Cambridge Heartwear Limited

James Charles

Roberto Cipolla

Rameen Shakur

A method of detecting abnormalities in ECG signals by providing an ECG signal to a neural network, performing a first series of convolution operations to a first subset of layers and in a final layer, and determining a plurality of preliminary classification estimates, each preliminary classification estimate corresponding with a time segment of the ECG signal. Furthermore, determining input data for a second subset of layers of the neural network by concatenating the preliminary classification with the output of a layer of the first subset of layers that precedes the final layer of the first subset of layers. Within the second subset of layers of the neural network, performing a second series of convolution operations. In a final layer of the second subset, determining plurality of final classification estimates, each final classification estimate corresponding with a time segment of the ECG signal.

Detecting abnormalities in ECG signals

A method of detecting abnormalities in an ECG signals, comprising receiving an ECG signal, extracting at least one ECG beat the ECG signal; providing the at least one ECG beat to a neural network. Within the neural network, performing at least two layers of convolution operations, and for a beat of the ECG signal, determining a confidence map for the location of each of the P, Q, R, S and T points, determining, from the respective confidence maps the position or absence of points, the points comprising each of the P, Q, R, S and T points; and reporting the positions and/or absence of the points.

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Cambridge, United Kingdom

James Charles