{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T04:39:52Z","timestamp":1768711192389,"version":"3.49.0"},"reference-count":59,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,10]],"date-time":"2017-11-10T00:00:00Z","timestamp":1510272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004281","name":"Narodowe Centrum Nauki","doi-asserted-by":"publisher","award":["2015\/17\/D\/ST6\/04051"],"award-info":[{"award-number":["2015\/17\/D\/ST6\/04051"]}],"id":[{"id":"10.13039\/501100004281","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The aim of this paper is to propose and evaluate the novel method of template generation, matching, comparing and visualization applied to motion capture (kinematic) analysis. To evaluate our approach, we have used motion capture recordings (MoCap) of two highly-skilled black belt karate athletes consisting of 560 recordings of various karate techniques acquired with wearable sensors. We have evaluated the quality of generated templates; we have validated the matching algorithm that calculates similarities and differences between various MoCap data; and we have examined visualizations of important differences and similarities between MoCap data. We have concluded that our algorithms works the best when we are dealing with relatively short (2\u20134 s) actions that might be averaged and aligned with the dynamic time warping framework. In practice, the methodology is designed to optimize the performance of some full body techniques performed in various sport disciplines, for example combat sports and martial arts. We can also use this approach to generate templates or to compare the correct performance of techniques between various top sportsmen in order to generate a knowledge base of reference MoCap videos. The motion template generated by our method can be used for action recognition purposes. We have used the DTW classifier with angle-based features to classify various karate kicks. We have performed leave-one-out action recognition for the Shorin-ryu and Oyama karate master separately. In this case,     100 %     actions were correctly classified. In another experiment, we used templates generated from Oyama master recordings to classify Shorin-ryu master recordings and vice versa. In this experiment, the overall recognition rate was     94.2 %    , which is a very good result for this type of complex action.<\/jats:p>","DOI":"10.3390\/s17112590","type":"journal-article","created":{"date-parts":[[2017,11,10]],"date-time":"2017-11-10T11:12:26Z","timestamp":1510312346000},"page":"2590","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Human Actions Analysis: Templates Generation, Matching and Visualization Applied to Motion Capture of Highly-Skilled Karate Athletes"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1390-9021","authenticated-orcid":false,"given":"Tomasz","family":"Hachaj","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Pedagogical University of Krakow, 2 Podchorazych Ave, 30-084 Krakow, Poland"}]},{"given":"Marcin","family":"Piekarczyk","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Pedagogical University of Krakow, 2 Podchorazych Ave, 30-084 Krakow, Poland"}]},{"given":"Marek","family":"Ogiela","sequence":"additional","affiliation":[{"name":"AGH University of Science and Technology, Cryptography and Cognitive Informatics Research Group, 30 Mickiewicza Ave, 30-059 Krakow, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1016\/j.humov.2011.07.016","article-title":"The effect of hand dominance on martial arts strikes","volume":"31","author":"Neto","year":"2012","journal-title":"Hum. Mov. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Matsumoto, T., Konno, A., Gou, L., and Uchiyama, M. (2006, January 9\u201315). A Humanoid Robot that Breaks Wooden Boards Applying Impulsive Force. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Beijing, China.","DOI":"10.1109\/IROS.2006.282473"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1007\/BF00713501","article-title":"Changes in muscle strength and speed of an unloaded movement after various training programmes","volume":"60","author":"Voigt","year":"1990","journal-title":"Eur. J. Appl. Physiol. Occup. Physiol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.1016\/j.jelekin.2007.03.009","article-title":"Electromiographic and kinematic characteristics of Kung Fu Yau-Man palm strike","volume":"18","author":"Neto","year":"2008","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1016\/j.jelekin.2011.09.007","article-title":"Kinematic and electromyographic analyses of a karate punch","volume":"21","author":"VencesBrito","year":"2011","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jelekin.2016.06.001","article-title":"Neuromuscular performance of Bandal Chagui: Comparison of subelite and elite taekwondo athletes","volume":"30","author":"Moreira","year":"2016","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.bspc.2007.02.001","article-title":"Design of a marker-based human motion tracking system","volume":"2","author":"Kolahi","year":"2007","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/978-3-540-45243-0_67","article-title":"Estimation of Skill Levels in Sports Based on Hierarchical Spatio-Temporal Correspondences","volume":"2781","author":"Ilg","year":"2003","journal-title":"Pattern Recognit."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.jelekin.2012.09.006","article-title":"Differences in neuromuscular control between impact and no impact roundhouse kick in athletes of different skill levels","volume":"23","author":"Quinzi","year":"2013","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1007\/s00421-009-1338-5","article-title":"Neuromuscular control adaptations in elite athletes: The case of top level karateka","volume":"108","author":"Sbriccoli","year":"2010","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_11","first-page":"335","article-title":"Kinematic Analysis of the Cross Punch Applied in the Full-contact System Using Inertial Navigation Technology and Surface Electromyography","volume":"117","author":"Irina","year":"2014","journal-title":"Procedia"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1007\/s40520-015-0508-z","article-title":"Changes in dual-task performance after 5 months of karate and fitness training for older adults to enhance fall prevention","volume":"28","author":"Pliske","year":"2016","journal-title":"Aging Clin. Exp. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1670","DOI":"10.3390\/sym7041670","article-title":"Application of Assistive Computer Vision Methods to Oyama Karate Techniques Recognition","volume":"7","author":"Hachaj","year":"2015","journal-title":"Symmetry"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1854","DOI":"10.1016\/j.jbiomech.2016.04.016","article-title":"Estimating missing marker positions using low dimensional Kalman smoothing","volume":"49","author":"Burke","year":"2016","journal-title":"J. Biomech."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.measurement.2013.11.022","article-title":"The adaptive Kalman filter based on fuzzy logic for inertial motion capture system","volume":"49","author":"Jin","year":"2014","journal-title":"Measurement"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1109\/TBME.2015.2403368","article-title":"Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm","volume":"62","author":"McNames","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_17","first-page":"2310","article-title":"Online tracking of the lower body joint angles using IMUs for gait rehabilitation","volume":"2014","author":"Joukov","year":"2014","journal-title":"Conf. Proc. IEEE Eng. Med. Biol. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Masiero, A., and Cenedese, A. (2012, January 10\u201313). A Kalman filter approach for the synchronization of motion capture systems. Proceedings of the 51st IEEE Conference on Decision and Control, Maui, HI, USA.","DOI":"10.1109\/CDC.2012.6425864"},{"key":"ref_19","unstructured":"Qi, Y., Soh, C.B., Gunawan, E., and Low, K.S. (2014). A wearable wireless ultrasonic sensor network for human arm motion tracking. Conf. Proc. IEEE Eng. Med. Biol. Soc., 5960\u20135963."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.humov.2015.04.010","article-title":"Effect of different knee starting angles on intersegmental coordination and performance in vertical jumps","volume":"42","author":"Gheller","year":"2015","journal-title":"Hum. Mov. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.humov.2011.04.007","article-title":"External loading and maximum dynamic output in vertical jumping: The role of training history","volume":"31","author":"Vuk","year":"2012","journal-title":"Hum. Mov. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.gaitpost.2016.05.002","article-title":"Gait analysis of national athletes after anterior cruciate ligament reconstruction following three stages of rehabilitation program: Symmetrical perspective","volume":"48","author":"Hadizadeh","year":"2016","journal-title":"Gait Posture"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Vishnoi, N., Mitra, A., Duric, Z., and Gerber, N.L. (2014). Motion based markerless gait analysis using standard events of gait and ensemble Kalman filtering. Conf. Proc. IEEE Eng. Med. Biol. Soc., 2512\u20132516.","DOI":"10.1109\/EMBC.2014.6944133"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.chb.2016.05.009","article-title":"Do player performance, real sport experience, and gender affect movement patterns during equivalent exergame?","volume":"63","author":"Soltani","year":"2016","journal-title":"Comput. Hum. Behav."},{"key":"ref_25","unstructured":"M\u00fcller, M., and R\u00f6der, T. (2006, January 2\u20134). Motion templates for automatic classification and retrieval of motion capture data. Proceedings of the ACM SIGGRAPH\/Eurographics Symposium on Computer Animation, Vienna, Austria."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1174","DOI":"10.1109\/TSP.2011.2177832","article-title":"Quaternion dynamic time warping","volume":"60","year":"2012","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Sempena, S., Maulidevi, N.U., and Aryan, P.R. (2011, January 17\u201319). Human action recognition using dynamic time warping. Proceedings of the International Conference on Electrical Engineering and Informatics (ICEEI), Bandung, Indonesia.","DOI":"10.1109\/ICEEI.2011.6021605"},{"key":"ref_28","first-page":"1289","article-title":"Dynamic Time warping in gait classification of motion capture data","volume":"6","author":"Wojciechowski","year":"2012","journal-title":"Proc. World Acad. Sci. Eng. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"660003","DOI":"10.1063\/1.4912879","article-title":"Selection of pose configuration parameters of motion capture data based on dynamic time warping","volume":"1648","author":"Josinski","year":"2015","journal-title":"AIP Conf. Proc."},{"key":"ref_30","first-page":"1598","article-title":"Normalization of motion sequences based on DTW and hermite interpolation","volume":"25","author":"Liu","year":"2013","journal-title":"J. Syst. Simul."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"180013","DOI":"10.1063\/1.4951960","article-title":"Synchronization of motion sequences from different sources","volume":"1738","author":"Skurowski","year":"2016","journal-title":"AIP Conf. Proc."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"8508","DOI":"10.3390\/s91108508","article-title":"Classifying human leg motions with uniaxial piezoelectric gyroscopes","volume":"9","author":"Altun","year":"2009","journal-title":"Sensors"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"7505","DOI":"10.3390\/s130607505","article-title":"Early Improper Motion Detection in Golf Swings Using Wearable Motion Sensors: The First Approach","volume":"13","year":"2013","journal-title":"Sensors"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1109\/THMS.2014.2362520","article-title":"Improving human action recognition using fusion of depth camera and inertial sensors","volume":"45","author":"Chen","year":"2015","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Liu, H., Ju, Z., Ji, X., Chan, C.S., and Khoury, M. (2017). Human Motion Sensing and Recognition, Springer.","DOI":"10.1007\/978-3-662-53692-6"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"11929","DOI":"10.1007\/s11042-015-2609-2","article-title":"A novel approach to extract hand gesture feature in depth images","volume":"75","author":"Ju","year":"2016","journal-title":"Multimed. Tools Appl."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Hachaj, T., Ogiela, M.R., Piekarczyk, M., and Koptyra, K. (2017). Averaging Three-Dimensional Time-Varying Sequences of Rotations: Application to Preprocessing of Motion Capture Data, Springer.","DOI":"10.1007\/978-3-319-59126-1_2"},{"key":"ref_38","unstructured":"(2017, November 01). The Website Containing Motion Database. Available online: http:\/\/gdl.org.pl\/."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1007\/s00776-012-0350-5","article-title":"The kinematic analysis of female subjects after double-bundle anterior cruciate ligament reconstruction during single-leg squatting","volume":"18","author":"Yamazaki","year":"2013","journal-title":"J. Orthopaedic Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1111\/j.1756-5391.2010.01107.x","article-title":"Effects of martial arts on health status: A systematic review","volume":"3","author":"Bu","year":"2010","journal-title":"J. Evid. Based Med."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.humov.2014.10.006","article-title":"Which technology to investigate visual perception in sport: Video vs. virtual reality","volume":"39","author":"Vignais","year":"2015","journal-title":"Hum. Mov. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Marin, J., Blanco, T., and Marin, J.J. (2017). Octopus: A Design Methodology for Motion Capture Wearables. Sensors, 17.","DOI":"10.3390\/s17081875"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Vamsikrishna, K.M., Dogra, D.P., and Bhaskar, H. (2016, January 20\u201325). Classification of head movement patterns to aid patients undergoing home-based cervical spine rehabilitation, Acoustics. Proceedings of the Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China.","DOI":"10.1109\/ICASSP.2016.7471795"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Lebel, K., Boissy, P., Hamel, M., and Duval, C. (2013). Inertial Measures of Motion for Clinical Biomechanics: Comparative Assessment of Accuracy under Controlled Conditions - Effect of Velocity. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0079945"},{"key":"ref_45","unstructured":"Zhang, B., Jiang, S., Wei, D., Marschollek, M., and Zhang, W. (June, January 30). State of the Art in Gait Analysis Using Wearable Sensors for Healthcare Applications. Proceedings of the IEEE\/ACIS 11th International Conference on Computer and Information Science, Shanghai, China."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Schulze, M., Liu, T.-H., Xie, J., Zhang, W., Wolf, K.-H., Calliess, T., Windhagen, H., and Marschollek, M. (2012, January 5\u20137). Unobtrusive ambulatory estimation of knee joint angles during walking using gyroscope and accelerometer data\u2014A preliminary evaluation study. Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics, Hong Kong, China.","DOI":"10.1109\/BHI.2012.6211643"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"An, Q., Ishikawa, Y., Nakagawa, J., Kuroda, A., Oka, H., Yamakawa, H., Yamashita, A., and Asama, H. (2012, January 9\u201313). Evaluation of wearable gyroscope and accelerometer sensor (PocketIMU2) during walking and sit-to-stand motions. Proceedings of the IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, Paris, France.","DOI":"10.1109\/ROMAN.2012.6343838"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Cloete, T., and Scheffer, C. (2008, January 20\u201324). Benchmarking of a full-body inertial motion capture system for clinical gait analysis. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, BC, USA.","DOI":"10.1109\/IEMBS.2008.4650232"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Valtazanos, A., Arvind, D.K., and Ramamoorthy, S. (2013, January 8\u201311). Using wearable inertial sensors for posture and position tracking in unconstrained environments through learned translation manifolds. Proceedings of the ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Philadelphia, PA, USA.","DOI":"10.1145\/2461381.2461411"},{"key":"ref_50","unstructured":"Solberg, R.T., and Jensenius, A.R. (September, January 23). Optical or Inertial? Evaluation of two motion capture systems for studies of dancing to electronic dance music. Proceedings of the SMC Conference on Creative Commons, Hamburg, DE, USA."},{"key":"ref_51","unstructured":"Funakoshi, G. (2013). Karate-Do Kyohan: The Master Text, Kodansha International, Kodansha International. [1st ed.]."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1016\/j.patcog.2010.09.013","article-title":"A global averaging method for dynamic time warping, with applications to clustering","volume":"44","author":"Petitjean","year":"2011","journal-title":"Pattern Recognit."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.2514\/1.28949","article-title":"Averaging Quaternions","volume":"30","author":"Markley","year":"2007","journal-title":"J. Guid. Control Dyn."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3169","DOI":"10.1109\/TBME.2012.2211355","article-title":"Robust Human Activity and Sensor Location Corecognition via Sparse Signal Representation","volume":"59","author":"Xu","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_55","unstructured":"Chen, C., Kehtarnavaz, N., and Jafari, R. (2014, January 26\u201330). A medication adherence monitoring system for pill bottles based on a wearable inertial sensor. Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Hachaj, T., Koptyra, K., and Ogiela, M.R. (2016, January 18\u201320). Initial Proposition of Kinematics Model for Selected Karate Actions Analysis. Proceedings of the Ninth International Conference on Machine Vision (ICMV 2016), Nice, France.","DOI":"10.1117\/12.2268402"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Hachaj, T., Ogiela, M.R., and Koptyra, K. (2015, January 4\u20136). Human actions modeling and recognition in low-dimensional feature space. Proceedings of the BWCCA 2015, 10th International Conference on Broadband and Wireless Computing, Communication and Applications, Krakow, Poland.","DOI":"10.1109\/BWCCA.2015.15"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1080\/10255840802125526","article-title":"Dynamic accuracy of inertial measurement units during simple pendulum motion","volume":"11","author":"Brodie","year":"2008","journal-title":"Comput. Methods Biomech. Biomed. Eng."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"105","DOI":"10.18002\/rama.v10i2.1687","article-title":"Motion analysis systems as optimization training tools in combat sports and martial arts","volume":"10","author":"Polak","year":"2015","journal-title":"Rev. Artes Marciales Asiat. Vol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2590\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:48:57Z","timestamp":1760208537000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2590"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,10]]},"references-count":59,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2017,11]]}},"alternative-id":["s17112590"],"URL":"https:\/\/doi.org\/10.3390\/s17112590","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,10]]}}}