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This study investigated how to detect the possibility of high fall risk subjects among older adults. The original signal is based on center of pressure (COP) measured using a force plate. The falling group includes 29 subjects who had a history of falls in the year preceding this study or had received high scores on the Short Falls Efficacy Scale (FES). The nonfalling group includes 47 enrollees with no history of falls and who had received low scores on the Short FES. The COP in both the anterior\u2013posterior and mediolateral direction were calculated and analyzed through empirical mode decomposition (EMD) up to six levels. The following five features were extracted and imported to a decision tree algorithm: root-mean-square deviation, median frequency, total frequency power, approximate entropy, and sample entropy. The results showed that there were a larger number of statistically different feature parameters, and a higher classification of accuracy was obtained. With the aid of empirical mode decomposition, the average classification accuracy increased 10% and achieved a level of 99.74% in the training group and 96.77% in the testing group, respectively.<\/jats:p>","DOI":"10.1155\/2021\/6252445","type":"journal-article","created":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T22:50:15Z","timestamp":1637880615000},"page":"1-10","source":"Crossref","is-referenced-by-count":10,"title":["Analysis of Center of Pressure Signals by Using Decision Tree and Empirical Mode Decomposition to Predict Falls among Older Adults"],"prefix":"10.1155","volume":"2021","author":[{"given":"Fang-Yin","family":"Liao","sequence":"first","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, China Medical University Hospital, 40402 Taichung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun-Chang","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Traditional Chinese Medicine, Asia University Hospital, 41354 Taichung, Taiwan"},{"name":"School of Chinese Medicine, College of Chinese Medicine, China Medical University, 40402 Taichung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Chun","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Asia University, 41354 Taichung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3540-6225","authenticated-orcid":true,"given":"Li-Wei","family":"Chou","sequence":"additional","affiliation":[{"name":"Department of Physical Medicine and Rehabilitation, China Medical University Hospital, 40402 Taichung, Taiwan"},{"name":"Department of Physical Medicine and Rehabilitation, Asia University Hospital, Asia University, 41354 Taichung, Taiwan"},{"name":"Department of Physical Therapy and Graduate Institute of Rehabilitation Science, China Medical University, 40402 Taichung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1102-8650","authenticated-orcid":true,"given":"Kang-Ming","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Asia University, 41354 Taichung, Taiwan"},{"name":"Department of Medical Research, China Medical University Hospital, China Medical University, 40402 Taichung, Taiwan"},{"name":"Department of Digital Media Design, Asia University, 41354 Taichung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.3390\/app7101101"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2012.01.926"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.3390\/app10030774"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.humov.2018.02.002"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2017.05.019"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2006.03.004"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.2648"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1186\/s12984-018-0465-9"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.3390\/s19235203"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2020.107857"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.3390\/e23040472"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2003.821662"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1515\/bmt.2010.030"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1186\/1687-6180-2012-127"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.3390\/s21010193"},{"issue":"3","key":"16","first-page":"1174","article-title":"Machine learning algorithms: a review","volume":"7","author":"A. 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