Systems and methods for providing user insights based on heart rate variability

1. A system for providing user insights based on heart rate variability (HRV), comprising:

a wearable device that obtains real-time physiological data from a user, obtains activity data from a user, and transmits the real-time physiological data and activity data; and

a processor configured to:

receive the physiological data and the activity data,

wherein the physiological data is used to calculate the HRV,

wherein the activity data describes at least two of a physical state of the user, the wearable device, or an environment of the user, and

wherein the activity data comprises at least three of the accelerometer-based movements of the user, illumination information, illumination change information, atmospheric pressure information, activity type, apparel worn by the user, running speed and distance information, step information, temperature information, temperature change information, light frequency, sound information, or location information;

identify, using the activity data, a stationary state of the user; and

in response to identifying the stationary state:

determine, based on correlating the physiological data and the activity data, whether the user's autonomic nervous system is in a predominantly parasympathetic state; and

in response to determining that the user's autonomic nervous system is in a parasympathetic state, perform an action.

2. The system of claim 1 , wherein determining whether the user's autonomic nervous system is in a predominantly parasympathetic state comprises calculating a heart rate variability score and comparing the score to a threshold value.

3. The system of claim 1 , wherein determining whether the user's autonomic nervous system is in a predominantly parasympathetic state comprises calculating a heart rate variability score, weighting the score based on information associated with the user, and comparing the weighted score to a threshold value.

4. The system of claim 3 , wherein the information associated with the user includes at least one of the user's age, sex, physical fitness level, and fitness history.

5. The system of claim 1 , wherein performing an action comprises providing an alert to the user indicating that the user is under stress.

6. The system of claim 1 , wherein performing an action comprises recommending an activity for the user to perform.

7. The system of claim 1 , wherein performing an action comprises dimming or turning off a light.

8. The system of claim 1 , wherein performing an action comprises playing music or adjusting the volume of music.

9. A method for providing user insights based on heart rate variability, comprising:

receiving physiological data and activity data obtained in real time from a user;

determining, based on the physiological data and the activity data, whether the user's autonomic nervous system is in a predominantly parasympathetic state by steps comprising;

identifying, using the activity data, a stationary state of the user using a body state of the user, wherein the stationary state is identified using criteria including identifying the stationary state when a same body position or pose of the user is kept and a heart rate does not change abruptly during a time threshold; and

in response to not identifying an activity associated with the stationary state, calculating a first heart rate variation indicium and a second heart rate variation indicium separately according to when the same body position or pose was unchanged and after the body position or pose changed; and

in response to determining that the user's autonomic nervous system is in a parasympathetic state, performing an action.

10. The method of claim 9 , wherein determining whether the user's autonomic nervous system is in a predominantly parasympathetic state comprises calculating a heart rate variability score and comparing the score to a threshold value.

11. The method of claim 9 , wherein determining whether the user's autonomic nervous system is in a predominantly parasympathetic state comprises calculating a heart rate variability score, weighting the score based on information associated with the user, and comparing the weighted score to a threshold value.

12. The method of claim 11 , wherein the information associated with the user includes at least one of the user's age, sex, physical fitness level, and fitness history.

13. The method of claim 9 , wherein performing an action comprises providing an alert to the user indicating that the user is under stress.

14. The method of claim 9 , wherein performing an action comprises recommending an activity for the user to perform.

15. The method of claim 9 , wherein performing an action comprises a first action of dimming or turning off a light or a second action of playing music or adjusting the volume of the music.

16. The method of claim 9 , further comprising:

calculating a plurality of heart rate variability scores using at least the physiological data for a respective plurality of time periods; and

displaying, on a device of the user, each of the plurality of the heart rate variability scores in a respective slice of a doughnut-shaped graph,

wherein the respective slices have equal widths,

wherein the respective slices have respective heights indicative of respective magnitudes of the heart rate variability scores, and

wherein an average of the plurality of the heart rate variability scores is displayed at a center of the doughnut-shaped graph.

17. A non-transitory, computer-readable medium containing instructions that, when executed by the processor of a computing device, cause the processor to carry out stages for providing user insights based on heart rate variability, the stages comprising:

receiving physiological data and activity data obtained in real time from a user,

wherein the physiological data is used to calculate the HRV,

wherein the activity data describes at least two of a physical state of the user, the wearable device, or an environment of the user, and

wherein the activity data comprises at least three of the accelerometer-based movements of the user, illumination information, illumination change information, atmospheric pressure information, activity type, apparel worn by the user, running speed and distance information, step information, temperature information, temperature change information, light frequency, sound information, or location information;

identify, using the activity data, a stationary state of the user; and

in response to identifying the stationary state:

determine, based on correlating the physiological data and the activity data, whether the user's autonomic nervous system is in a predominantly parasympathetic state; and

in response to determining that the user's autonomic nervous system is in a parasympathetic state, perform an action.

18. The non-transitory, computer-readable medium of claim 17 , further comprising:

determining, based on at least the physiological data, whether the user's autonomic nervous system is in a predominantly parasympathetic state,

wherein determining whether the user's autonomic nervous system is in a predominantly parasympathetic state comprises calculating a heart rate variability score and comparing the score to a threshold value; and

in response to determining that the user's autonomic system is in a parasympathetic state and to identifying that the user is driving:

identifying based on the location of the user a proximal location to stop; and

informing the user to stop at the location to perform an activity, wherein the activity is at least one of resting or exercising.

19. The non-transitory, computer-readable medium of claim 17 , wherein determining whether the user's autonomic nervous system is in a predominantly parasympathetic state comprises calculating a heart rate variability score, weighting the score based on information associated with the user, and comparing the weighted score to a threshold value.

20. The non-transitory, computer-readable medium of claim 19 , wherein the information associated with the user includes at least one of the user's age, sex, physical fitness level, and fitness history.