{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T00:29:55Z","timestamp":1777508995577,"version":"3.51.4"},"reference-count":30,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T00:00:00Z","timestamp":1719446400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61471293"],"award-info":[{"award-number":["61471293"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A 77 GHz frequency-modulated continuous wave (FMCW) radar was utilized to extract biomechanical parameters for gait analysis in indoor scenarios. By preprocessing the collected raw radar data and eliminating environmental noise, a range\u2013velocity\u2013time (RVT) data cube encompassing the subjects\u2019 information was derived. The strongest signals from the torso in the velocity and range dimensions and the enveloped signal from the toe in the velocity dimension were individually separated for the gait parameters extraction. Then, six gait parameters, including step time, stride time, step length, stride length, torso velocity, and toe velocity, were measured. In addition, the Qualisys system was concurrently utilized to measure the gait parameters of the subjects as the ground truth. The reliability of the parameters extracted by the radar was validated through the application of the Wilcoxon test, the intraclass correlation coefficient (ICC) value, and Bland\u2013Altman plots. The average errors of the gait parameters in the time, range, and velocity dimensions were less than 0.004 s, 0.002 m, and 0.045 m\/s, respectively. This non-contact radar modality promises to be employable for gait monitoring and analysis of the elderly at home.<\/jats:p>","DOI":"10.3390\/s24134184","type":"journal-article","created":{"date-parts":[[2024,6,27]],"date-time":"2024-06-27T11:19:02Z","timestamp":1719487142000},"page":"4184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Extraction and Validation of Biomechanical Gait Parameters with Contactless FMCW Radar"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0804-0280","authenticated-orcid":false,"given":"Linyu","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information and Communications Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0554-3226","authenticated-orcid":false,"given":"Zhongfei","family":"Ni","sequence":"additional","affiliation":[{"name":"College of Physics and Electronic Engineering, Shanxi University, Taiyuan 030006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4552-5914","authenticated-orcid":false,"given":"Binke","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Information and Communications Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1093\/gerona\/60.5.627","article-title":"Effect of age on characteristics of forward and backward gait at preferred and accelerated walking speed","volume":"60","author":"Laufer","year":"2005","journal-title":"J. Gerontol. Ser. A Biol. Sci. Med. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Blumrosen, G., Uziel, M., Rubinsky, B., and Porrat, D. (2010, January 27\u201330). Non-contact UWB radar technology to assess tremor. Proceedings of the XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010, MEDICON 2010, Chalkidiki, Greece. IFMBE Proceedings.","DOI":"10.1007\/978-3-642-13039-7_123"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1109\/RBME.2018.2807182","article-title":"A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications","volume":"11","author":"Jarchi","year":"2018","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ruiz-Ruiz, L., Jimenez, A.R., Garcia-Villamil, G., and Seco, F. (2021). Detecting Fall Risk and Frailty in Elders with Inertial Motion Sensors: A Survey of Significant Gait Parameters. Sensors, 21.","DOI":"10.3390\/s21206918"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ding, C., Ding, Z., Wang, L., and Jia, Y. (2021, January 22\u201324). A Fall Detection Method Based on K-Nearest Neighbor Algorithm with MIMO Millimeter-Wave Radar. Proceedings of the 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP), Nanjing, China.","DOI":"10.1109\/ICSIP52628.2021.9688752"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1109\/JERM.2022.3198814","article-title":"Estimation of Gait Parameters From Trunk Movement Measured by Doppler Radar","volume":"6","author":"Saho","year":"2022","journal-title":"IEEE J. Electromagn. RF Microw. Med. Biol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.cmpb.2012.02.003","article-title":"Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: Validation on normal subjects by standard gait analysis","volume":"108","author":"Benedetti","year":"2012","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/S0966-6362(02)00053-X","article-title":"Concurrent related validity of the GAITRite\u00ae walkway system for quantification of the spatial and temporal parameters of gait","volume":"17","author":"Bilney","year":"2003","journal-title":"Gait Posture"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2186","DOI":"10.1109\/TMC.2020.2975158","article-title":"GaitWay: Monitoring and Recognizing Gait Speed Through the Walls","volume":"20","author":"Wu","year":"2021","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1109\/JBHI.2020.2994471","article-title":"Doppler Radar for the Extraction of Biomechanical Parameters in Gait Analysis","volume":"25","author":"Seifert","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1640","DOI":"10.1049\/iet-rsn.2020.0183","article-title":"Human identification based on natural gait micro-Doppler signatures using deep transfer learning","volume":"14","author":"Ni","year":"2020","journal-title":"IET Radar Sonar Navig."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Wang, Y., Shu, Y., and Zhou, M. (2021, January 28\u201330). A Novel Eye Blink Detection Method using Frequency Modulated Continuous Wave Radar. Proceedings of the 2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM), Guangzhou, China.","DOI":"10.1109\/iWEM53379.2021.9790529"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1049\/bme2.12116","article-title":"Heartbeat information prediction based on transformer model using millimetre-wave radar","volume":"12","author":"Hu","year":"2023","journal-title":"IET Biom."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Singh, A.D., Sandha, S.S., Garcia, L., and Srivastava, M.B. (2019, January 25). RadHAR: Human Activity Recognition from Point Clouds Generated through a Millimeter-wave Radar. Proceedings of the 3rd ACM Workshop on Millimeter-Wave Networks and Sensing Systems, Los Cabos, Mexico.","DOI":"10.1145\/3349624.3356768"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"138496","DOI":"10.1109\/ACCESS.2021.3117985","article-title":"Noncontact Extraction of Biomechanical Parameters in Gait Analysis Using a Multi-Input and Multi-Output Radar Sensor","volume":"9","author":"Wang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2434","DOI":"10.1109\/TBME.2014.2319333","article-title":"Quantitative Gait Measurement with Pulse-Doppler Radar for Passive In-Home Gait Assessment","volume":"61","author":"Wang","year":"2014","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_17","unstructured":"(2023, September 20). WR1443 Single-Chip 76-GHz to 81-GHz mm Wave Sensor Evaluation Module. [Online]. Available online: https:\/\/www.ti.com\/tool\/IWR1443BOOST."},{"key":"ref_18","unstructured":"(2023, September 20). Real-Time Data-Capture Adapter for Radar Sensing Evaluation Module. [Online]. Available online: https:\/\/www.ti.com\/tool\/DCA1000EVM."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"167959","DOI":"10.1109\/ACCESS.2021.3137387","article-title":"Signal Processing for TDM MIMO FMCW Millimeter-Wave Radar Sensors","volume":"9","author":"Li","year":"2021","journal-title":"IEEE Access"},{"key":"ref_20","first-page":"1","article-title":"Robust Person Gait Identification Based on Limited Radar Measurements Using Set-Based Discriminative Subspaces Learning","volume":"71","author":"Ni","year":"2022","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.1109\/TAES.2013.6558022","article-title":"Fast Two-Dimensional CFAR Procedure","volume":"49","author":"Kronauge","year":"2013","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_22","unstructured":"Yan, J., Li, X., and Shao, Z. (2015, January 16\u201318). Intelligent and fast two-dimensional CFAR procedure. Proceedings of the 2015 IEEE International Conference on Communication Problem-Solving (ICCP), Guilin, China."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zeng, X., B\u00e1ruson, H.S.L., and Sundvall, A. (2022). Walking Step Monitoring with a Millimeter-Wave Radar in Real-Life Environment for Disease and Fall Prevention for the Elderly. Sensors, 22.","DOI":"10.3390\/s22249901"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1109\/TMTT.2021.3134992","article-title":"Radar-Based Human Activity Recognition Using Hyperdimensional Computing","volume":"70","author":"Yao","year":"2022","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Rahman, M.M., Martelli, D., and Gurbuz, S.Z. (2022, January 20\u201323). Gait Variability Analysis with Multi-Channel FMCW Radar for Fall Risk Assessment. Proceedings of the 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM), Trondheim, Norway.","DOI":"10.1109\/SAM53842.2022.9827886"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"107097","DOI":"10.1016\/j.measurement.2019.107097","article-title":"Selective health indicator for bearings ensemble remaining useful life prediction with genetic algorithm and Weibull proportional hazards model","volume":"150","author":"Qiu","year":"2020","journal-title":"Measurement"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"15133","DOI":"10.1109\/JSEN.2022.3184188","article-title":"Hallway Gait Monitoring Using Novel Radar Signal Processing and Unsupervised Learning","volume":"22","author":"Abedi","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Abedi, H., Boger, J., Morita, P.P., Wong, A., and Shaker, G. (2023). Hallway Gait Monitoring System Using an In-Package Integrated Dielectric Lens Paired with a mm-Wave Radar. Sensors, 23.","DOI":"10.3390\/s23010071"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1214\/aoms\/1177730491","article-title":"On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other","volume":"18","author":"Mann","year":"1947","journal-title":"Ann. Math. Stat."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"307","DOI":"10.2307\/2987937","article-title":"Measurement in Medicine: The Analysis of Method Comparison Studies","volume":"32","author":"Altman","year":"1983","journal-title":"Statistician"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4184\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:06:25Z","timestamp":1760108785000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4184"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,27]]},"references-count":30,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["s24134184"],"URL":"https:\/\/doi.org\/10.3390\/s24134184","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,27]]}}}