{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T03:33:38Z","timestamp":1777520018643,"version":"3.51.4"},"reference-count":46,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,9]],"date-time":"2021-01-09T00:00:00Z","timestamp":1610150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["BES-2016-076901"],"award-info":[{"award-number":["BES-2016-076901"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["PGC2018-095145-B-I00"],"award-info":[{"award-number":["PGC2018-095145-B-I00"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010801","name":"Xunta de Galicia","doi-asserted-by":"publisher","award":["ED431C2019\/29"],"award-info":[{"award-number":["ED431C2019\/29"]}],"id":[{"id":"10.13039\/501100010801","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Optical motion capture is currently the most popular method for acquiring motion data in biomechanical applications. However, it presents a number of problems that make the process difficult and inefficient, such as marker occlusions and unwanted reflections. In addition, the obtained trajectories must be numerically differentiated twice in time in order to get the accelerations. Since the trajectories are normally noisy, they need to be filtered first, and the selection of the optimal amount of filtering is not trivial. In this work, an extended Kalman filter (EKF) that manages marker occlusions and undesired reflections in a robust way is presented. A preliminary test with inertial measurement units (IMUs) is carried out to determine their local reference frames. Then, the gait analysis of a healthy subject is performed using optical markers and IMUs simultaneously. The filtering parameters used in the optical motion capture process are tuned in order to achieve good correlation between the obtained accelerations and those measured by the IMUs. The results show that the EKF provides a robust and efficient method for optical system-based motion analysis, and that the availability of accelerations measured by inertial sensors can be very helpful for the adjustment of the filters.<\/jats:p>","DOI":"10.3390\/s21020427","type":"journal-article","created":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T23:03:42Z","timestamp":1610319822000},"page":"427","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Using Accelerometer Data to Tune the Parameters of an Extended Kalman Filter for Optical Motion Capture: Preliminary Application to Gait Analysis"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8604-6816","authenticated-orcid":false,"given":"Javier","family":"Cuadrado","sequence":"first","affiliation":[{"name":"Laboratory of Mechanical Engineering, University of La Coru\u00f1a, 15403 Ferrol, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2415-4007","authenticated-orcid":false,"given":"Florian","family":"Michaud","sequence":"additional","affiliation":[{"name":"Laboratory of Mechanical Engineering, University of La Coru\u00f1a, 15403 Ferrol, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3537-9597","authenticated-orcid":false,"given":"Urbano","family":"Lugr\u00eds","sequence":"additional","affiliation":[{"name":"Laboratory of Mechanical Engineering, University of La Coru\u00f1a, 15403 Ferrol, Spain"}]},{"given":"Manuel","family":"P\u00e9rez Soto","sequence":"additional","affiliation":[{"name":"Laboratory of Mechanical Engineering, University of La Coru\u00f1a, 15403 Ferrol, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.gaitpost.2006.10.014","article-title":"The history of gait analysis before the advent of modern computers","volume":"26","author":"Baker","year":"2007","journal-title":"Gait Posture"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Winter, D.A. (2009). Biomechanics and Motor Control of Human Movement, John Wiley & Sons, Inc.. [4th ed.].","DOI":"10.1002\/9780470549148"},{"key":"ref_3","unstructured":"Bachmann, E.R., Yun, X., and McGhee, R.B. (2003, January 16\u201320). Sourceless tracking of human posture using small inertial\/magnetic sensors. Proceedings of the 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694), Kobe, Japan."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"11556","DOI":"10.3390\/s101211556","article-title":"The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review","volume":"10","author":"Fong","year":"2010","journal-title":"Sensors"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1109\/TBME.2004.840727","article-title":"Assessment of Walking Features From Foot Inertial Sensing","volume":"52","author":"Sabatini","year":"2005","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1016\/j.measurement.2009.02.002","article-title":"Development of a wearable sensor system for quantitative gait analysis","volume":"42","author":"Liu","year":"2009","journal-title":"Measurement"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Teufl, W., Lorenz, M., Miezal, M., Taetz, B., Fr\u00f6hlich, M., and Bleser, G. (2018). Towards inertial sensor based mobile gait analysis: Event-detection and spatio-temporal parameters. Sensors, 19.","DOI":"10.3390\/s19010038"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1515\/bmt-2019-0163","article-title":"A review of foot pose and trajectory estimation methods using inertial and auxiliary sensors for kinematic gait analysis","volume":"65","author":"Okkalidis","year":"2020","journal-title":"Biomed. Tech."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/978-3-642-38556-8_16","article-title":"Human movement analysis with inertial sensors","volume":"4","author":"Lambrecht","year":"2014","journal-title":"Biosyst. Biorobotics"},{"key":"ref_10","unstructured":"Blair, S.J. (2019). Biomechanical Considerations in Goal- Kicking Accuracy: Application of an Inertial Measurement System. [Ph.D. Thesis, College of Sport and Exercise Science Institute for Health and Sport (IHES)]."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.gaitpost.2010.12.006","article-title":"A spot check for assessing static orientation consistency of inertial and magnetic sensing units","volume":"33","author":"Picerno","year":"2011","journal-title":"Gait Posture"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.proeng.2012.04.079","article-title":"Comparison of optical and inertial tracking of full golf swings","volume":"34","author":"Seaman","year":"2012","journal-title":"Procedia Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1080\/10255840802326736","article-title":"The static accuracy and calibration of inertial measurement units for 3D orientation","volume":"11","author":"Brodie","year":"2008","journal-title":"Comput. Methods Biomech. Biomed. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/s12938-017-0347-6","article-title":"Inertial measurement systems for segments and joints kinematics assessment: Towards an understanding of the variations in sensors accuracy","volume":"16","author":"Lebel","year":"2017","journal-title":"Biomed. Eng. Online"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1007\/s11517-016-1537-2","article-title":"Validation of inertial measurement units with an optoelectronic system for whole-body motion analysis","volume":"55","author":"Mecheri","year":"2017","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Poitras, I., Dupuis, F., Bielmann, M., Campeau-Lecours, A., Mercier, C., Bouyer, L.J., and Roy, J. (2019). Validity and reliability ofwearable sensors for joint angle estimation: A systematic review. Sensors, 19.","DOI":"10.3390\/s19071555"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Rezaei, A., Cuthbert, T.J., Gholami, M., and Menon, C. (2019). Application-based production and testing of a core\u2013sheath fiber strain sensor for wearable electronics: Feasibility study of using the sensors in measuring tri-axial trunk motion angles. Sensors, 19.","DOI":"10.3390\/s19194288"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Weygers, I., Kok, M., Konings, M., Hallez, H., de Vroey, H., and Claeys, K. (2020). Inertial sensor-based lower limb joint kinematics: A methodological systematic review. Sensors, 20.","DOI":"10.3390\/s20030673"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Pacher, L., Chatellier, C., Vauzelle, R., and Fradet, L. (2020). Sensor-to-segment calibration methodologies for lower-body kinematic analysis with inertial sensors: A systematic review. Sensors, 20.","DOI":"10.3390\/s20113322"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1145\/3197517.3201302","article-title":"Robust solving of optical motion capture data by denoising","volume":"37","author":"Holden","year":"2018","journal-title":"ACM Trans. Graph."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/978-3-030-22514-8_14","article-title":"Auto-labelling of Markers in Optical Motion Capture by Permutation Learning","volume":"11542","author":"Ghorbani","year":"2019","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_22","unstructured":"Lugr\u00eds, U., Vilela, R., Sanjurjo, E., Mouzo, F., and Michaud, F. (2017, January 11\u201315). Implementation of an Extended Kalman Filter for robust real-time motion capture using IR cameras and optical markers. Proceedings of the IUTAM Symposium on Intelligent Multibody Systems\u2014Dynamics, Control, Simulation, Sozopol, Bulgaria."},{"key":"ref_23","unstructured":"Skogstad, S.A.v., Nymoen, K., H\u00f8vin, M.E., Holm, S., and Jensenius, A.R. (2013, January 27\u201330). Filtering Motion Capture Data for Real-Time Applications. Proceedings of the 13th International Conference on New Interfaces for Musical Expression, Daejeon, Korea."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2438","DOI":"10.1016\/j.jbiomech.2005.07.021","article-title":"Handling of impact forces in inverse dynamics","volume":"39","author":"Bisseling","year":"2006","journal-title":"J. Biomech."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1016\/j.sigpro.2014.06.009","article-title":"Automatic motion capture data denoising via filtered subspace clustering and low rank matrix approximation","volume":"105","author":"Liu","year":"2014","journal-title":"Signal Process."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Skurowski, P., and Pawlyta, M. (2019). On the noise complexity in an optical motion capture facility. Sensors, 19.","DOI":"10.20944\/preprints201909.0178.v1"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"260","DOI":"10.3389\/fbioe.2020.00260","article-title":"Systematic Comparison of the Influence of Different Data Preprocessing Methods on the Performance of Gait Classifications Using Machine Learning","volume":"8","author":"Burdack","year":"2020","journal-title":"Front. Bioeng. Biotechnol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"25","DOI":"10.2478\/hukin-2013-0065","article-title":"Digital filtering of three-dimensional lower extremity kinematics: An assessment","volume":"39","author":"Sinclair","year":"2013","journal-title":"J. Hum. Kinet."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/j.gaitpost.2008.03.012","article-title":"The effects of industry standard averaging and filtering techniques in kinematic gait analysis","volume":"28","author":"Molloy","year":"2008","journal-title":"Gait Posture"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/0020-7101(96)01167-1","article-title":"Optimization and smoothing techniques in movement analysis","volume":"41","author":"Cappello","year":"1996","journal-title":"Int. J. Biomed. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1016\/j.jelekin.2015.06.004","article-title":"Optimising filtering parameters for a 3D motion analysis system","volume":"25","author":"Schreven","year":"2015","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A New Approach to Linear Filtering and Prediction Problems","volume":"82","author":"Kalman","year":"1960","journal-title":"J. Basic Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.1016\/j.jbiomech.2008.09.035","article-title":"Kalman smoothing improves the estimation of joint kinematics and kinetics in marker-based human gait analysis","volume":"41","author":"Jonkers","year":"2008","journal-title":"J. Biomech."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/S0167-9457(03)00004-6","article-title":"Robust recovery of human motion from video using Kalman filters and virtual humans","volume":"22","author":"Cerveri","year":"2003","journal-title":"Hum. Mov. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Madgwick, S.O.H., Harrison, A.J.L., and Vaidyanathan, R. (July, January 29). Estimation of IMU and MARG orientation using a gradient descent algorithm. Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland.","DOI":"10.1109\/ICORR.2011.5975346"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1346","DOI":"10.1109\/TBME.2006.875664","article-title":"Quaternion-Based Extended Kalman Filter for Determining Orientation by Inertial and Magnetic Sensing","volume":"53","author":"Sabatini","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_37","unstructured":"Vaughan, C.L., Davis, B.L., and O\u2019Connor, J.C. (1999). Dynamics of Human Gait, Kiboho Publishers. [2nd ed.]."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Cordillet, S., Bideau, N., Bideau, B., and Nicolas, G. (2019). Estimation of 3D knee joint angles during cycling using inertial sensors: Accuracy of a novel sensor-to-segment calibration procedure based on pedaling motion. Sensors, 19.","DOI":"10.3390\/s19112474"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/s11044-013-9363-x","article-title":"Solution methods for the double-support indeterminacy in human gait","volume":"30","author":"Cuadrado","year":"2013","journal-title":"Multibody Syst. Dyn."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1940","DOI":"10.1109\/TBME.2007.901024","article-title":"OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement","volume":"54","author":"Delp","year":"2007","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s11044-010-9191-1","article-title":"A compact smoothing-differentiation and projection approach for the kinematic data consistency of biomechanical systems","volume":"24","author":"Alonso","year":"2010","journal-title":"Multibody Syst. Dyn."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Bar-Shalom, Y., Li, X.R., and Kirubarajan, T. (2001). Estimation with Applications to Tracking and Navigation, John Wiley & Sons, Inc.","DOI":"10.1002\/0471221279"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Lutz, J., Memmert, D., Raabe, D., Dornberger, R., and Donath, L. (2020). Wearables for integrative performance and tactic analyses: Opportunities, challenges, and future directions. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17010059"},{"key":"ref_44","unstructured":"Woodman, O.J. (2007). An Introduction to Inertial Navigation, Computer Laboratory, University of Cambridge. UCAM-CL-TR-696."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Bartlett, R. (2007). Introduction to Sports Biomechanics, Routledge.","DOI":"10.4324\/9780203462027"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1016\/j.jbiomech.2011.12.011","article-title":"Effect of low pass filtering on joint moments from inverse dynamics: Implications for injury prevention","volume":"45","author":"Kristianslund","year":"2012","journal-title":"J. Biomech."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/2\/427\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:09:05Z","timestamp":1760159345000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/2\/427"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,9]]},"references-count":46,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["s21020427"],"URL":"https:\/\/doi.org\/10.3390\/s21020427","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,9]]}}}