http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113288131-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-7235 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-14532 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-1455 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A61B5-02416 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-1455 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/A61B5-024 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 |
| filingDate | 2021-05-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-07-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-07-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113288131-B |
| titleOfInvention | Non-invasive blood glucose detection method, processor and device based on graph convolution network |
| abstract | The invention relates to the field of signal processing, and discloses a non-invasive blood sugar detection method, processor, device and storage medium based on a graph convolution network. The method includes: acquiring the PPG signal to be predicted; filtering the PPG signal to be predicted; converting the filtered PPG signal to be predicted into a node graph; obtaining a corresponding adjacency matrix and a feature matrix according to the node graph; inputting the adjacency matrix and the feature matrix into the graph Convolutional network, the corresponding blood sugar value is obtained through the graph convolutional network. Through the above technical solution, the present invention provides a deep learning method using a graph convolution network, which can make the model automatically find out the important feature information required for the blood sugar prediction problem, and at the same time, through the iterative update of the node information, In the case of retaining all feature information, the feature information is continuously optimized, so that the accuracy of blood glucose prediction is greatly improved. |
| priorityDate | 2021-05-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 24.