{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T04:40:29Z","timestamp":1782189629669,"version":"3.54.5"},"reference-count":56,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,7]],"date-time":"2023-01-07T00:00:00Z","timestamp":1673049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Regional Development Intensive Industrial Innovation Programme (IIIP)","award":["25R17P01847"],"award-info":[{"award-number":["25R17P01847"]}]},{"name":"European Regional Development Intensive Industrial Innovation Programme (IIIP)","award":["PF-FBS-1898"],"award-info":[{"award-number":["PF-FBS-1898"]}]},{"name":"European Regional Development Intensive Industrial Innovation Programme (IIIP)","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}]},{"name":"DANU Sports","award":["25R17P01847"],"award-info":[{"award-number":["25R17P01847"]}]},{"name":"DANU Sports","award":["PF-FBS-1898"],"award-info":[{"award-number":["PF-FBS-1898"]}]},{"name":"DANU Sports","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}]},{"name":"Northumbria University","award":["25R17P01847"],"award-info":[{"award-number":["25R17P01847"]}]},{"name":"Northumbria University","award":["PF-FBS-1898"],"award-info":[{"award-number":["PF-FBS-1898"]}]},{"name":"Northumbria University","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}]},{"DOI":"10.13039\/100001262","name":"Parkinson\u2019s Foundation","doi-asserted-by":"publisher","award":["25R17P01847"],"award-info":[{"award-number":["25R17P01847"]}],"id":[{"id":"10.13039\/100001262","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001262","name":"Parkinson\u2019s Foundation","doi-asserted-by":"publisher","award":["PF-FBS-1898"],"award-info":[{"award-number":["PF-FBS-1898"]}],"id":[{"id":"10.13039\/100001262","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001262","name":"Parkinson\u2019s Foundation","doi-asserted-by":"publisher","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}],"id":[{"id":"10.13039\/100001262","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google\u2019s pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold-standard Vicon 3D motion capture system was used as a reference. The proposed approach performs robustly, demonstrating good (ICC(2,1) &gt; 0.75) to excellent (ICC(2,1) &gt; 0.90) agreement in all running gait outcomes. Additionally, temporal outcomes exhibit low mean error (0.01\u20130.014 s) in left foot outcomes. However, there are some discrepancies in right foot outcomes, due to occlusion. This study demonstrates that the proposed low-cost and markerless system provides accurate running gait assessment outcomes. The approach may help routine running gait assessment in low-resource environments.<\/jats:p>","DOI":"10.3390\/s23020696","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T07:05:09Z","timestamp":1673247909000},"page":"696","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera"],"prefix":"10.3390","volume":"23","author":[{"given":"Fraser","family":"Young","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5087-1969","authenticated-orcid":false,"given":"Rachel","family":"Mason","sequence":"additional","affiliation":[{"name":"Department of Health and Life Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosie","family":"Morris","sequence":"additional","affiliation":[{"name":"Department of Health and Life Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Stuart","sequence":"additional","affiliation":[{"name":"Department of Health and Life Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4049-9291","authenticated-orcid":false,"given":"Alan","family":"Godfrey","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1177\/1757913910379191","article-title":"Running free: Embracing a healthy lifestyle through distance running","volume":"130","author":"Shipway","year":"2010","journal-title":"Perspect. Public Health"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.pmr.2005.02.007","article-title":"Biomechanics and analysis of running gait","volume":"16","author":"Dugan","year":"2005","journal-title":"Phys. Med. Rehabil. Clin."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Agresta, C. (2020). Running Gait Assessment. Clinical Care of the Runner, Elsevier.","DOI":"10.1016\/B978-0-323-67949-7.00007-0"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1249\/MSS.0b013e3182465115","article-title":"Foot strike and injury rates in endurance runners: A retrospective study","volume":"44","author":"Daoud","year":"2012","journal-title":"Med. Sci. Sport. Exerc."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1080\/02640414.2012.707326","article-title":"Foot strike patterns and ground contact times during high-calibre middle-distance races","volume":"30","author":"Hayes","year":"2012","journal-title":"J. Sport. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1111\/j.1748-1716.1995.tb09943.x","article-title":"Metabolic and mechanical aspects of foot landing type, forefoot and rearfoot strike, in human running","volume":"155","author":"Lafortuna","year":"1995","journal-title":"Acta Physiol. Scand."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"453","DOI":"10.26603\/ijspt20180453","article-title":"Reliability of two-dimensional video-based running gait analysis","volume":"13","author":"Reinking","year":"2018","journal-title":"Int. J. Sport. Phys. Ther."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1249\/JSR.0b013e3181a6187a","article-title":"Methods of running gait analysis","volume":"8","author":"Higginson","year":"2009","journal-title":"Curr. Sport. Med. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Benson, L.C., R\u00e4is\u00e4nen, A.M., Clermont, C.A., and Ferber, R. (2022). Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis. Sensors, 22.","DOI":"10.3390\/s22051722"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.proeng.2014.06.009","article-title":"Assessment of foot kinematics during steady state running using a foot-mounted IMU","volume":"72","author":"Bailey","year":"2014","journal-title":"Procedia Eng."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zrenner, M., Gradl, S., Jensen, U., Ullrich, M., and Eskofier, B.M. (2018). Comparison of different algorithms for calculating velocity and stride length in running using inertial measurement units. Sensors, 18.","DOI":"10.3390\/s18124194"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Albert, J.A., Owolabi, V., Gebel, A., Brahms, C.M., Granacher, U., and Arnrich, B. (2020). Evaluation of the pose tracking performance of the azure kinect and kinect v2 for gait analysis in comparison with a gold standard: A pilot study. Sensors, 20.","DOI":"10.3390\/s20185104"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ye, M., Yang, C., Stankovic, V., Stankovic, L., and Cheng, S. (2017, January 10\u201314). Gait phase classification for in-home gait assessment. Proceedings of the 2017 IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, China.","DOI":"10.1109\/ICME.2017.8019500"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2555","DOI":"10.1109\/JSEN.2017.2786587","article-title":"Optimal foot location for placing wearable IMU sensors and automatic feature extraction for gait analysis","volume":"18","author":"Anwary","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1109\/JBHI.2020.3014963","article-title":"Accurate impact loading rate estimation during running via a subject-independent convolutional neural network model and optimal IMU placement","volume":"25","author":"Tan","year":"2020","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"956889","DOI":"10.3389\/fspor.2022.956889","article-title":"Examination of a Foot Mounted IMU-based Methodology for Running Gait Assessment","volume":"4","author":"Young","year":"2022","journal-title":"Front. Sport. Act. Living"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Cao, Z., Simon, T., Wei, S.-E., and Sheikh, Y. (2017, January 21\u201326). Realtime multi-person 2d pose estimation using part affinity fields. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.143"},{"key":"ref_18","unstructured":"Preis, J., Kessel, M., Werner, M., and Linnhoff-Popien, C. (2012, January 18\u201322). Gait recognition with kinect. Proceedings of the 1st International Workshop on Kinect in Pervasive Computing, New Castle, UK."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Springer, S., and Yogev Seligmann, G. (2016). Validity of the kinect for gait assessment: A focused review. Sensors, 16.","DOI":"10.3390\/s16020194"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"D\u2019Antonio, E., Taborri, J., Palermo, E., Rossi, S., and Patane, F. (2020, January 25\u201328). A markerless system for gait analysis based on OpenPose library. Proceedings of the 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Dubrovnik, Croatia.","DOI":"10.1109\/I2MTC43012.2020.9128918"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Stenum, J., Rossi, C., and Roemmich, R.T. (2021). Two-dimensional video-based analysis of human gait using pose estimation. PLoS Comput. Biol., 17.","DOI":"10.1371\/journal.pcbi.1008935"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Viswakumar, A., Rajagopalan, V., Ray, T., and Parimi, C. (2019, January 15\u201317). Human gait analysis using OpenPose. Proceedings of the 2019 fifth international conference on image information processing (ICIIP), Shimla, India.","DOI":"10.1109\/ICIIP47207.2019.8985781"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"12777","DOI":"10.1007\/s11042-022-12026-8","article-title":"Markerless gait estimation and tracking for postural assessment","volume":"81","author":"Tay","year":"2022","journal-title":"Multimed. Tools Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1097\/01.CSMR.0000319711.63793.84","article-title":"Training to maximize economy of motion in running gait","volume":"7","author":"McCann","year":"2008","journal-title":"Curr. Sport. Med. Rep."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1249\/MSS.0b013e318255a727","article-title":"Mechanisms for improved running economy in beginner runners","volume":"44","author":"Moore","year":"2012","journal-title":"Med. Sci. Sport. Exerc."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s40279-022-01760-6","article-title":"Wearables for Running Gait Analysis: A Systematic Review","volume":"53","author":"Mason","year":"2022","journal-title":"Sport. Med."},{"key":"ref_27","unstructured":"Bazarevsky, V., Grishchenko, I., Raveendran, K., Zhu, T., Zhang, F., and Grundmann, M. (2020). Blazepose: On-device real-time body pose tracking. arXiv."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Mroz, S., Baddour, N., McGuirk, C., Juneau, P., Tu, A., Cheung, K., and Lemaire, E. (2021, January 8\u201310). Comparing the Quality of Human Pose Estimation with BlazePose or OpenPose. Proceedings of the 2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART), Paris, France.","DOI":"10.1109\/BioSMART54244.2021.9677850"},{"key":"ref_29","unstructured":"Deloitte (2022, December 08). Digital Consumer Trends: The UK Cut. Available online: https:\/\/www2.deloitte.com\/uk\/en\/pages\/technology-media-and-telecommunications\/articles\/digital-consumer-trends.html."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gupta, A., Chakraborty, C., and Gupta, B. (2019). Medical information processing using smartphone under IoT framework. Energy Conservation for IoT Devices, Springer.","DOI":"10.1007\/978-981-13-7399-2_12"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.jmbbm.2018.08.032","article-title":"Effect of the cushioning running shoes in ground contact time of phases of gait","volume":"88","year":"2018","journal-title":"J. Mech. Behav. Biomed. Mater."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"274","DOI":"10.3109\/03091902.2014.909540","article-title":"Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis","volume":"38","author":"Pfister","year":"2014","journal-title":"J. Med. Eng. Technol."},{"key":"ref_33","unstructured":"Simoes, M.A. (2011). Feasibility of Wearable Sensors to Determine Gait Parameters, University of South Florida."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wei, S.-E., Ramakrishna, V., Kanade, T., and Sheikh, Y. (2016, January 27\u201330). Convolutional pose machines. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.511"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","article-title":"OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields","volume":"43","author":"Cao","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.csm.2011.10.001","article-title":"The anatomy and biomechanics of running","volume":"31","author":"Nicola","year":"2012","journal-title":"Clin. Sport. Med."},{"key":"ref_37","first-page":"120","article-title":"OpenCV","volume":"3","author":"Bradski","year":"2000","journal-title":"Dr. Dobb\u2019s J. Softw. Tools"},{"key":"ref_38","unstructured":"Bressert, E. (2012). SciPy and NumPy: An Overview for Developers, O\u2019Reilly Media, Inc."},{"key":"ref_39","first-page":"1","article-title":"pandas: A foundational Python library for data analysis and statistics","volume":"14","author":"McKinney","year":"2011","journal-title":"Python High Perform. Sci. Comput."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.csm.2010.03.013","article-title":"Kinematics and kinetics of gait: From lab to clinic","volume":"29","author":"Dicharry","year":"2010","journal-title":"Clin. Sport. Med."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.gaitpost.2015.06.008","article-title":"Comparative assessment of different methods for the estimation of gait temporal parameters using a single inertial sensor: Application to elderly, post-stroke, Parkinson\u2019s disease and Huntington\u2019s disease subjects","volume":"42","author":"Trojaniello","year":"2015","journal-title":"Gait Posture"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1080\/02640414.2011.610347","article-title":"Foot strike patterns of recreational and sub-elite runners in a long-distance road race","volume":"29","author":"Larson","year":"2011","journal-title":"J. Sport. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A guideline of selecting and reporting intraclass correlation coefficients for reliability research","volume":"15","author":"Koo","year":"2016","journal-title":"J. Chiropr. Med."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"e19498","DOI":"10.2196\/19498","article-title":"Agreement Between Spatiotemporal Gait Parameters Measured by a Markerless Motion Capture System and Two Reference Systems\u2014A Treadmill-Based Photoelectric Cell and High-Speed Video Analyses: Comparative Study","volume":"8","author":"Hermoso","year":"2020","journal-title":"JMIR Mhealth Uhealth"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.jsams.2013.05.012","article-title":"The concurrent effects of strike pattern and ground-contact time on running economy","volume":"17","author":"Merni","year":"2014","journal-title":"J. Sci. Med. Sport"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"159","DOI":"10.32098\/mltj.02.2014.13","article-title":"Walking and running on treadmill: The standard criteria for kinematics studies","volume":"4","author":"Padulo","year":"2014","journal-title":"Muscles Ligaments Tendons J."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Young, F., Stuart, S., Morris, R., Downs, C., Coleman, M., and Godfrey, A. (2021, January 1\u20135). Validation of an inertial-based contact and swing time algorithm for running analysis from a foot mounted IoT enabled wearable. Proceedings of the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Mexico City, Mexico.","DOI":"10.1109\/EMBC46164.2021.9631046"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/MIM.2014.6825388","article-title":"Camera as the instrument: The rising trend of vision based measurement","volume":"17","author":"Shirmohammadi","year":"2014","journal-title":"IEEE Instrum. Meas. Mag."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"e141","DOI":"10.1016\/j.physio.2021.10.135","article-title":"Investigating the use of an open source wearable as a tool to assess sports related concussion (SRC)","volume":"113","author":"Powell","year":"2021","journal-title":"Physiotherapy"},{"key":"ref_50","unstructured":"S\u00e1r\u00e1ndi, I., Linder, T., Arras, K.O., and Leibe, B. (2018). How robust is 3D human pose estimation to occlusion?. arXiv."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Tsai, Y.-S., Hsu, L.-H., Hsieh, Y.-Z., and Lin, S.-S. (2020). The real-time depth estimation for an occluded person based on a single image and OpenPose method. Mathematics, 8.","DOI":"10.3390\/math8081333"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1109\/TMM.2019.2944745","article-title":"2D pose-based real-time human action recognition with occlusion-handling","volume":"22","author":"Angelini","year":"2019","journal-title":"IEEE Trans. Multimed."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Cheng, Y., Yang, B., Wang, B., and Tan, R.T. (2020, January 7\u201312). 3d human pose estimation using spatio-temporal networks with explicit occlusion training. Proceedings of the AAAI Conference on Artificial Intelligence, New York, NY, USA.","DOI":"10.1609\/aaai.v34i07.6689"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"109791","DOI":"10.1109\/ACCESS.2020.3002075","article-title":"Just find it: The Mymo approach to recommend running shoes","volume":"8","author":"Young","year":"2020","journal-title":"IEEE Access"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1249\/00005768-198201000-00006","article-title":"The effect of stride length variation on oxygen uptake during distance running","volume":"14","author":"Cavanagh","year":"1982","journal-title":"Med. Sci. Sport. Exerc."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s00421-002-0646-9","article-title":"Relationship between shock attenuation and stride length during running at different velocities","volume":"87","author":"Mercer","year":"2002","journal-title":"Eur. J. Appl. Physiol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/2\/696\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:02:43Z","timestamp":1760119363000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/2\/696"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,7]]},"references-count":56,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["s23020696"],"URL":"https:\/\/doi.org\/10.3390\/s23020696","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,7]]}}}