Telemedicine-based baby incubator system with DWT method to detect respiratory rate from electrocardiogram signals

Abstract

This pioneering research introduces a telemedicine-based baby incubator designed to accurately monitor premature babies’ electrical heart signals and respiratory rates. The research aims to monitor premature babies, especially those related to heart and respiratory problems. This research combines telemedicine technology with the discrete wavelet transform (DWT) method to obtain respiratory rate values from electrocardiogram (ECG) signal leads directly. This research contribution can be used for simultaneous and non-invasive monitoring of heart electrical signals and respiratory rate. By leveraging existing telemedicine infrastructure, this incubator enables real-time monitoring. Using a data-driven approach with premature babies as subjects, respiratory signals are captured using sensitive sensors and analyzed via the DWT method. The results show that the accuracy of this telemedicine-based incubator is superior in monitoring respiratory rate compared to conventional methods with a P-value>0.05. This study confirms the effectiveness of DWT-based telemedicine incubators in monitoring the breathing of premature babies, thereby offering superior performance compared to traditional methods. The implications resulting from this research as a whole, this telemedicine-based baby incubator marks a significant advancement in the care of premature babies, ensuring precise and real-time breathing monitoring.