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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 Methodļ¼
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AF monitoring by a smartwatch with PPG | Device | The device we used for intervention is a smartwatch (JKwear 1, Chengdu CVhealth Science and Technology Co., Ltd, CN) for collecting watch-recorded-PPG (W-PPG). |
| Measure | Description | Time Frame |
|---|---|---|
| Automatically analyze the W-PPG data and the W-PPG data calibrated by W-ECG. | Automatically analyze the W-PPG data and the W-PPG data calibrated by W-ECG through the "Smart-AF" of Xinjikang Company, and then compare the analyzed results with the P-ECG results manually annotated and proofread. | One day |
| Measure | Description | Time Frame |
|---|---|---|
| Automatically analyze the W-PPG data and the W-PPG data calibrated by W-ECG. | Automatically analyze the W-PPG data calibrated by W-ECG through artificial intelligence algorithms. Then compare the analyzed results with the P-ECG results that have been manually annotated and proofread. Finally, evaluate the sensitivity and specificity of the artificial intelligence algorithms in analyzing and identifying atrial fibrillation from the W-PPG data calibrated by W-ECG. |
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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:
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Patients with AF who were hospitalized for AF in the Department of Cardiology, Beijing Anzhen Hospital.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Beijing Anzhen Hospital | Beijing | China |
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Photoplethysmography dataćElectrocardiogram data
| One day |
| ID | Term |
|---|---|
| D001281 | Atrial Fibrillation |
| ID | Term |
|---|---|
| D001145 | Arrhythmias, Cardiac |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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