LABOR ONSET AND BIRTH 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;

calculating a pregnancy baseline temperature slope for the user for at least a portion of the plurality of days;

identifying that a temperature slope of at least a set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user based at least in part on calculating the pregnancy baseline temperature slope;

detecting an indication of a labor onset of the user based at least in part on identifying that the temperature slope of at least the set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user; and

generating a message for display on a graphical user interface on a user device that indicates the indication of the labor onset.

2 . The method of claim 1 , further comprising:

computing a deviation in the temperature slope of at least the set of the plurality of temperature values relative to the pregnancy baseline temperature slope for the user based at least in part on calculating the pregnancy baseline temperature slope, wherein the pregnancy baseline temperature slope comprises a negative slope different from a negative slope of the temperature slope of at least the set of the plurality of temperature values, wherein detecting the indication of the labor onset is based at least in part on computing the deviation.

3 . The method of claim 1 , further comprising:

identifying one or more positive slopes of the plurality of temperature values based at least in part on determining the time series, wherein detecting the labor onset is based at least in part on identifying the one or more positive slopes of the plurality of temperature values.

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 deviates from a pregnancy baseline heart rate for the user for at least a portion of the plurality of days, wherein detecting the indication of the labor onset is based at least in part on determining that the received heart rate data deviates from 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 deviates from 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 labor onset is based at least in part on determining that the received heart rate variability data deviates from the pregnancy baseline heart rate variability for the user.

6 . 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 deviates from a pregnancy baseline respiratory rate for the user for at least a portion of the plurality of days, wherein detecting the indication of the labor onset is based at least in part on determining that the received respiratory rate data deviates from the pregnancy baseline respiratory rate for the user.

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

determining that a quantity of detected sleep disturbances from the received sleep data deviates from a pregnancy baseline sleep disturbance for the user for at least a portion of the plurality of days, wherein detecting the indication of the labor onset is based at least in part on determining that the quantity of detected sleep disturbances deviates from the pregnancy baseline sleep disturbance for the user.

8 . The method of claim 1 , further comprising:

identifying a circadian rhythm for the user based at least in part on determining the time series, wherein detecting the indication of the labor onset is based at least in part on identifying the circadian rhythm for the user and applying the circadian rhythm to the time series of the plurality of temperature values.

9 . The method of claim 1 , further comprising:

receiving a confirmation of the labor onset, wherein detecting the indication of the labor onset 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 future labor onset, a likelihood that the user will experience the labor onset, a likelihood of future birth, a likelihood that the user will experience birth, a likelihood of future labor contractions, a likelihood that the user will experience labor contractions, or a combination thereof, based at least in part on identifying that the temperature slope of at least the set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user, wherein detecting the indication of the labor onset is based at least in part on the estimation.

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 labor onset.

13 . The method of claim 1 , further comprising:

transmitting the message that indicates the indication of the labor onset 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 labor onset symptom tags based at least in part on detecting the indication of the labor onset.

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 labor onset, wherein the indication of the labor onset comprises an indication of labor contractions, an indication of birth, or both.

16 . The method of claim 15 , wherein the message further comprises a time interval during which the labor onset occurred, a time interval during which the labor onset is predicted to occur, a time interval during which the birth is predicted to occur, a time interval during which the labor contractions are predicted to occur, a duration between each labor contraction of the labor contractions that are predicted to occur, a request to input symptoms associated with the labor onset, educational content associated with the labor onset, an adjusted set of sleep targets, an adjusted set of activity targets, recommendations to improve symptoms associated with the labor onset, 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 labor onset is based at least in part on inputting the physiological data into the machine learning classifier.

18 . The method of claim 1 , wherein the wearable device comprises a wearable ring device.

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;

calculate a pregnancy baseline temperature slope for the user for at least a portion of the plurality of days;

identify that a temperature slope of at least a set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user based at least in part on calculating the pregnancy baseline temperature slope;

detect an indication of a labor onset of the user based at least in part on identifying that the temperature slope of at least the set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user; and

generate a message for display on a graphical user interface on a user device that indicates the indication of the labor onset.

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;

calculate a pregnancy baseline temperature slope for the user for at least a portion of the plurality of days;

identify that a temperature slope of at least a set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user based at least in part on calculating the pregnancy baseline temperature slope;

detect an indication of a labor onset of the user based at least in part on identifying that the temperature slope of at least the set of the plurality of temperature values deviates from the pregnancy baseline temperature slope for the user; and

generate a message for display on a graphical user interface on a user device that indicates the indication of the labor onset.