Apparatus and method for dynamically determining a label for a cardiac potential signal via simulation of neural network trained data

An apparatus for determining a label dynamically using a potential signal, wherein the apparatus comprises:

• a catheter which includes a transducer configured to detect at least a cardiac phenomenon and output the at least a potential signal as a function of the cardiac phenomenon;
• a memory;
• and
• at least a processor communicatively connected to the memory, wherein the memory contains instructions configuring the at least a processor to:
• receive a user input comprising a labeled datum associated with the at least a potential signal of one or both of electrocardiogram (ECG) signal and electrogram (EGM) signal;
• receive a plurality of stored data associated with the at least a potential signal;
• generate, using the at least a processor, a plurality of canonicalized data by processing the plurality of stored data;
• transmit, using a real time data simulator, the plurality of canonicalized data to a simulation module, wherein the simulation module has been trained using a plurality of labeled training data comprising a signal segment corresponding to a segment label;
• wherein the simulation module comprises:
• a segmentation model comprising a convolutional neural network and configured to generate a plurality of segmented data as a function of the plurality of canonicalized data and at least a temporal datum;
• generate, using the simulation module, a labeled prediction corresponding to a segmented datum of the plurality of segmented data, wherein generating the labeled prediction comprises:
• receiving the plurality of canonicalized data from the real time data simulator;
• segmenting the plurality of canonicalized data;
• predicting a labeled prediction for each of the plurality of canonicalized data;
• generating a labeled prediction corresponding to a segmented datum;
• and
• display the labeled prediction through a graphical user interface.