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US 12,661,051 B2Granted
Electrocardiogram interpretation
AssigneeWelch Allyn, Inc.
InventorsPatrick James Noffke, Nicoletta Marzocchi, Reyhaneh Sepehr, Eugene G. Urrutia
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Abstract
A system for interpreting an electrocardiogram identifies a segment of the electrocardiogram having an abnormality using a machine learning algorithm. The system assigns an interpretation output to the segment of the electrocardiogram having the abnormality. The interpretation output describes a morphology of the abnormality.
Claims17
A system for interpreting an electrocardiogram, the system comprising:
- at least one processing device;
- and
- a memory device storing instructions which, when executed by the at least one processing device, cause the at least one processing device to:
- receive the electrocardiogram;
- identify a segment of the electrocardiogram having an abnormality using a machine learning algorithm;
- and
- assign an interpretation output to the segment of the electrocardiogram having the abnormality, the interpretation output describing a morphology of the abnormality, wherein the interpretation output is assigned by:
- applying a range of transformations to the segment;
- feeding the range of transformations through a convolutional neural network;
- determining which transformation in the range of transformations produces a greatest return to normal;
- and
- generating the interpretation output as a reverse of the transformation that produces the greatest return to normal.
9 more elements
A system for generating an electrocardiogram, the system including:
- one or more electrodes for receiving heart electrical signals;
- at least one processing device;
- and
- a memory device storing instructions which, when executed by the at least one processing device, cause the at least one processing device to:
- generate the electrocardiogram based on the heart electrical signals;
- display the electrocardiogram on a display device;
- identify a segment of the electrocardiogram having an abnormality using a machine learning algorithm;
- and
- assign an interpretation output to the segment of the electrocardiogram having the abnormality, the interpretation output describing a morphology of the abnormality, wherein the interpretation output is assigned by:
- applying a range of transformations to the segment;
- feeding the range of transformations through a convolutional neural network;
- determining which transformation in the range of transformations produces a greatest return to normal;
- and
- generating the interpretation output as a reverse of the transformation that produces the greatest return to normal.
11 more elements
A method of interpreting an electrocardiogram, the method comprising:
- generating the electrocardiogram based on heart electrical signals;
- displaying the electrocardiogram;
- identifying a segment of the electrocardiogram having an abnormality using a machine learning algorithm;
- and
- assigning an interpretation output to the segment of the electrocardiogram having the abnormality, the interpretation output describing a morphology of the abnormality, wherein the interpretation output is assigned by:
- applying a range of transformations to the segment;
- feeding the range of transformations through a convolutional neural network;
- determining which transformation in the range of transformations produces a greatest return to normal;
- and
- generating the interpretation output as a reverse of the transformation that produces the greatest return to normal.
7 more elements
Dependencies are inferred from the claim text.