Method, apparatus and program for measuring electrocardiogram-based blood glucose using artificial intelligence
AssigneeIplemind.inc
InventorsSeoung Han Lee, Seung Hee Baik
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Abstract
A method for measuring an electrocardiogram-based blood glucose using artificial intelligence is provided. The method includes: receiving an electrocardiogram signal of a user; extracting a plurality of unit electrocardiogram signals from the received electrocardiogram signal; extracting a blood glucose spatial feature from each of the plurality of unit electrocardiogram signals using a first artificial neural network model; and extracting a blood glucose feature by analyzing a time series change of the blood glucose spatial feature using a second artificial neural network model, and predicting blood glucose of the user based on the extracted blood glucose feature.
Claims21
1-10. (canceled)
A method for measuring electrocardiogram-based blood glucose using artificial intelligence, the method comprising:
- receiving an electrocardiogram signal of a user;
- extracting a plurality of unit electrocardiogram signals from the received electrocardiogram signal;
- extracting a blood glucose spatial feature from each of the plurality of unit electrocardiogram signals using a first artificial neural network model;
- and
- extracting a blood glucose feature by analyzing a time series change of the blood glucose spatial feature using a second artificial neural network model, and predicting blood glucose of the user based on the extracted blood glucose feature.
An apparatus for measuring electrocardiogram-based blood glucose using artificial intelligence, the apparatus comprising:
- an electrocardiogram signal receiving unit configured to receive an electrocardiogram signal of a user and extract a plurality of unit electrocardiogram signals from the received electrocardiogram signal;
- and
- an AI processor configured to extract a blood glucose spatial feature from each of the plurality of unit electrocardiogram signals using a first artificial neural network model, extract a blood glucose feature by analyzing a time series change of the blood glucose spatial feature using a second artificial neural network model, and predict blood glucose of the user based on the extracted blood glucose feature.
A user-customized healthcare service system comprising:
- an electrocardiogram measuring device configured to measure an electrocardiogram of a user;
- an electrocardiogram-based blood glucose apparatus configured to receive an electrocardiogram signal of the user from the electrocardiogram measuring device, extract a plurality of unit electrocardiogram signals from the received electrocardiogram signal, and predict blood glucose of the user from the plurality of unit electrocardiogram signals using a trained artificial neural network model;
- and
- a server configured to provide an emergency dispatch service to a location of the user or provide a user-customized prescription service when the blood glucose of the user measured by the electrocardiogram-based blood glucose measuring apparatus is in a dangerous state,
- wherein the electrocardiogram-based blood glucose measuring apparatus is configured to extract a blood glucose spatial feature from each of the plurality of unit electrocardiogram signals using a first artificial neural network model, extract a blood glucose feature by analyzing a time series change of the blood glucose spatial feature using a second artificial neural network model, and predict blood glucose of the user based on the extracted blood glucose feature.
Dependencies are inferred from the claim text.