Next Article in Journal
An Efficient Topology Discovery Protocol with Node ID Assignment Based on Layered Model for Underwater Acoustic Networks
Next Article in Special Issue
Bioimpedance Sensor and Methodology for Acute Pain Monitoring
Previous Article in Journal
Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set
Previous Article in Special Issue
Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sensors
Volume 20
Issue 22
10.3390/s20226593
sensors-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology

by
Ahmed Youssef Ali Amer
1,2,
Femke Wouters
3,4,
Julie Vranken
3,4,
Dianne de Korte-de Boer
5,
Valérie Smit-Fun
5,
Patrick Duflot
6,
Marie-Hélène Beaupain
7,
Pieter Vandervoort
3,4,
Stijn Luca
8,
Jean-Marie Aerts
2 and
Bart Vanrumste
1,*
1
E-MEDIA, STADIUS, Department of Electrical Engineering (ESAT), Campus Group T, KU Leuven, 3000 Leuven, Belgium
2
Measure, Model & Manage Bioresponses (M3-BIORES), Department of Biosystems, KU Leuven, 3000 Leuven, Belgium
3
Limburg Clinical Research Center/Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium
4
Limburg Clinical Research Center/Mobile Health Unit, Department of Anesthesiology, Department of Cardiology and Department Future Health, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium
5
Department of Anesthesiology and Pain Management, Maastricht UMC+, 6229 HX Maastricht, The Netherlands
6
Service des Applications Informatiques, Centre Hospitalier Universitaire de Liège—CHU, 4000 Liège, Belgium
7
Unité de Pneumologie—Cardiologie—radiothéRapie, Centre Hospitalier Universitaire de Liège—CHU, 4000 Liège, Belgium
8
Department of Data Analysis and Mathematical Modelling, Ghent University, 9000 Ghent, Belgium
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(22), 6593; https://doi.org/10.3390/s20226593
Submission received: 30 September 2020 / Revised: 13 November 2020 / Accepted: 16 November 2020 / Published: 18 November 2020
(This article belongs to the Special Issue Sensors and Biomedical Signal Processing for Patient Monitoring)
Browse Figures
Versions Notes

Abstract

In this prospective, interventional, international study, we investigate continuous monitoring of hospitalised patients’ 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.
Keywords: vital signs; early warning score; time-series prediction; kNN-LS-SVM; wearable technology vital signs; early warning score; time-series prediction; kNN-LS-SVM; wearable technology

Share and Cite

MDPI and ACS Style

Youssef Ali Amer, A.; Wouters, F.; Vranken, J.; de Korte-de Boer, D.; Smit-Fun, V.; Duflot, P.; Beaupain, M.-H.; Vandervoort, P.; Luca, S.; Aerts, J.-M.; et al. Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology. Sensors 2020, 20, 6593. https://doi.org/10.3390/s20226593

AMA Style

Youssef Ali Amer A, Wouters F, Vranken J, de Korte-de Boer D, Smit-Fun V, Duflot P, Beaupain M-H, Vandervoort P, Luca S, Aerts J-M, et al. Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology. Sensors. 2020; 20(22):6593. https://doi.org/10.3390/s20226593

Chicago/Turabian Style

Youssef Ali Amer, Ahmed, Femke Wouters, Julie Vranken, Dianne de Korte-de Boer, Valérie Smit-Fun, Patrick Duflot, Marie-Hélène Beaupain, Pieter Vandervoort, Stijn Luca, Jean-Marie Aerts, and et al. 2020. "Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology" Sensors 20, no. 22: 6593. https://doi.org/10.3390/s20226593

APA Style

Youssef Ali Amer, A., Wouters, F., Vranken, J., de Korte-de Boer, D., Smit-Fun, V., Duflot, P., Beaupain, M.-H., Vandervoort, P., Luca, S., Aerts, J.-M., & Vanrumste, B. (2020). Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology. Sensors, 20(22), 6593. https://doi.org/10.3390/s20226593

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop