{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T19:50:30Z","timestamp":1774554630423,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T00:00:00Z","timestamp":1605657600000},"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>In this prospective, interventional, international study, we investigate continuous monitoring of hospitalised patients\u2019 vital signs using wearable technology as a basis for real-time early warning scores (EWS) estimation and vital signs time-series prediction. The collected continuous monitored vital signs are heart rate, blood pressure, respiration rate, and oxygen saturation of a heterogeneous patient population hospitalised in cardiology, postsurgical, and dialysis wards. Two aspects are elaborated in this study. The first is the high-rate (every minute) estimation of the statistical values (e.g., minimum and mean) of the vital signs components of the EWS for one-minute segments in contrast with the conventional routine of 2 to 3 times per day. The second aspect explores the use of a hybrid machine learning algorithm of kNN-LS-SVM for predicting future values of monitored vital signs. It is demonstrated that a real-time implementation of EWS in clinical practice is possible. Furthermore, we showed a promising prediction performance of vital signs compared to the most recent state of the art of a boosted approach of LSTM. The reported mean absolute percentage errors of predicting one-hour averaged heart rate are 4.1, 4.5, and 5% for the upcoming one, two, and three hours respectively for cardiology patients. The obtained results in this study show the potential of using wearable technology to continuously monitor the vital signs of hospitalised patients as the real-time estimation of EWS in addition to a reliable prediction of the future values of these vital signs is presented. Ultimately, both approaches of high-rate EWS computation and vital signs time-series prediction is promising to provide efficient cost-utility, ease of mobility and portability, streaming analytics, and early warning for vital signs deterioration.<\/jats:p>","DOI":"10.3390\/s20226593","type":"journal-article","created":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T07:41:00Z","timestamp":1605685260000},"page":"6593","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5347-9009","authenticated-orcid":false,"given":"Ahmed","family":"Youssef Ali Amer","sequence":"first","affiliation":[{"name":"E-MEDIA, STADIUS, Department of Electrical Engineering (ESAT), Campus Group T, KU Leuven, 3000 Leuven, Belgium"},{"name":"Measure, Model &amp; Manage Bioresponses (M3-BIORES), Department of Biosystems, KU Leuven, 3000 Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4420-6372","authenticated-orcid":false,"given":"Femke","family":"Wouters","sequence":"additional","affiliation":[{"name":"Limburg Clinical Research Center\/Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium"},{"name":"Limburg Clinical Research Center\/Mobile Health Unit, Department of Anesthesiology, Department of Cardiology and Department Future Health, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2691-0569","authenticated-orcid":false,"given":"Julie","family":"Vranken","sequence":"additional","affiliation":[{"name":"Limburg Clinical Research Center\/Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium"},{"name":"Limburg Clinical Research Center\/Mobile Health Unit, Department of Anesthesiology, Department of Cardiology and Department Future Health, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dianne","family":"de Korte-de Boer","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Pain Management, Maastricht UMC+, 6229 HX Maastricht, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5528-853X","authenticated-orcid":false,"given":"Val\u00e9rie","family":"Smit-Fun","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Pain Management, Maastricht UMC+, 6229 HX Maastricht, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Duflot","sequence":"additional","affiliation":[{"name":"Service des Applications Informatiques, Centre Hospitalier Universitaire de Li\u00e8ge\u2014CHU, 4000 Li\u00e8ge, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marie-H\u00e9l\u00e8ne","family":"Beaupain","sequence":"additional","affiliation":[{"name":"Unit\u00e9 de Pneumologie\u2014Cardiologie\u2014radioth\u00e9Rapie, Centre Hospitalier Universitaire de Li\u00e8ge\u2014CHU, 4000 Li\u00e8ge, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pieter","family":"Vandervoort","sequence":"additional","affiliation":[{"name":"Limburg Clinical Research Center\/Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium"},{"name":"Limburg Clinical Research Center\/Mobile Health Unit, Department of Anesthesiology, Department of Cardiology and Department Future Health, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6781-7870","authenticated-orcid":false,"given":"Stijn","family":"Luca","sequence":"additional","affiliation":[{"name":"Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5548-9163","authenticated-orcid":false,"given":"Jean-Marie","family":"Aerts","sequence":"additional","affiliation":[{"name":"Measure, Model &amp; Manage Bioresponses (M3-BIORES), Department of Biosystems, KU Leuven, 3000 Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bart","family":"Vanrumste","sequence":"additional","affiliation":[{"name":"E-MEDIA, STADIUS, Department of Electrical Engineering (ESAT), Campus Group T, KU Leuven, 3000 Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Brekke, I.J., Puntervoll, L.H., Pedersen, P.B., Kellett, J., and Brabr, M. 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