US 12,293,833 B2
Heart condition detection sensor device and system for providing complex life support solution using same
Dong Joo Kim, Seoul (KR); Young Tak Kim, Nonsan-si (KR); and Hyun Ji Kim, Seoul (KR)
Assigned to Korea University Research and Business Foundation, Seoul (KR)
Appl. No. 18/008,266
Filed by Korea University Research and Business Foundation, Seoul (KR)
PCT Filed Jun. 11, 2021, PCT No. PCT/KR2021/007339
§ 371(c)(1), (2) Date Dec. 5, 2022,
PCT Pub. No. WO2021/251796, PCT Pub. Date Dec. 16, 2021.
Claims priority of application No. 10-2020-0071654 (KR), filed on Jun. 12, 2020; application No. 10-2020-0108603 (KR), filed on Aug. 27, 2020; and application No. 10-2020-0108604 (KR), filed on Aug. 27, 2020.
Prior Publication US 2023/0282352 A1, Sep. 7, 2023
Int. Cl. G16H 50/20 (2018.01); G16H 40/67 (2018.01); G16H 40/20 (2018.01)
CPC G16H 50/20 (2018.01) [G16H 40/67 (2018.01); G16H 40/20 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A server that is linked to a sensor device for detecting a heart condition and provides user condition information, the server comprising:
a monitoring information collector for collecting monitoring information comprising biosignals comprising electrocardiogram signals measured from a user;
a signal extractor for extracting the electrocardiogram signals comprised in the collected monitoring information;
an artificial intelligence processor configured to execute instructions; and
a memory storing the instructions, wherein execution of the instructions configures the artificial intelligence processor to:
extract morphological information as feature information by converting the extracted electrocardiogram signals into a time-standardized image based on a pre-stored artificial intelligence machine learning algorithm;
determining a plurality of cardiac abnormality type models using the extracted feature information;
calculating classification accuracy for the determined cardiac abnormality type models; and
determine a cardiovascular disease of the user using the determined cardiac abnormality type models and public cardiovascular disease data based on the calculated accuracy; and
a controller for controlling to provide the determined cardiovascular disease to a user terminal.