{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T22:54:54Z","timestamp":1775084094855,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,8,7]],"date-time":"2022-08-07T00:00:00Z","timestamp":1659830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Remotely monitoring people\u2019s healthcare is still among the most important research topics for researchers from both industry and academia. In addition, with the Wireless Body Networks (WBANs) emergence, it becomes possible to supervise patients through an implanted set of body sensors that can communicate through wireless interfaces. These body sensors are characterized by their tiny sizes, and limited resources (power, computing, and communication capabilities), which makes these devices prone to have faults and sensible to be damaged. Thus, it is necessary to establish an efficient system to detect any fault or anomalies when receiving sensed data. In this paper, we propose a novel, optimized, and hybrid solution between machine learning and statistical techniques, for detecting faults in WBANs that do not affect the devices\u2019 resources and functionality. Experimental results illustrate that our approach can detect unwanted measurement faults with a high detection accuracy ratio that exceeds the 99.62%, and a low mean absolute error of 0.61%, clearly outperforming the existing state-of-art solutions.<\/jats:p>","DOI":"10.3390\/s22155893","type":"journal-article","created":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T04:16:55Z","timestamp":1660018615000},"page":"5893","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Towards an Accurate Faults Detection Approach in Internet of Medical Things Using Advanced Machine Learning Techniques"],"prefix":"10.3390","volume":"22","author":[{"given":"Mohamed","family":"Bahache","sequence":"first","affiliation":[{"name":"Laboratoire d\u2019Informatique et de Math\u00e9matiques, Universit\u00e9 Amar Telidji, Laghouat 03000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdou El Karim","family":"Tahari","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Informatique et de Math\u00e9matiques, Universit\u00e9 Amar Telidji, Laghouat 03000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8673-0236","authenticated-orcid":false,"given":"Jorge","family":"Herrera-Tapia","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Inform\u00e1ticas, Universidad Laica Eloy Alfaro de Manab\u00ed, Manta 130214, Ecuador"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1414-3649","authenticated-orcid":false,"given":"Nasreddine","family":"Lagraa","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Informatique et de Math\u00e9matiques, Universit\u00e9 Amar Telidji, Laghouat 03000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5729-3041","authenticated-orcid":false,"given":"Carlos Tavares","family":"Calafate","sequence":"additional","affiliation":[{"name":"Computer Engineering Department (DISCA), Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9990-519X","authenticated-orcid":false,"given":"Chaker Abdelaziz","family":"Kerrache","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019Informatique et de Math\u00e9matiques, Universit\u00e9 Amar Telidji, Laghouat 03000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,7]]},"reference":[{"key":"ref_1","unstructured":"(2022, July 17). 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