A Study on the Effectiveness of the Application of an Artificial Intelligence Algorithm for Calibrating PPG With ECG to Improve the Accuracy of Atrial Fibrillation Burden Estimation
A Study on the Effectiveness of the Application of an Artificial Intelligence Algorithm for Calibrating PPG With ECG to Improve the Accuracy of Atrial Fibrillation Burden Estimation
Use the ECG watch to collect W-PPG and W-ECG data. Through artificial intelligence algorithms, compare the W-PPG data collected by the ECG watch and the W-PPG data calibrated by the W-ECG data of the ECG watch with the P-ECG data manually annotated after being collected by the ECG recorder. Then evaluate the effectiveness of the calibrated algorithm in improving the accuracy of estimating atrial fibrillation burden.
After the subjects are fully informed and sign the informed consent form, they will be asked to wear the "ECG recorder" and the "ECG watch" simultaneously to collect P-ECG data as well as W-PPG and W-ECG data respectively. The collection period is from the patient's admission to the time before the patient's surgery. The collected data will be analyzed by the "Smart-AF" of Xinjikang Company. The W-PPG data collected by the ECG watch and the W-PPG data calibrated by the W-ECG data of the ECG watch will be compared with the P-ECG data that has been manually annotated after being collected by the ECG recorder. The differences in identifying atrial fibrillation and in the statistics of atrial fibrillation burden between the W-PPG data of atrial fibrillation patients and the P-ECG data as well as the W-PPG and P-ECG data calibrated by comparison with the W-ECG data will be compared.
ECG Watch ECG Monitoring Method:
Inclusion Criteria
Patients must meet all of the following criteria to be included in the study:
Exclusion Criteria
Patients who meet any of the following criteria cannot be included in this study: