乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:50:25Z","timestamp":1740149425096,"version":"3.37.3"},"reference-count":58,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T00:00:00Z","timestamp":1630368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003170","name":"Stiftelsen f\u00f6r Kunskaps- och Kompetensutveckling","doi-asserted-by":"publisher","award":["20180158"],"id":[{"id":"10.13039\/501100003170","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals\u2019 motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers\/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and\/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.<\/jats:p>","DOI":"10.3390\/s21175863","type":"journal-article","created":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T02:58:15Z","timestamp":1630465095000},"page":"5863","source":"Crossref","is-referenced-by-count":12,"title":["Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4368-4751","authenticated-orcid":false,"given":"Annica","family":"Kristoffersson","sequence":"first","affiliation":[{"name":"School of Innovation, Design and Engineering, M\u00e4lardalen University, 722 20 V\u00e4ster\u00e5s, Sweden"}]},{"given":"Jiaying","family":"Du","sequence":"additional","affiliation":[{"name":"Motion Control i V\u00e4ster\u00e5s AB, 721 30 V\u00e4ster\u00e5s, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5179-7158","authenticated-orcid":false,"given":"Maria","family":"Ehn","sequence":"additional","affiliation":[{"name":"School of Innovation, Design and Engineering, M\u00e4lardalen University, 722 20 V\u00e4ster\u00e5s, Sweden"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"ref_1","unstructured":"(2021, August 06). 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