Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor
•A low-cost motion capture method using Kinect v2 and colored markers is proposed.•Kinematics accuracy was evaluated using a Vicon motion analysis system.•The proposed low-cost method was in good agreement with the Vicon system.•Limits of agreement for surrogate knee flexion angle were within − 1.8°...
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Veröffentlicht in: | Medical engineering & physics 2018-09, Vol.59, p.63-69 |
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creator | Timmi, Alessandro Coates, Gino Fortin, Karine Ackland, David Bryant, Adam L. Gordon, Ian Pivonka, Peter |
description | •A low-cost motion capture method using Kinect v2 and colored markers is proposed.•Kinematics accuracy was evaluated using a Vicon motion analysis system.•The proposed low-cost method was in good agreement with the Vicon system.•Limits of agreement for surrogate knee flexion angle were within − 1.8°, 1.7°.•A negative relationship between marker speed and accuracy was observed.
Microsoft Kinect for Windows v2 is a motion analysis system that features a markerless human pose estimation algorithm. Given its affordability and portability, Kinect v2 has potential for use in biomechanical research and within clinical settings; however, recent studies suggest high inaccuracy of the markerless algorithm compared to marker-based motion capture systems. A novel tracking method was developed using Kinect v2, employing custom-made colored markers and computer vision techniques. The aim of this study was to test the accuracy of this approach relative to a conventional Vicon motion analysis system, performing a Bland–Altman analysis of agreement. Twenty participants were recruited, and markers placed on bony prominences near hip, knee and ankle. Three-dimensional coordinates of the markers were recorded during treadmill walking and running. The limits of agreement (LOA) of marker coordinates were narrower than − 10 and 10 mm in most conditions, however a negative relationship between accuracy and treadmill speed was observed along Kinect depth direction. LOA of the surrogate knee angles were within − 1.8°, 1.7° for flexion in all conditions and − 2.9°, 1.7° for adduction during fast walking. The proposed methodology exhibited good agreement with a marker-based system over a range of gait speeds and, for this reason, may be useful as low-cost motion analysis tool for selected biomechanical applications. |
doi_str_mv | 10.1016/j.medengphy.2018.04.020 |
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Microsoft Kinect for Windows v2 is a motion analysis system that features a markerless human pose estimation algorithm. Given its affordability and portability, Kinect v2 has potential for use in biomechanical research and within clinical settings; however, recent studies suggest high inaccuracy of the markerless algorithm compared to marker-based motion capture systems. A novel tracking method was developed using Kinect v2, employing custom-made colored markers and computer vision techniques. The aim of this study was to test the accuracy of this approach relative to a conventional Vicon motion analysis system, performing a Bland–Altman analysis of agreement. Twenty participants were recruited, and markers placed on bony prominences near hip, knee and ankle. Three-dimensional coordinates of the markers were recorded during treadmill walking and running. The limits of agreement (LOA) of marker coordinates were narrower than − 10 and 10 mm in most conditions, however a negative relationship between accuracy and treadmill speed was observed along Kinect depth direction. LOA of the surrogate knee angles were within − 1.8°, 1.7° for flexion in all conditions and − 2.9°, 1.7° for adduction during fast walking. The proposed methodology exhibited good agreement with a marker-based system over a range of gait speeds and, for this reason, may be useful as low-cost motion analysis tool for selected biomechanical applications.</description><identifier>ISSN: 1350-4533</identifier><identifier>EISSN: 1873-4030</identifier><identifier>DOI: 10.1016/j.medengphy.2018.04.020</identifier><identifier>PMID: 29983277</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Accuracy ; Adult ; Bland–Altman ; Costs and Cost Analysis ; Female ; Gait analysis ; Humans ; Kinect v2 ; Male ; Monitoring, Physiologic - economics ; Monitoring, Physiologic - instrumentation ; Motion capture ; Movement ; Software ; Vicon</subject><ispartof>Medical engineering & physics, 2018-09, Vol.59, p.63-69</ispartof><rights>2018 IPEM</rights><rights>Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c437t-3f2705e158c4e3d29f2f3f0473d2d304f84ca013596a8811b62ef37d77d47e8b3</citedby><cites>FETCH-LOGICAL-c437t-3f2705e158c4e3d29f2f3f0473d2d304f84ca013596a8811b62ef37d77d47e8b3</cites><orcidid>0000-0002-0559-7569 ; 0000-0001-9831-3344</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.medengphy.2018.04.020$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29983277$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Timmi, Alessandro</creatorcontrib><creatorcontrib>Coates, Gino</creatorcontrib><creatorcontrib>Fortin, Karine</creatorcontrib><creatorcontrib>Ackland, David</creatorcontrib><creatorcontrib>Bryant, Adam L.</creatorcontrib><creatorcontrib>Gordon, Ian</creatorcontrib><creatorcontrib>Pivonka, Peter</creatorcontrib><title>Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor</title><title>Medical engineering & physics</title><addtitle>Med Eng Phys</addtitle><description>•A low-cost motion capture method using Kinect v2 and colored markers is proposed.•Kinematics accuracy was evaluated using a Vicon motion analysis system.•The proposed low-cost method was in good agreement with the Vicon system.•Limits of agreement for surrogate knee flexion angle were within − 1.8°, 1.7°.•A negative relationship between marker speed and accuracy was observed.
Microsoft Kinect for Windows v2 is a motion analysis system that features a markerless human pose estimation algorithm. Given its affordability and portability, Kinect v2 has potential for use in biomechanical research and within clinical settings; however, recent studies suggest high inaccuracy of the markerless algorithm compared to marker-based motion capture systems. A novel tracking method was developed using Kinect v2, employing custom-made colored markers and computer vision techniques. The aim of this study was to test the accuracy of this approach relative to a conventional Vicon motion analysis system, performing a Bland–Altman analysis of agreement. Twenty participants were recruited, and markers placed on bony prominences near hip, knee and ankle. Three-dimensional coordinates of the markers were recorded during treadmill walking and running. The limits of agreement (LOA) of marker coordinates were narrower than − 10 and 10 mm in most conditions, however a negative relationship between accuracy and treadmill speed was observed along Kinect depth direction. LOA of the surrogate knee angles were within − 1.8°, 1.7° for flexion in all conditions and − 2.9°, 1.7° for adduction during fast walking. The proposed methodology exhibited good agreement with a marker-based system over a range of gait speeds and, for this reason, may be useful as low-cost motion analysis tool for selected biomechanical applications.</description><subject>Accuracy</subject><subject>Adult</subject><subject>Bland–Altman</subject><subject>Costs and Cost Analysis</subject><subject>Female</subject><subject>Gait analysis</subject><subject>Humans</subject><subject>Kinect v2</subject><subject>Male</subject><subject>Monitoring, Physiologic - economics</subject><subject>Monitoring, Physiologic - instrumentation</subject><subject>Motion capture</subject><subject>Movement</subject><subject>Software</subject><subject>Vicon</subject><issn>1350-4533</issn><issn>1873-4030</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1PAyEQhonR-P0XlKOXXYePLttjY_yKGi96NISyQ0vdLhW2Nf330lR7lQsT8gwz70PIJYOSAauuZ-UcG-wmi-m65MDqEmQJHPbIMauVKCQI2M-1GEAhB0IckZOUZgAgZSUOyREfDmvBlTomHyNrl9HYNQ2OGtqFFbZ0buInRtrn90_fTahZLGIwdkrHJmFDQ0f7KdI2fBc2pJ6-eBtDCq6nT75D29MVpwm7FOIZOXCmTXj-e5-S97vbt5uH4vn1_vFm9FxYKVRfCMcVDJANaitRNHzouBMOpMp1I0C6WloDOc2wMnXN2Lji6IRqlGqkwnosTsnV9t-859cSU6_nPllsW9NhWCbNoVJM5MMyqrboZucU0elF9DnwWjPQG7d6pndu9catBqmz29x58TtkOc7Eru9PZgZGWwBz1JXHqJP12FlsfMxadBP8v0N-AK5vjpk</recordid><startdate>201809</startdate><enddate>201809</enddate><creator>Timmi, Alessandro</creator><creator>Coates, Gino</creator><creator>Fortin, Karine</creator><creator>Ackland, David</creator><creator>Bryant, Adam L.</creator><creator>Gordon, Ian</creator><creator>Pivonka, Peter</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0559-7569</orcidid><orcidid>https://orcid.org/0000-0001-9831-3344</orcidid></search><sort><creationdate>201809</creationdate><title>Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor</title><author>Timmi, Alessandro ; Coates, Gino ; Fortin, Karine ; Ackland, David ; Bryant, Adam L. ; Gordon, Ian ; Pivonka, Peter</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c437t-3f2705e158c4e3d29f2f3f0473d2d304f84ca013596a8811b62ef37d77d47e8b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Accuracy</topic><topic>Adult</topic><topic>Bland–Altman</topic><topic>Costs and Cost Analysis</topic><topic>Female</topic><topic>Gait analysis</topic><topic>Humans</topic><topic>Kinect v2</topic><topic>Male</topic><topic>Monitoring, Physiologic - economics</topic><topic>Monitoring, Physiologic - instrumentation</topic><topic>Motion capture</topic><topic>Movement</topic><topic>Software</topic><topic>Vicon</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Timmi, Alessandro</creatorcontrib><creatorcontrib>Coates, Gino</creatorcontrib><creatorcontrib>Fortin, Karine</creatorcontrib><creatorcontrib>Ackland, David</creatorcontrib><creatorcontrib>Bryant, Adam L.</creatorcontrib><creatorcontrib>Gordon, Ian</creatorcontrib><creatorcontrib>Pivonka, Peter</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Medical engineering & physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Timmi, Alessandro</au><au>Coates, Gino</au><au>Fortin, Karine</au><au>Ackland, David</au><au>Bryant, Adam L.</au><au>Gordon, Ian</au><au>Pivonka, Peter</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor</atitle><jtitle>Medical engineering & physics</jtitle><addtitle>Med Eng Phys</addtitle><date>2018-09</date><risdate>2018</risdate><volume>59</volume><spage>63</spage><epage>69</epage><pages>63-69</pages><issn>1350-4533</issn><eissn>1873-4030</eissn><abstract>•A low-cost motion capture method using Kinect v2 and colored markers is proposed.•Kinematics accuracy was evaluated using a Vicon motion analysis system.•The proposed low-cost method was in good agreement with the Vicon system.•Limits of agreement for surrogate knee flexion angle were within − 1.8°, 1.7°.•A negative relationship between marker speed and accuracy was observed.
Microsoft Kinect for Windows v2 is a motion analysis system that features a markerless human pose estimation algorithm. Given its affordability and portability, Kinect v2 has potential for use in biomechanical research and within clinical settings; however, recent studies suggest high inaccuracy of the markerless algorithm compared to marker-based motion capture systems. A novel tracking method was developed using Kinect v2, employing custom-made colored markers and computer vision techniques. The aim of this study was to test the accuracy of this approach relative to a conventional Vicon motion analysis system, performing a Bland–Altman analysis of agreement. Twenty participants were recruited, and markers placed on bony prominences near hip, knee and ankle. Three-dimensional coordinates of the markers were recorded during treadmill walking and running. The limits of agreement (LOA) of marker coordinates were narrower than − 10 and 10 mm in most conditions, however a negative relationship between accuracy and treadmill speed was observed along Kinect depth direction. LOA of the surrogate knee angles were within − 1.8°, 1.7° for flexion in all conditions and − 2.9°, 1.7° for adduction during fast walking. The proposed methodology exhibited good agreement with a marker-based system over a range of gait speeds and, for this reason, may be useful as low-cost motion analysis tool for selected biomechanical applications.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>29983277</pmid><doi>10.1016/j.medengphy.2018.04.020</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-0559-7569</orcidid><orcidid>https://orcid.org/0000-0001-9831-3344</orcidid></addata></record> |
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subjects | Accuracy Adult Bland–Altman Costs and Cost Analysis Female Gait analysis Humans Kinect v2 Male Monitoring, Physiologic - economics Monitoring, Physiologic - instrumentation Motion capture Movement Software Vicon |
title | Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor |
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