Methods and systems for arrhythmia tracking and scoring
A dashboard centered around arrhythmia or atrial fibrillation tracking is provided. The dashboard includes a heart or cardiac health score that can be calculated in response to data from the user such as their ECG and other personal information and cardiac health influencing factors. The dashboard also provides to the user recommendations or goals, such as daily goals, for the user to meet and thereby improve their heart or cardiac health score. These goals and recommendations may be set by the user or a medical professional and routinely updated as his or her heart or cardiac health score improves or otherwise changes. The dashboard is generally displayed from an application provided on a smartphone or tablet computer of the user.
1. A smart watch to detect a presence of an arrhythmia of a user, comprising:
a processing device;
a photoplethysmography (“PPG”) sensor operatively coupled to the processing device;
an ECG sensor, comprising two or more ECG electrodes, the ECG sensor operatively coupled to the processing device;
a display operatively coupled to the processing device; and
a memory, operatively coupled to the processing device, the memory having instructions stored thereon that, when executed by the processing device, cause the processing device to:
receive PPG data from the PPG sensor;
receive ECG data from the ECG sensor;
detect, based on the PPG data and the ECG data simultaneously, the presence of an arrhythmia; and
provide one or more recommendations to the user based on the PPG data and the ECG data.
2. The smart watch of claim 1 , further comprising a motion sensor operatively coupled to the processing device, wherein to detect the presence of the arrhythmia, the processing device is configured to:
receive motion sensor data from the motion sensor; and
determine, from motion sensor data, that the user is at rest.
3. The smart watch of claim 2 , wherein to detect the presence of the arrhythmia, the processing device is configured to input the PPG data and the ECG data into a machine learning algorithm trained to detect arrhythmias.
4. The smart watch of claim 2 , wherein to detect the presence of the arrhythmia, the processing device is configured to:
determine heartrate variability (“HRV”) data from the PPG data and the ECG data;
input the HRV data into a machine learning algorithm trained to detect arrhythmias;
input the motion sensor data with the HRV data into the machine learning algorithm trained to detect arrhythmias; and
detect, based on the HRV data, the presence of the arrhythmia.
5. The smart watch of claim 1 , wherein the processing device is further configured to:
extract one or more features from the PPG data and the ECG data; and
detect, based on the one or more features, the presence of the arrhythmia.
6. The smart watch of claim 1 , wherein the processing device is further configured to generate a notification of the detected arrhythmia.
7. The smart watch of claim 1 , further comprising a biometric data sensor, wherein the processing device is further configured to:
receive biometric data of the user from the biometric data sensor, wherein the biometric data comprises at least one of: a temperature, a blood pressure, or an inertial data of the user, and wherein the processing device detects the presence of the arrhythmia based on the biometric data as well as the PPG data and the ECG data.
8. The smart watch of claim 1 , wherein the processing device is further configured to display an ECG rhythm strip from the ECG data on the display.
9. The smart watch of claim 1 , wherein the processing device is further to receive the ECG data from the ECG sensor in response to receiving an indication of a user action.
10. A method to detect a presence of an arrhythmia of a user on a smart watch, comprising:
receiving PPG data from a PPG sensor of the smart watch;
receiving ECG data from an ECG sensor of the smart watch;
detecting by a processing device, based on the PPG data and the ECG data simultaneously, the presence of an arrhythmia; and
providing one or more recommendations to the user based on the PPG data and the ECG data.
11. The method of claim 10 , wherein detecting the presence of the arrhythmia comprises:
receiving motion sensor data from a motion sensor of the smart watch; and
determining, from motion sensor data, that the user is at rest.
12. The method of claim 11 , wherein detecting the presence of the arrhythmia comprises inputting the PPG data and the ECG data into a machine learning algorithm trained to detect arrhythmias.
13. The method of claim 11 , wherein detecting the presence of the arrhythmia comprises:
determining heartrate variability (“HRV”) data from the PPG data and the ECG data; and
detecting, based on the HRV data, the presence of the arrhythmia.
14. The method of claim 13 , wherein detecting the presence of the arrhythmia comprises inputting the HRV data into a machine learning algorithm trained to detect arrhythmias.
15. The method of claim 14 , wherein detecting the presence of the arrhythmia comprises inputting the motion sensor data with the HRV data into the machine learning algorithm trained to detect arrhythmias.
16. The method of claim 10 , further comprising generating a notification of the detected arrhythmia.
17. The method of claim 10 , wherein the ECG data is received from the ECG sensor in response to receiving an indication of a user action.
18. A non-transitory computer-readable storage medium including instructions that, when executed by a processing device, cause the processing device to:
receive PPG data from a PPG sensor of a smart watch;
receive ECG data from an ECG sensor of the smart watch;
detect by the processing device, based on the PPG data and the ECG data simultaneously, a presence of an arrhythmia; and
providing one or more recommendations to the user based on the PPG data and the ECG data.
19. The non-transitory computer-readable storage medium of claim 18 , wherein the processing device is further configured to:
extract one or more features from the PPG data and the ECG data; and
detect, based on the one or more features, the presence of the arrhythmia.
20. The non-transitory computer-readable storage medium of claim 18 , wherein the processing device is further to receive the ECG data from the ECG sensor in response to receiving an indication of a user action.