Sensors, Vol. 20, Pages 6593: Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology

Sensors, Vol. 20, Pages 6593: Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology Sensors doi: 10.3390/s20226593 Authors: Ahmed Youssef Ali Amer Femke Wouters Julie Vranken Dianne de Korte-de Boer Valérie Smit-Fun Patrick Duflot Marie-Hélène Beaupain Pieter Vandervoort Stijn Luca Jean-Marie Aerts Bart Vanrumste 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 o...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research