Real-time Imitation of Autonomous MCG Node using Dual ECG Probing IoT Node Suitable for Delivery by UAV

The gigantic increase in population, social isolation, and mobility constraint lifestyle since the COVID-19 era has resulted in challenges like remote availability of critical bio-instrumentation like magnetocardiography (MCG) and electrocardiography (ECG). This availability can only be made possible through portable hand-held bio-instrumentation systems. Unmanned aerial vehicles (UAVs) can be used to deliver these systems to remote areas. In cardiological bioinstrumentation, MCG and ECG are two major innovations-based field effect techno-scientific approaches. The MCG systems face several major challenges that have hampered their applications and utility for cardio patients and their inspection labs. In this work, the main challenges were addressed by using a novel ML-based probabilistic interpolation algorithm over a dual ECG probing system-on-chip (SoC) with IoT capabilities to generate the identical MCG signal from two ECG signals with a segmented translation of PR, QRS, ST, and QT characteristic patches at real-time. The implementation findings provided a rich resource for approximating wave-shaping filters, frequencies, mean, and variance whilst addressing redundancy.