Accuracy and Characteristic of Electrocardiographic Signal from Mobile Biomedical Sensor

Abstract

Based on the Global Burden of Disease and the Institute for Health Metrics and Evaluation 2014-2019, heart disease is the highest cause of death in Indonesia. One way to deal with this disease is through early detection by reading the electrical signals of the heart. Therefore, the technology for recording the electrocardiographic signal is developing rapidly. Recently, there have been many uses of biomedical sensors to record the electrical activity of the heart by utilizing internet facilities and without cables. This study discusses the accuracy and characterization of cardiac signals recorded by the portable KardiaMobile 6L against the Fukuda M.E Cardisuny type C100 clinical electrocardiograph (ECG). The data are taken from 9 patients using both devices simultaneously. ECG signals from the two devices are digitized using web plot digitizer to obtain the RR interval values. The clinical ECG produces 6 ECG signals (as short data). Meanwhile, the KardiaMobile produces ECG signals for 30 seconds (as long data- and five sequential ECG signals can be sampled as short data). Accuracy is done through linear regression, percent difference, and root mean squared error for the heart rate in two devices and RR interval from ECG signals. They provide excellent goodness of fit measures for the linear regression. The percent difference is still in the reliability of the devices. The value of RMSE is very low. Characterization of ECG signals is done by t-test between two array RR interval data from two leads for the same device. Using KardiaMobile, the RR interval value of short data is not significantly different from long data for a subject with normal sinus rhythm. The RR interval value of long data and short data between two leads is not significantly different. Using clinical ECG, the RR interval value of short data between two leads is not significantly different. Therefore, KardiaMobile has an accuracy similar with a clinical electrocardiograph in determining HR and is effective for analyzing dynamic changes based on RR intervals.