{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:14:05Z","timestamp":1761808445847,"version":"build-2065373602"},"reference-count":57,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,26]],"date-time":"2021-04-26T00:00:00Z","timestamp":1619395200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ss. Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]},{"name":"FCT\/MEC","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]},{"name":"FEDER---PT2020 partnership agreement","award":["UIDB\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020"]}]},{"name":"FCT-Foundation for Science and Technology, I.P.","award":["UIDB\/00742\/2020"],"award-info":[{"award-number":["UIDB\/00742\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Pneumonia caused by COVID-19 is a severe health risk that sometimes leads to fatal outcomes. Due to constraints in medical care systems, technological solutions should be applied to diagnose, monitor, and alert about the disease\u2019s progress for patients receiving care at home. Some sleep disturbances, such as obstructive sleep apnea syndrome, can increase the risk for COVID-19 patients. This paper proposes an approach to evaluating patients\u2019 sleep quality with the aim of detecting sleep disturbances caused by pneumonia and other COVID-19-related pathologies. We describe a non-invasive sensor network that is used for sleep monitoring and evaluate the feasibility of an approach for training a machine learning model to detect possible COVID-19-related sleep disturbances. We also discuss a cloud-based approach for the implementation of the proposed system for processing the data streams. Based on the preliminary results, we conclude that sleep disturbances are detectable with affordable and non-invasive sensors.<\/jats:p>","DOI":"10.3390\/s21093030","type":"journal-article","created":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T06:19:11Z","timestamp":1619504351000},"page":"3030","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Towards Detecting Pneumonia Progression in COVID-19 Patients by Monitoring Sleep Disturbance Using Data Streams of Non-Invasive Sensor Networks"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2744-0845","authenticated-orcid":false,"given":"Ace","family":"Dimitrievski","sequence":"first","affiliation":[{"name":"Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7664-0168","authenticated-orcid":false,"given":"Eftim","family":"Zdravevski","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5336-1796","authenticated-orcid":false,"given":"Petre","family":"Lameski","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4957-9477","authenticated-orcid":false,"given":"Mar\u00eda Vanessa","family":"Villasana","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Universidade da Beira Interior, 6200-506 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3394-6762","authenticated-orcid":false,"given":"Ivan","family":"Miguel Pires","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"},{"name":"Computer Science Department, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal"},{"name":"UICISA:E Research Centre, School of Health, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3195-3168","authenticated-orcid":false,"given":"Nuno M.","family":"Garcia","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3391-711X","authenticated-orcid":false,"given":"Francisco","family":"Fl\u00f3rez-Revuelta","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, Universidad de Alicante, 03690 Alicante, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8103-8059","authenticated-orcid":false,"given":"Vladimir","family":"Trajkovik","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science and Engineering, Ss. 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