Cardiac Arrhythmia Prediction by Adaptive Analysis via Bluetooth

Ricardo Rodrguez-Jorge; Jiri Bila

doi:10.13164/mendel.2020.2.029

Ricardo Rodrguez-Jorge Jan Evangelista Purkyne University
Jiri Bila Department of Instrumentation and Control Engineering, Czech Technical University in Prague, Czech Republic

DOI: https://doi.org/10.13164/mendel.2020.2.029

Keywords: Dynamic quadratic neural unit, recurrent learning, adaptive monitoring, biomedical data acquisition, cardiac arrhythmia, prediction

Abstract

In this work, the development of a data acquisition system for adaptive monitoring based on a dynamic quadratic neural unit is presented. Acquisition of the continuous signal is achieved with the BITalino biomedical data acquisition card. The system is trained sample-by-sample with a real time recurrent learning method. Then, possible cardiac arrhythmia is predicted by implementing the adaptive monitoring in real time to recognize patterns that predict cardiac arrhythmia up to 1 second in advance. For the evaluation of the interface, tests are performed using the obtained signal in real time

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