Y Osuka, N Takeshima, N Kojima, T Kohama, E Fujita, M Kusunoki, Y Kato, W F Brechue, H Sasai
{"title":"通过基于 KinectTM 的步进参数识别虚弱表型。","authors":"Y Osuka, N Takeshima, N Kojima, T Kohama, E Fujita, M Kusunoki, Y Kato, W F Brechue, H Sasai","doi":"10.14283/jarlife.2023.17","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Frailty increases the risk of falling, hospitalization, and premature death, necessitating practical early-detection tools.</p><p><strong>Objectives: </strong>To examine the discriminative ability of Kinect<sup>TM</sup>-based stepping parameters for identifying frailty phenotype.</p><p><strong>Design: </strong>Population-based cross-sectional study.</p><p><strong>Setting: </strong>Eighteen neighborhoods near Tokyo Metropolitan Institute for Geriatrics and Gerontology, Itabashi, Tokyo, Japan.</p><p><strong>Participants: </strong>In total, 563 community-dwelling older adults aged ≥75 years without mobility limitations, neurological disease, or dementia were included.</p><p><strong>Measurements: </strong>Step number (SN) and knee total movement distance (KMD) during a 20-s stepping test were evaluated using the Kinect<sup>TM</sup> infrared depth sensor.</p><p><strong>Results: </strong>The number (%) of participants with frailty were 51 (9.1). The area under the receiver operating characteristic curves (95% confidence interval) of a parameter consisting of SN and KMD for frailty was 0.72 (0.64, 0.79).</p><p><strong>Conclusions: </strong>Stepping parameters evaluated using Kinect<sup>TM</sup> provided acceptable ability in identifying frailty phenotype, making it a practical screening tool in primary care and home settings.</p>","PeriodicalId":73537,"journal":{"name":"JAR life","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10767484/pdf/","citationCount":"0","resultStr":"{\"title\":\"Discrimination of Frailty Phenotype by Kinect<sup>TM</sup>-Based Stepping Parameters.\",\"authors\":\"Y Osuka, N Takeshima, N Kojima, T Kohama, E Fujita, M Kusunoki, Y Kato, W F Brechue, H Sasai\",\"doi\":\"10.14283/jarlife.2023.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Frailty increases the risk of falling, hospitalization, and premature death, necessitating practical early-detection tools.</p><p><strong>Objectives: </strong>To examine the discriminative ability of Kinect<sup>TM</sup>-based stepping parameters for identifying frailty phenotype.</p><p><strong>Design: </strong>Population-based cross-sectional study.</p><p><strong>Setting: </strong>Eighteen neighborhoods near Tokyo Metropolitan Institute for Geriatrics and Gerontology, Itabashi, Tokyo, Japan.</p><p><strong>Participants: </strong>In total, 563 community-dwelling older adults aged ≥75 years without mobility limitations, neurological disease, or dementia were included.</p><p><strong>Measurements: </strong>Step number (SN) and knee total movement distance (KMD) during a 20-s stepping test were evaluated using the Kinect<sup>TM</sup> infrared depth sensor.</p><p><strong>Results: </strong>The number (%) of participants with frailty were 51 (9.1). The area under the receiver operating characteristic curves (95% confidence interval) of a parameter consisting of SN and KMD for frailty was 0.72 (0.64, 0.79).</p><p><strong>Conclusions: </strong>Stepping parameters evaluated using Kinect<sup>TM</sup> provided acceptable ability in identifying frailty phenotype, making it a practical screening tool in primary care and home settings.</p>\",\"PeriodicalId\":73537,\"journal\":{\"name\":\"JAR life\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10767484/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JAR life\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14283/jarlife.2023.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JAR life","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14283/jarlife.2023.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Discrimination of Frailty Phenotype by KinectTM-Based Stepping Parameters.
Background: Frailty increases the risk of falling, hospitalization, and premature death, necessitating practical early-detection tools.
Objectives: To examine the discriminative ability of KinectTM-based stepping parameters for identifying frailty phenotype.
Design: Population-based cross-sectional study.
Setting: Eighteen neighborhoods near Tokyo Metropolitan Institute for Geriatrics and Gerontology, Itabashi, Tokyo, Japan.
Participants: In total, 563 community-dwelling older adults aged ≥75 years without mobility limitations, neurological disease, or dementia were included.
Measurements: Step number (SN) and knee total movement distance (KMD) during a 20-s stepping test were evaluated using the KinectTM infrared depth sensor.
Results: The number (%) of participants with frailty were 51 (9.1). The area under the receiver operating characteristic curves (95% confidence interval) of a parameter consisting of SN and KMD for frailty was 0.72 (0.64, 0.79).
Conclusions: Stepping parameters evaluated using KinectTM provided acceptable ability in identifying frailty phenotype, making it a practical screening tool in primary care and home settings.
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