Cardiac condition detection
First Claim
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1. A system, comprising:
- a garment comprising a plurality of electrodes and one or more accelerometers; and
a processing apparatus that is configured to;
receive acceleration measurements from the one or more accelerometers;
receive electrocardiogram measurements from the plurality of electrodes;
determine a posture pattern of a human based on the acceleration measurements;
determine a cardiac condition of the human based on the posture pattern and the electrocardiogram measurements by inputting features extracted from the electrocardiogram measurements and the posture pattern to a machine learning model previously determined based on training data; and
transmit or display an alert message that indicates the determined cardiac condition.
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Abstract
Systems and methods for determining a cardiac condition of the human based on acceleration measurements received from one or more accelerometers of a garment worn by a human, electrocardiogram measurements received from electrodes of a garment worn by the human, and a machine learning model previously determined based on training data. An alert message that indicates the determined cardiac condition may be transmitted or displayed to the human wearing the garment or another person who will assist the human. For example, a posture pattern may be determined based on the acceleration measurements. The cardiac condition may be determined based in part on the posture pattern.
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Citations
20 Claims
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1. A system, comprising:
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a garment comprising a plurality of electrodes and one or more accelerometers; and a processing apparatus that is configured to; receive acceleration measurements from the one or more accelerometers; receive electrocardiogram measurements from the plurality of electrodes; determine a posture pattern of a human based on the acceleration measurements; determine a cardiac condition of the human based on the posture pattern and the electrocardiogram measurements by inputting features extracted from the electrocardiogram measurements and the posture pattern to a machine learning model previously determined based on training data; and transmit or display an alert message that indicates the determined cardiac condition. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A method comprising:
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receiving acceleration measurements from one or more accelerometers of a garment worn by a human; receiving electrocardiogram measurements from electrodes of a garment worn by the human; determining a posture pattern of the human based on the acceleration measurements; determining a cardiac condition of the human based on the posture pattern and the electrocardiogram measurements by inputting features extracted from the electrocardiogram measurements and the posture pattern to a machine learning model previously determined based on training data; and transmitting or displaying an alert message that indicates the determined cardiac condition.
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20. A system comprising:
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a processor; a network interface; and a memory storing instructions executable by the processor that upon execution by the processor cause the processor to perform operations comprising; receiving acceleration measurements from one or more accelerometers of a garment worn by a human; receiving electrocardiogram measurements from electrodes of a garment worn by the human; determining a posture pattern of the human based on the acceleration measurements; determining a cardiac condition of the human based on the posture pattern and the electrocardiogram measurements by inputting features extracted from the electrocardiogram measurements and the posture pattern to a machine learning model previously determined based on training data; and transmitting, via the network interface, an alert message that indicates the determined cardiac condition.
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Specification