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Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation

Human motion capture is driven by joint center location estimates, and error in their estimation can be compounded by subsequent kinematic calculations. Soft tissue artifact (STA), the motion of tissue relative to the underlying bones, is a primary cause of error in joint center calculations. A meth...

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Autores principales: Frick, Eric, Rahmatalla, Salam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6112042/
https://www.ncbi.nlm.nih.gov/pubmed/30081601
http://dx.doi.org/10.3390/s18082563
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author Frick, Eric
Rahmatalla, Salam
author_facet Frick, Eric
Rahmatalla, Salam
author_sort Frick, Eric
collection PubMed
description Human motion capture is driven by joint center location estimates, and error in their estimation can be compounded by subsequent kinematic calculations. Soft tissue artifact (STA), the motion of tissue relative to the underlying bones, is a primary cause of error in joint center calculations. A method for mitigating the effects of STA, single-frame optimization (SFO), was introduced and numerically verified in Part 1 of this work, and the purpose of this article (Part 2) is to experimentally compare the results of SFO with a marker-based solution. The experimentation herein employed a single-degree-of-freedom pendulum to simulate human joint motion, and the effects of STA were simulated by affixing the inertial measurement unit to the pendulum indirectly through raw, vacuum-sealed meat. The inertial sensor was outfitted with an optical marker adapter so that its location could be optically determined by a camera-based motion-capture system. During the motion, inertial effects and non-rigid attachment of the inertial sensor caused the simulated STA to manifest via unrestricted motion (six degrees of freedom) relative to the rigid pendulum. The redundant inertial and optical instrumentation allowed a time-varying joint center solution to be determined both by optical markers and by SFO, allowing for comparison. The experimental results suggest that SFO can achieve accuracy comparable to that of state-of-the-art joint center determination methods that use optical skin markers (root mean square error of 7.87–37.86 mm), and that the time variances of the SFO solutions are correlated ([Formula: see text] 0.58–0.99) with the true, time-varying joint center solutions. This suggests that SFO could potentially help to fill a gap in the existing literature by improving the characterization and mitigation of STA in human motion capture.
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spelling pubmed-61120422018-08-30 Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation Frick, Eric Rahmatalla, Salam Sensors (Basel) Article Human motion capture is driven by joint center location estimates, and error in their estimation can be compounded by subsequent kinematic calculations. Soft tissue artifact (STA), the motion of tissue relative to the underlying bones, is a primary cause of error in joint center calculations. A method for mitigating the effects of STA, single-frame optimization (SFO), was introduced and numerically verified in Part 1 of this work, and the purpose of this article (Part 2) is to experimentally compare the results of SFO with a marker-based solution. The experimentation herein employed a single-degree-of-freedom pendulum to simulate human joint motion, and the effects of STA were simulated by affixing the inertial measurement unit to the pendulum indirectly through raw, vacuum-sealed meat. The inertial sensor was outfitted with an optical marker adapter so that its location could be optically determined by a camera-based motion-capture system. During the motion, inertial effects and non-rigid attachment of the inertial sensor caused the simulated STA to manifest via unrestricted motion (six degrees of freedom) relative to the rigid pendulum. The redundant inertial and optical instrumentation allowed a time-varying joint center solution to be determined both by optical markers and by SFO, allowing for comparison. The experimental results suggest that SFO can achieve accuracy comparable to that of state-of-the-art joint center determination methods that use optical skin markers (root mean square error of 7.87–37.86 mm), and that the time variances of the SFO solutions are correlated ([Formula: see text] 0.58–0.99) with the true, time-varying joint center solutions. This suggests that SFO could potentially help to fill a gap in the existing literature by improving the characterization and mitigation of STA in human motion capture. MDPI 2018-08-05 /pmc/articles/PMC6112042/ /pubmed/30081601 http://dx.doi.org/10.3390/s18082563 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Frick, Eric
Rahmatalla, Salam
Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation
title Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation
title_full Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation
title_fullStr Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation
title_full_unstemmed Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation
title_short Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation
title_sort joint center estimation using single-frame optimization: part 2: experimentation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6112042/
https://www.ncbi.nlm.nih.gov/pubmed/30081601
http://dx.doi.org/10.3390/s18082563
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