Abstract: The disclosure relates to systems and methods of converting a representation of a physiological signal (e.g., a non-digitized version such as a printed curve) into a digitized representation of the physiological signal of a subject. For example, a printed electrocardiogram (ECG) may be digitized using the systems are methods provided herein. The method may include receiving a digitized image of a printed curve representing the physiological signal of the subject, and detecting at least one region of interest having a portion of the physiological signal. For each of the regions of interest, the method may include extracting coordinates representing the physiological signal and registering the extracted coordinates.

Abstract: A method for computerizing delineation and/or multi-label classification of an ECG signal, includes: applying a neural network to the ECG whereby labelling the ECG, and optionally displaying the labels according to time, optionally with the ECG signal.

Abstract: Disclosed is a method for computerizing delineation and/or multi-label classification of an ECG signal, including: applying a neural network to the ECG, labelling the ECG, and optionally displaying the labels according to time with the ECG signal.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.