Coaching based on physiological cycle

Abstract

A method of suggesting adjustments to a sleep regimen based on a hormonal cycle by performing the steps of: acquiring heart rate data for a user from a wearable physiological monitoring device worn co

Claims

1. A computer implemented method for calculating an amount of sleep for a user to optimize their rest and recovery based on a user’s measured physiological data, the method comprising:acquiring heart rate data for a user with a hormonal cycle, the data acquired from a wearable physiological monitoring device worn substantially continuously by the user over at least one entire menstrual cycle;identifying the hormonal cycle and a phase within the hormonal cycle for the user based on the physiological data from the wearable physiological monitoring device;identifying a prior sleep history including prior sleep activity automatically detected for the user based on the heart rate data from the wearable physiological monitoring device;identify a circadian cycle for the user based on the heart rate data;determining a current sleep need for the user based on a prior sleep history for the user wherein sleep need is determined as a function calculated from the heart rate data and a strain for the user;calculating a first amount of sleep for the user based on the current sleep need; andcalculating a second amount of sleep to optimize rest and recovery for the user by adjusting the first calculated amount of sleep for the user according to the phase within the hormonal cycle identified based on the heart rate data and the circadian cycle; andpresenting the calculated second amount of sleep for the user in a user interface.

2. The method of claim 1, wherein identifying the hormonal cycle and the phase includes identifying the hormonal cycle and the phase based on heart rate data.

3. The method of claim 2, wherein identifying the phase within the hormonal cycle includes identifying the phase based on a pattern of change in a heart rate variability for the user over a period of the hormonal cycle.

4. The method of any of claims 2 to 3, wherein identifying the phase within the hormonal cycle includes determining a respiratory rate for the user based on a heart rate variability for the user and identifying the phase based on a pattern of change in the respiratory rate.

5. The method of any of claims 1 to 4, wherein identifying the phase within the hormonal cycle includes training a machine learning model to detect the phase within the hormonal cycle based on one or more of a respiratory rate and a resting heart rate for the user.

6. The method of any of claims 1 to 5, wherein identifying the hormonal cycle and the phase includes identifying the hormonal cycle and the phase based on a skin temperature measured for the user with the wearable physiological monitoring device.

7. The method of any of claims 1 to 6, wherein the prior sleep history for the user includes a duration of sleep for a prior sleep event.

8. The method of any of claims 1 to 7, wherein the first recommended time in bed includes a time selected to satisfy the current sleep need based on an historic ratio of time in bed to time asleep for the user.

9. The method of any of claims 1 to 8, wherein the hormonal cycle is a menstrual cycle.

10. The method of claim 9, wherein adjusting the first recommended time in bed includes decreasing the first recommended time in bed during an early follicular phase of the menstrual cycle.

11. The method of any of claims 9 to 10, wherein adjusting the first recommended time in bed includes increasing the first recommended time in bed during a late luteal phase of the menstrual cycle.

12. The method of any of claims 1 to 11, wherein the heart rate data spans at least twentyeight days for the user.

13. The method of any of claims 1 to 12, wherein the heart rate data is captured substantially continuously by the wearable physiological monitoring device.

14. The method of any of claims 1 to 13, further comprising presenting the second recommended time in bed to the user in a user interface.

15. The method of any of claims 14, further comprising transmitting the heart rate data to a server for remote processing and transmitting the second recommended time in bed from the server to a local device for viewing by the user.

16. A system comprising:a wearable physiological monitor including one or more sensors, a first processor configured to substantially continuously acquire physiological data including heart rate data for a user based on a signal from the one or more sensors, and a communications interface for coupling with a remote resource;a server coupled in a communicating relationship with the wearable physiological monitor, the server including a second processor configured by computer executable code to:receive the heart rate data from the wearable physiological monitor worn substantially continuously by the user,identify a circadian cycle for the user based on the heart rate data,identify a prior sleep history including prior sleep activity automatically detected for the user based on the heart rate data from the wearable physiological monitoring device;identify a current sleep cycle for the user based on a prior sleep history for the user, and to generate a recommendation to optimize rest and recovery for the user based on the current sleep cycle and the circadian cycle; anda user interface configured to present the recommendation to the user.

17. The system of claim 16 wherein the server adjusts the recommended time in bed by decreasing the recommended time in bed during an early follicular phase of the menstrual cycle and increasing the recommended time in bed during a late luteal phase of the menstrual cycle.

18. A computer program product comprising computer executable code that, when executing on one or more computing devices, performs the steps of any of method claims 1 to 15.