System and method for characterizing cardiac arrhythmia
In an embodiment, a data processing method comprises obtaining one or more photoplethysmography (PPG) signals from one or more PPG sensors of a monitoring apparatus, the PPG signals being generated based upon optically detecting pulsed variations in blood flow; obtaining a motion sensor signal from a motion sensor in the monitoring apparatus; identifying, based upon the motion sensor signal, one or more periods of motion (e.g., low motion) of the monitoring apparatus; and selectively obtaining and storing segments of the PPG signals based on a temporal relationship between the segments of the PPG signals and the identified periods of motion.
1. A method comprising:
obtaining photoplethysmography (PPG) waveform data for a user based on data from one or more optical sensors;
detecting a cardiac arrhythmia event based, at least in part, on the PPG waveform data; and
responsive to detecting the cardiac arrhythmia event based, at least in part, on the PPG waveform data, thereafter, prompting the user to perform an electrocardiogram (ECG) measurement.
2. The method of claim 1 , wherein the cardiac arrhythmia event is an atrial fibrillation event.
3. The method of claim 1 , wherein the PPG waveform data that is obtained was generated by:
determining a plurality of interbeat intervals in a PPG signal;
determining an interval of time that based, at least in part, on the plurality of interbeat intervals in the PPG signal, the interval of time including multiple of the plurality of interbeat intervals; and
determining one or more parameters of the PPG signal during the interval of time.
4. The method of claim 3 , wherein determining the plurality of interbeat intervals comprises identifying successive peak-to-peak intervals in the PPG signal.
5. The method of claim 3 , wherein the one or more parameters include a duration of the interbeat intervals occurring during the interval of time.
6. The method of claim 3 , wherein detecting the cardiac arrhythmia event comprises:
processing the one or more parameters with a classifier configured to determine whether the cardiac arrhythmia event occurred during the interval of time.
7. The method of claim 6 , wherein the classifier is trained using training data that includes values of the one or more parameters for a person having the cardiac arrhythmia event.
8. The method of claim 6 , wherein the classifier includes a linear discriminant classifier, a quadratic classifier, a random forest classifier, a decision tree classifier, a support vector machine classifier, and a neural network classifier.
9. The method of claim 1 , wherein prompting the user to perform the ECG measurement comprises generating a notification indicative of a need to perform the ECG measurement to confirm the cardiac arrhythmia event.
10. The method of claim 9 , wherein the notification comprises a messaged display on a display of an apparatus.
11. The method of claim 1 , further comprising obtaining an electrocardiogram (ECG) signal for the user via one or more electrical sensors.
12. A system comprising:
one or more processors; and
one or more memory devices, the one or more memory devices configured to store computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
obtaining photoplethysmography (PPG) waveform data for a user based on data from one or more optical sensors;
detecting a cardiac arrhythmia event based, at least in part, on the PPG waveform data; and
responsive to detecting the cardiac arrhythmia event based, at least in part, on the PPG waveform data, thereafter, prompting the user to perform an electrocardiogram (ECG) measurement.
13. The system of claim 12 , wherein the cardiac arrhythmia event is an atrial fibrillation event.
14. The system of claim 12 , wherein the PPG waveform data that is obtained was generated by:
determining a plurality of interbeat intervals in a PPG signal;
determining an interval of time that based, at least in part, on the plurality of interbeat intervals in the PPG signal, the interval of time including multiple of the plurality of interbeat intervals; and
determining one or more parameters of the PPG signal during the interval of time.
15. The system of claim 14 , wherein determining the plurality of interbeat intervals comprises identifying successive peak-to-peak intervals in the PPG signal.
16. The system of claim 14 , wherein the one or more parameters include a duration of the interbeat intervals occurring during the interval of time.
17. The system of claim 14 , wherein detecting the cardiac arrhythmia event comprises:
processing the one or more parameters with a classifier configured to determine whether the cardiac arrhythmia event occurred during the interval of time.
18. The system of claim 17 , wherein the classifier is trained using training data that includes values of the one or more parameters for a person having the cardiac arrhythmia event.
19. The system of claim 17 , wherein the classifier includes a linear discriminant classifier, a quadratic classifier, a random forest classifier, a decision tree classifier, a support vector machine classifier, and a neural network classifier.
20. The system of claim 12 , further comprising one or more electrical sensors for obtaining an electrocardiogram (ECG) signal for the user.