Techniques for measuring cumulative stress using wearable-based data

1 . A method for measuring cumulative stress of a user over time, comprising:

acquiring baseline physiological data from the user via a wearable device, the baseline physiological data comprising at least a pulse waveform associated with a heart rate of the user;

determining a baseline stress level associated with the user based at least in part on the baseline physiological data, one or more user inputs received via a user device, or both;

determining, based at least in part on variation in an interbeat interval (IBI) of the pulse waveform of the baseline physiological data, a first baseline heart rate variability (HRV) value of the user during periods that the user is awake, and a second baseline HRV value of the user during periods that the user is asleep;

acquiring additional physiological data from the user via the wearable device throughout a time interval that spans a plurality of days and a plurality of nights;

determining, based at least in part on the additional physiological data, a first set of HRV values of the user during periods of the time interval that the user is awake, and a second set of HRV values of the user during periods of the time interval that the user is asleep;

determining one or more stress scores associated with the user throughout periods of the time interval that the user is awake based at least in part on a first comparison of the first set of HRV values with the first baseline HRV value;

determining one or more recovery scores associated with the user throughout periods of the time interval that the user is asleep based at least in part on a second comparison of the second set of HRV values with the second baseline HRV value;

determining a cumulative stress level of the user throughout the time interval based at least in part on the one or more stress scores associated with periods of the time interval that the user is awake, and the one or more recovery scores associated with periods of the time interval that the user is asleep, wherein the cumulative stress level is based at least in part on the baseline stress level, and wherein the cumulative stress level is associated with a total amount of stress the user experienced throughout the time interval, a trend in a stress level of the user throughout the time interval, or both; and

displaying, to the user via a graphical user interface (GUI) of the user device, a visual representation of the cumulative stress level.

2 . The method of claim 1 , further comprising:

determining the baseline stress level associated with the user based at least in part on the baseline physiological data, wherein the baseline physiological data comprises heart rate data, respiratory rate data, skin temperature data, or any combination thereof, and wherein determining the cumulative stress level is based at least in part on the baseline stress level.

3 . The method of claim 2 , further comprising:

predicting a burnout condition of the user, a chronic stress condition of the user, or both, based at least in part on a comparison between the cumulative stress level and the baseline stress level associated with the user; and

causing the GUI of the user device to display an alert associated with the burnout condition, the chronic stress condition, or both.

4 . The method of claim 2 , further comprising:

receiving, from the user device, the one or more user inputs comprising one or more characteristics associated with the user, wherein determining the baseline stress level is based at least in part on the one or more user inputs.

5 . The method of claim 4 , further comprising:

acquiring additional baseline physiological data associated with a plurality of users associated with a set of characteristics that are common between the plurality of users and the user; and

determining a plurality of baseline stress levels associated with the plurality of users, wherein determining the baseline stress level associated with the user is based at least in part on determining the plurality of baseline stress levels and a comparison between the baseline physiological data associated with the user and the additional baseline physiological data associated with the plurality of users.

6 . The method of claim 1 , wherein acquiring the baseline physiological data further comprises:

providing, to the user via the GUI of the user device, instructions for the user to modify one or more behaviors associated with a target stress level of the user;

receiving, from the wearable device and based at least in part on providing the instructions to the user, a plurality of physiological measurements associated with the one or more behaviors; and

determining the baseline stress level associated with the user based at least in part on comparing the plurality of physiological measurements with the baseline physiological data, wherein determining the cumulative stress level is based at least in part on determining the baseline stress level.

7 . The method of claim 1 , wherein the visual representation indicates a relative change between a baseline stress level associated with the user and the cumulative stress level.

8 . The method of claim 1 , further comprising:

classifying a plurality of periods within time interval that the user is either awake or asleep as one of a stressful period, a recovery period, or a neutral period based at least in part on the first comparison of the first set of HRV values with the first baseline HRV value and the second comparison of the second set of HRV values with the second baseline HRV value, wherein determining the cumulative stress level is based at least in part on the classifying.

9 . The method of claim 1 , further comprising:

providing, via the GUI of the user device, feedback to the user comprising instructions for modifying one or more behaviors of the user, the one or more behaviors configured to modify the cumulative stress level of the user.

10 . The method of claim 1 , wherein the baseline physiological data is acquired throughout a second time interval prior to the time interval, the second time interval comprising a second plurality of days and a second plurality of nights.

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

12 . A system for measuring cumulative stress of a user over time, comprising:

at least one processor;

at least one memory coupled with the at least one processor; and

instructions stored in the at least one memory and executable by the at least one processor to:

acquire baseline physiological data from the user via a wearable device, the baseline physiological data comprising at least a pulse waveform associated with a heart rate of the user;

determine a baseline stress level associated with the user based at least in part on the baseline physiological data, one or more user inputs received via a user device, or both;

determine, based at least in part on variation in an interbeat interval (IBI) of the pulse waveform of the baseline physiological data, a first baseline heart rate variability (HRV) value of the user during periods that the user is awake, and a second baseline HRV value of the user during periods that the user is asleep;

acquire additional physiological data from the user via the wearable device throughout a time interval that spans a plurality of days and a plurality of nights;

determine, based at least in part on the additional physiological data, a first set of HRV values of the user during periods of the time interval that the user is awake, and a second set of HRV values of the user during periods of the time interval that the user is asleep;

determine one or more stress scores associated with the user throughout periods of the time interval that the user is awake based at least in part on a first comparison of the first set of HRV values with the first baseline HRV value;

determine one or more recovery scores associated with the user throughout periods of the time interval that the user is asleep based at least in part on a second comparison of the second set of HRV values with the second baseline HRV value;

determine a cumulative stress level of the user throughout the time interval based at least in part on the one or more stress scores associated with periods of the time interval that the user is awake, and the one or more recovery scores associated with periods of the time interval that the user is asleep, wherein the cumulative stress level is based at least in part on the baseline stress level, and wherein the cumulative stress level is associated with a total amount of stress the user experienced throughout the time interval, a trend in a stress level of the user throughout the time interval, or both; and

display, to the user via a graphical user interface (GUI) of the user device, a visual representation of the cumulative stress level.

13 . The system of claim 12 , wherein the at least one processor is further configured to:

determine the baseline stress level associated with the user based at least in part on the baseline physiological data, wherein the baseline physiological data comprises heart rate data, respiratory rate data, skin temperature data, or any combination thereof, and wherein determining the cumulative stress level is based at least in part on the baseline stress level.

14 . The system of claim 13 , wherein the at least one processor is further configured to:

predict a burnout condition of the user, a chronic stress condition of the user, or both, based at least in part on a comparison between the cumulative stress level and the baseline stress level associated with the user; and

cause the GUI of the user device to display an alert associated with the burnout condition, the chronic stress condition, or both.

15 . The system of claim 12 , wherein the at least one processor is further configured to:

classify a plurality of periods within time interval that the user is either awake or asleep as one of a stressful period, a recovery period, or a neutral period based at least in part on the first comparison of the first set of HRV values with the first baseline HRV value and the second comparison of the second set of HRV values with the second baseline HRV value, wherein determining the cumulative stress level is based at least in part on the classifying.

16 . A non-transitory computer-readable medium storing code for measuring cumulative stress of a user over time, the code comprising instructions executable by at least one processor to:

acquire baseline physiological data from the user via a wearable device, the baseline physiological data comprising at least a pulse waveform associated with a heart rate of the user;

determine a baseline stress level associated with the user based at least in part on the baseline physiological data, one or more user inputs received via a user device, or both;

determine, based at least in part on variation in an interbeat interval (IBI) of the pulse waveform of the baseline physiological data, a first baseline heart rate variability (HRV) value of the user during periods that the user is awake, and a second baseline HRV value of the user during periods that the user is asleep;

acquire additional physiological data from the user via the wearable device throughout a time interval that spans a plurality of days and a plurality of nights;

determine, based at least in part on the additional physiological data, a first set of HRV values of the user during periods of the time interval that the user is awake, and a second set of HRV values of the user during periods of the time interval that the user is asleep;

determine one or more stress scores associated with the user throughout periods of the time interval that the user is awake based at least in part on a first comparison of the first set of HRV values with the first baseline HRV value;

determine one or more recovery scores associated with the user throughout periods of the time interval that the user is asleep based at least in part on a second comparison of the second set of HRV values with the second baseline HRV value;

determine a cumulative stress level of the user throughout the time interval based at least in part on the one or more stress scores associated with periods of the time interval that the user is awake, and the one or more recovery scores associated with periods of the time interval that the user is asleep, wherein the cumulative stress level is based at least in part on the baseline stress level, and wherein the cumulative stress level is associated with a total amount of stress the user experienced throughout the time interval, a trend in a stress level of the user throughout the time interval, or both; and

display, to the user via a graphical user interface (GUI) of the user device, a visual representation of the cumulative stress level.

17 . The non-transitory computer-readable medium of claim 16 , the code comprising instructions executable by the at least one processor to:

determine the baseline stress level associated with the user based at least in part on the baseline physiological data, wherein the baseline physiological data comprises heart rate data, respiratory rate data, skin temperature data, or any combination thereof, and wherein determining the cumulative stress level is based at least in part on the baseline stress level.

18 . The non-transitory computer-readable medium of claim 17 , the code comprising instructions executable by the at least one processor to:

predict a burnout condition of the user, a chronic stress condition of the user, or both, based at least in part on a comparison between the cumulative stress level and the baseline stress level associated with the user; and

cause the GUI of the user device to display an alert associated with the burnout condition, the chronic stress condition, or both.

19 . The non-transitory computer-readable medium of claim 16 , the code comprising instructions executable by the at least one processor to:

classify a plurality of periods within time interval that the user is either awake or asleep as one of a stressful period, a recovery period, or a neutral period based at least in part on the first comparison of the first set of HRV values with the first baseline HRV value and the second comparison of the second set of HRV values with the second baseline HRV value, wherein determining the cumulative stress level is based at least in part on the classifying.