{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T05:56:10Z","timestamp":1769579770034,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,4,8]],"date-time":"2020-04-08T00:00:00Z","timestamp":1586304000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Coaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist\u2019s motion was collected by multiple miniature inertial sensor nodes. The gradient descent method was used to fuse data and obtain the canoeist\u2019s attitude information after sensor calibration, and then the motions of canoeist\u2019s actions were reconstructed. Stroke quality was performed based on the estimated joint angles. Machine learning algorithm was used as the classification method to divide the stroke cycle into different phases, including propulsion-phase and recovery-phase, a quantitative kinematic analysis was carried out. Experiments conducted in this paper demonstrated that our method possesses the capacity to reveal the similarities and differences between novice and coach, the whole process of canoeist\u2019s motions can be analyzed with satisfactory accuracy validated by videography method. It can provide quantitative data for coaches or athletes, which can be used to improve the skills of rowers.<\/jats:p>","DOI":"10.3390\/s20072110","type":"journal-article","created":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T03:40:19Z","timestamp":1586403619000},"page":"2110","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Canoeing Motion Tracking and Analysis via Multi-Sensors Fusion"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8818-4339","authenticated-orcid":false,"given":"Long","family":"Liu","sequence":"first","affiliation":[{"name":"The Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, China"},{"name":"Department of Electrical &amp; Information Engineering, Dalian Neusoft Institute of Information, Dalian 116023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6846-546X","authenticated-orcid":false,"given":"Sen","family":"Qiu","sequence":"additional","affiliation":[{"name":"The Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZheLong","family":"Wang","sequence":"additional","affiliation":[{"name":"The Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2977-8559","authenticated-orcid":false,"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"The Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4280-6486","authenticated-orcid":false,"given":"JiaXin","family":"Wang","sequence":"additional","affiliation":[{"name":"The Laboratory of Intelligent System, Dalian University of Technology, Dalian 116024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.gaitpost.2016.10.012","article-title":"A video based method to quantify posture of the head and trunk in sitting","volume":"51","author":"Loram","year":"2017","journal-title":"Gait Posture"},{"key":"ref_2","first-page":"123","article-title":"Intra-and inter-rater reliability of a video-based method to quantify stroke synchronisation in crew-boat sprint kayaking","volume":"35","author":"Tay","year":"2017","journal-title":"ISBS Proc. Arch."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1080\/14763141.2012.724701","article-title":"An observational model for biomechanical assessment of sprint kayaking technique","volume":"11","author":"McDonnell","year":"2012","journal-title":"Sports Biomech."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1016\/j.procs.2018.03.030","article-title":"Wearable sensors and smart equipment for feedback in watersports","volume":"129","author":"Umek","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1123\/jab.2014-0114","article-title":"Paddling force profiles at different stroke rates in elite sprint kayaking","volume":"31","author":"Gomes","year":"2015","journal-title":"J. Appl. Biomech."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.humov.2012.11.006","article-title":"Differences between elite, junior and non-rowers in kinematic and kinetic parameters during ergometer rowing","volume":"32","author":"Kamnik","year":"2013","journal-title":"Hum. Mov. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.jsams.2009.06.003","article-title":"Relationship between rowing ergometer performance and physiological responses to upper and lower body exercises in rowers","volume":"13","author":"Purge","year":"2010","journal-title":"J. Sci. Med. Sport"},{"key":"ref_8","first-page":"337","article-title":"Monitoring and evaluation of rowing performance using mobile mapping data","volume":"22","author":"Mpimis","year":"2011","journal-title":"Archiwum Fotogrametrii, Kartografii i Teledetekcji"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"7069","DOI":"10.3390\/s90907069","article-title":"REMOTE, a wireless sensor network based system to monitor rowing performance","volume":"9","author":"Llosa","year":"2009","journal-title":"Sensors"},{"key":"ref_10","unstructured":"Said, K.B.S., Ababou, N., Ouadahi, N., and Ababou, A. (2016, January 15\u201317). Embedded wireless sensor network for rower motion tracking. Proceedings of the 8th International Conference on Modelling, Identification and Control (ICMIC), Algiers, Algeria."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wang, Z., Wang, J., Zhao, H., Yang, N., and Fortino, G. (2016, January 9\u201312). CanoeSense: Monitoring canoe sprint motion using wearable sensors. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary.","DOI":"10.1109\/SMC.2016.7844313"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1016\/j.jbiomech.2010.03.007","article-title":"Functionally interpretable local coordinate systems for the upper extremity using inertial & magnetic measurement systems","volume":"43","author":"Veeger","year":"2010","journal-title":"J. Biomech."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1109\/TIM.2015.2504078","article-title":"Using Distributed Wearable Sensors to Measure and Evaluate Human Lower Limb Motions","volume":"65","author":"Qiu","year":"2016","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"11797","DOI":"10.3390\/s130911797","article-title":"Automatic determination of validity of input data used in ellipsoid fitting MARG calibration algorithms","volume":"13","author":"Olivares","year":"2013","journal-title":"Sensors"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1109\/TIM.2014.2335912","article-title":"Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter","volume":"64","author":"Fourati","year":"2014","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Madgwick, S.O., Harrison, A.J., 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_17","unstructured":"Jacobs, D. (1997, January 17\u201319). Linear fitting with missing data: Applications to structure-from-motion and to characterizing intensity images. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, PR, USA."},{"key":"ref_18","first-page":"63","article-title":"Boat acceleration, temporal structure of the stroke cycle, and effectiveness in rowing","volume":"224","author":"Kleshnev","year":"2010","journal-title":"Proc. Inst. Mech. Eng. Part P J. Sport. Eng. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1177\/1747954116676110","article-title":"Influence of acoustic feedback on boat speed and crew synchronization in elite junior rowing","volume":"11","author":"Schaffert","year":"2016","journal-title":"Int. J. Sports Sci. Coach."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Liu, H., and Motoda, H. (1998). Feature Extraction, Construction and Selection: A Data Mining Perspective, Springer Science & Business Media.","DOI":"10.1007\/978-1-4615-5725-8"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1080\/026404197367434","article-title":"Instrumentation of an ergometer to monitor the reliability of rowing performance","volume":"15","author":"MacFarlane","year":"1997","journal-title":"J. Sports Sci."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ghasemzadeh, H., Loseu, V., Guenterberg, E., and Jafari, R. (2009, January 1\u20133). Sport training using body sensor networks: A statistical approach to measure wrist rotation for golf swing. Proceedings of the Fourth International Conference on Body Area Networks, Los Angeles, CA, USA.","DOI":"10.4108\/ICST.BODYNETS2009.6035"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.jevs.2015.07.022","article-title":"Kinematic analysis of the rider according to different skill levels in sitting trot and canter","volume":"39","author":"Eckardt","year":"2016","journal-title":"J. Equine Vet. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2692","DOI":"10.1109\/TIM.2018.2826198","article-title":"Inertial sensor-based analysis of equestrian sports between beginner and professional riders under different horse gaits","volume":"67","author":"Wang","year":"2018","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"343","DOI":"10.2165\/11597230-000000000-00000","article-title":"Measures of rowing performance","volume":"42","author":"Smith","year":"2012","journal-title":"Sports Med."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1080\/026404199365650","article-title":"High reliability of performance of well-trained rowers on a rowing ergometer","volume":"17","author":"Schabort","year":"1999","journal-title":"J. Sports Sci."},{"key":"ref_27","first-page":"161","article-title":"Neighborhood Component Feature Selection for High-Dimensional Data","volume":"7","author":"Yang","year":"2012","journal-title":"JCP"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Nguyen, A.H., Tran, H.T., Thang, T.C., and Ro, Y.M. (2018, January 31). Fast recognition of human actions using autocorrelation sequence. Proceedings of the 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE), Nagoya, Japan.","DOI":"10.1109\/GCCE.2018.8574820"},{"key":"ref_29","unstructured":"Bishop, C.M. (2006). Pattern Recognition and Machine Learning, Springer."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Bosch, S., Shoaib, M., Geerlings, S., Buit, L., Meratnia, N., and Havinga, P. (2015, January 28\u201330). Analysis of indoor rowing motion using wearable inertial sensors. Proceedings of the 10th EAI International Conference on Body Area Networks, Sydney, Australia.","DOI":"10.4108\/eai.28-9-2015.2261465"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e170","DOI":"10.2196\/mhealth.9781","article-title":"The SPLENDID eating detection sensor: Development and feasibility study","volume":"6","author":"Zhou","year":"2018","journal-title":"JMIR mHealth uHealth"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/7\/2110\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:16:41Z","timestamp":1760174201000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/7\/2110"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,8]]},"references-count":31,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["s20072110"],"URL":"https:\/\/doi.org\/10.3390\/s20072110","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,8]]}}}