-body motion capture system to support the development of a biomechanical model
publisher	De Gruyter
series	Current Directions in Biomedical Engineering
issn	2364-5504
publishDate	2018-09-01
description	Motion capture systems or MoCap systems are used for game development and in the field of sports for the assessment and digitalization of human movement. Furthermore, MoCap systems are also used in the medical and therapeutic field for the analysis of human movement patterns. As examples gait analysis or examination of the musculoskeletal system and its function should be mentioned. Most application relate to a specific person and their movement or to the comparison of movements of different people. Within the scope of this paper an averaged motion sequence is supposed to be generated from MoCap data in order to be able to use it in the field of biomechanical modeling and simulation. For the averaging of individual movement sequences of different persons a Hidden Markov Model (HMM) based approach is presented.
topic	biosignal processing model driven development biomechanical modelling motion pattern database averaging motion pattern data
url	https://doi.org/10.1515/cdbme-2018-0093
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An HMM-based averaging approach for creating mean motion data from a full-body Motion Capture system to support the development of a biomechanical model

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