PREGNANCY-RELATED COMPLICATION IDENTIFICATION AND PREDICTION FROM WEARABLE-BASED PHYSIOLOGICAL DATA

1 . A method comprising:

receiving, from a wearable device, physiological data associated with a user that is pregnant, the physiological data comprising at least temperature data;

determining a time series of a plurality of temperature values taken over a plurality of days based at least in part on the received temperature data;

identifying that the plurality of temperature values deviates from a pregnancy baseline of temperature values for the user based at least in part on determining the time series;

detecting an indication of one or more pregnancy complications of the user based at least in part on identifying that the plurality of temperature values deviate from the pregnancy baseline of temperature values for the user; and

generating a message for display on a graphical user interface on a user device that indicates the indication of the one or more pregnancy complications.

2 . The method of claim 1 , further comprising:

computing a deviation in the time series of the plurality of temperature values relative to the pregnancy baseline of temperature values based at least in part on determining the time series, wherein the deviation comprises a decrease in the plurality of temperature values from the pregnancy baseline of temperature values for a first portion of time and an increase in the plurality of temperature values from the pregnancy baseline of temperature values for a second portion of time following the first portion, wherein identifying that the plurality of temperature values deviate from the pregnancy baseline of temperature values is based at least in part on computing the deviation.

3 . The method of claim 1 , further comprising:

computing a photoplethysmography amplitude change of systolic and diastolic inflection points of a photoplethysmography waveform based at least in part on receiving the physiological data; and

identifying that a value of a photoplethysmography reflection index is greater than a value of a pregnancy baseline photoplethysmography reflection index based at least in part on computing the photoplethysmography amplitude change.

4 . The method of claim 1 , wherein the physiological data further comprises heart rate data, the method further comprising:

determining that the received heart rate data exceeds a pregnancy baseline heart rate for the user for at least a portion of the plurality of days, wherein detecting the indication of the one or more pregnancy complications is based at least in part on determining that the received heart rate data exceeds the pregnancy baseline heart rate for the user.

5 . The method of claim 1 , wherein the physiological data further comprises heart rate variability data, the method further comprising:

determining that the received heart rate variability data is less than a pregnancy baseline heart rate variability for the user for at least a portion of the plurality of days, wherein detecting the indication of the one or more pregnancy complications is based at least in part on determining that the received heart rate variability data is less than the pregnancy baseline heart rate variability for the user.

6 . The method of claim 1 , wherein the physiological data further comprises low frequency heart rate variability data, the method further comprising:

determining that the received low frequency heart rate variability data exceeds a pregnancy baseline low frequency heart rate variability for the user for at least a portion of the plurality of days, wherein detecting the indication of the one or more pregnancy complications is based at least in part on determining that the received low frequency heart rate variability data exceeds the pregnancy baseline low frequency heart rate variability for the user.

7 . The method of claim 1 , wherein the physiological data further comprises respiratory rate data, the method further comprising:

determining that the received respiratory rate data exceeds a pregnancy baseline respiratory rate for the user for at least a portion of the plurality of days, wherein detecting the indication of the one or more pregnancy complications is based at least in part on determining that the received respiratory rate data exceeds the pregnancy baseline respiratory rate for the user.

8 . The method of claim 1 , wherein the physiological data further comprises blood oxygen saturation data, the method further comprising:

determining that the received blood oxygen saturation data is less than a pregnancy baseline blood oxygen saturation for the user for at least a portion of the plurality of days, wherein detecting the indication of the one or more pregnancy complications is based at least in part on determining that the received blood oxygen saturation data is less than the pregnancy baseline blood oxygen saturation for the user.

9 . The method of claim 1 , further comprising:

receiving a confirmation of the one or more pregnancy complications, one or more pregnancy symptoms, or both, wherein detecting the indication of the one or more pregnancy complications is based at least in part on receiving the confirmation.

10 . The method of claim 1 , further comprising:

determining each temperature value of the plurality of temperature values based at least in part on receiving the temperature data, wherein the temperature data comprises continuous nighttime temperature data.

11 . The method of claim 1 , further comprising:

estimating a likelihood of a future pregnancy complication based at least in part on identifying that the plurality of temperature values deviates from than the pregnancy baseline of temperature values.

12 . The method of claim 1 , further comprising:

updating a readiness score associated with the user, an activity score associated with the user, a sleep score associated with the user, or a combination thereof, based at least in part on detecting the indication of the one or more pregnancy complications.

13 . The method of claim 1 , further comprising:

transmitting the message that indicates the indication of the one or more pregnancy complications to the user device, wherein the user device is associated with a clinician, the user, or both.

14 . The method of claim 1 , further comprising:

causing a graphical user interface of a user device associated with the user to display pregnancy complication symptom tags based at least in part on detecting the indication of the one or more pregnancy complications.

15 . The method of claim 1 , further comprising:

causing a graphical user interface of a user device associated with the user to display a message associated with the indication of the one or more pregnancy complications.

16 . The method of claim 15 , wherein the message further comprises a time interval during which the one or more pregnancy complications occurred, a time interval during which the one or more pregnancy complications are predicted to occur, a request to input symptoms associated with the one or more pregnancy complications, educational content associated with the one or more pregnancy complications, an adjusted set of sleep targets, an adjusted set of activity targets, recommendations to improve symptoms associated with the one or more pregnancy complications, a recommendation to consult a clinician, or a combination thereof.

17 . The method of claim 1 , further comprising:

inputting the physiological data into a machine learning classifier, wherein detecting the indication of the one or more pregnancy complications is based at least in part on inputting the physiological data into the machine learning classifier.

18 . The method of claim 1 , wherein the one or more pregnancy complications comprise pre-existing chronic hypertension, gestational hypertension, preeclampsia, eclampsia, cardiometabolic disorders, gestational diabetes, infections, or a combination thereof.

19 . An apparatus, comprising:

a processor;

memory coupled with the processor; and

instructions stored in the memory and executable by the processor to cause the apparatus to:

receive, from a wearable device, physiological data associated with a user that is pregnant, the physiological data comprising at least temperature data;

determine a time series of a plurality of temperature values taken over a plurality of days based at least in part on the received temperature data;

identify that the plurality of temperature values deviates from a pregnancy baseline of temperature values for the user based at least in part on determining the time series;

detect an indication of one or more pregnancy complications of the user based at least in part on identifying that the plurality of temperature values deviate from the pregnancy baseline of temperature values for the user; and

generate a message for display on a graphical user interface on a user device that indicates the indication of the one or more pregnancy complications.

20 . A non-transitory computer-readable medium storing code, the code comprising instructions executable by a processor to:

receive, from a wearable device, physiological data associated with a user that is pregnant, the physiological data comprising at least temperature data;

determine a time series of a plurality of temperature values taken over a plurality of days based at least in part on the received temperature data;

identify that the plurality of temperature values deviates from a pregnancy baseline of temperature values for the user based at least in part on determining the time series;

detect an indication of one or more pregnancy complications of the user based at least in part on identifying that the plurality of temperature values deviate from the pregnancy baseline of temperature values for the user; and

generate a message for display on a graphical user interface on a user device that indicates the indication of the one or more pregnancy complications.