{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T17:28:13Z","timestamp":1767979693582,"version":"3.49.0"},"reference-count":37,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T00:00:00Z","timestamp":1643068800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009619","name":"Japan Agency for Medical Research and Development","doi-asserted-by":"publisher","award":["JP20dk0110041"],"award-info":[{"award-number":["JP20dk0110041"]}],"id":[{"id":"10.13039\/100009619","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["18K18463"],"award-info":[{"award-number":["18K18463"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009105","name":"Ministry of Internal Affairs and Communications","doi-asserted-by":"publisher","award":["SCOPE"],"award-info":[{"award-number":["SCOPE"]}],"id":[{"id":"10.13039\/501100009105","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NAKAJIMA Foundation","award":["R2"],"award-info":[{"award-number":["R2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In a previous study, we developed a classification model to detect fall risk for elderly adults with a history of falls (fallers) using micro-Doppler radar (MDR) gait measurements via simulation. The objective was to create daily monitoring systems that can identify elderly people with a high risk of falls. This study aimed to verify the effectiveness of our model by collecting actual MDR data from community-dwelling elderly people. First, MDR gait measurements were performed in a community setting, and the efficient gait parameters for the classification of fallers were extracted. Then, a support vector machine model that was trained and validated using the simulated MDR data was tested for the gait parameters extracted from the actual MDR data. A classification accuracy of 78.8% was achieved for the actual MDR data. The validity of the experimental results was confirmed based on a comparison with the results of our previous simulation study. Thus, the practicality of the faller classification model constructed using the simulated MDR data was verified for the actual MDR data.<\/jats:p>","DOI":"10.3390\/s22030930","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T21:07:11Z","timestamp":1643144831000},"page":"930","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Experimental Verification of Micro-Doppler Radar Measurements of Fall-Risk-Related Gait Differences for Community-Dwelling Elderly Adults"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2088-1231","authenticated-orcid":false,"given":"Kenshi","family":"Saho","sequence":"first","affiliation":[{"name":"Department of Intelligent Robotics, Toyama Prefectural University, Imizu 939-0398, Toyama, Japan"}]},{"given":"Masahiro","family":"Fujimoto","sequence":"additional","affiliation":[{"name":"Human Augmentation Research Center, National Institute of Advanced Industrial Science and Technology, Kashiwa 277-0882, Chiba, Japan"}]},{"given":"Yoshiyuki","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Human Augmentation Research Center, National Institute of Advanced Industrial Science and Technology, Kashiwa 277-0882, Chiba, Japan"}]},{"given":"Michito","family":"Matsumoto","sequence":"additional","affiliation":[{"name":"Toyama College of Welfare Science, Imizu 939-0341, Toyama, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.2105\/AJPH.2005.083055","article-title":"Outdoor falls among middle-aged and older adults: A neglected public health problem","volume":"96","author":"Li","year":"2006","journal-title":"Am. 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