公开(公告)号：US20220076814A1

公开(公告)日：2022-03-10

申请号：US17419459

申请日：2020-11-25

Applicant: BEIJING BOE HEALTH TECHNOLOGY CO., LTD. ,  BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Zhou WANG ,  Yang PENG ,  Tongbo WANG ,  Zigang LIU ,  Feng QI ,  Guilong YANG ,  Yuan GAO ,  Yang HAN ,  Haiyun CUI

IPC: G16H40/20 ,  G16H40/67 ,  G16H15/00 ,  G06F16/903

Abstract: A health administration method, a health administration apparatus, a health administration system, and a data collection apparatus are provided. The health administration method involves a plurality of objects and a plurality of devices, and includes: generating a device usage record of at least one object based at least on identity information of the at least one object among the plurality of objects and data generated by a device used by the at least one object (S10), and providing the device usage record of the at least one object to a memory associated with a health administration apparatus (S20). The health administration method, the health administration apparatus, the health administration system, and the data collection apparatus can improve work efficiency of medical workers.

公开(公告)号：US20220338764A1

公开(公告)日：2022-10-27

申请号：US17763658

申请日：2021-05-21

Applicant: BOE Technology Group Co., Ltd.

Inventor： Yuan GAO ,  Xun ZHANG ,  Zhou WANG ,  Dongsheng HUANG ,  Yang HAN ,  Li ZHOU ,  Xin LI

IPC: A61B5/145 ,  A61B5/00 ,  A61B5/11 ,  G16H10/60

Abstract: A method, apparatus and device for obtaining a blood glucose measurement result. A neural network model is trained by using the following method, so as to obtain a trained first neural network model: acquiring a first invasive blood glucose measurement result of a tested object (101); forming a group of new training data by means of same and characteristic values of the most recent PPG signals of the tested object (102); training the neural network model with the training data, so as to obtain a trained first neural network model (106); and after a group of new PPG signals is acquired, extracting characteristic values of the new PPG signals, and inputting the characteristic values into the trained first neural network model, so as to obtain a target blood glucose measurement result (107).