Cycle-based workout coaching
Physiological parameters such as respiratory rate and/or heart rate variability can be measured over time for a user and correlated to physiological and/or hormonal cycles such as the menstrual cycle. By determining the phase of such a cycle in this manner, an automatic coach for the user can recommend phase-specific adjustments to activities such as sleep and exercise.
1. A computer program product for suggesting adjustments to an exercise regimen based on a menstrual cycle, the computer program product comprising non-transitory computer executable code embodied in a computer readable medium that, when executing on one or more computing devices, performs the steps of:
acquiring heart rate data for a user from a wearable physiological monitoring device worn by the user over one or more menstrual cycles;
identifying a hormonal cycle and a phase within the hormonal cycle for the user based on at least one of a resting heart rate calculated from the heart rate data and a respiratory rate of the user calculated using the heart rate data;
detecting prior sleep activity for the user based on the heart rate data;
determining a current recovery level for the user based on the prior sleep activity for the user;
generating a recommended strain for new training activity by the user based on the current recovery level; and
automatically adjusting a training recommendation for the user by increasing a strain of the training recommendation during an early follicular phase of the menstrual cycle and decreasing the strain of the training recommendation during a late luteal phase of the menstrual cycle.
2. A system comprising:
a wearable physiological monitor including one or more sensors, a first processor configured to continuously acquire heart rate data for a user over one or more menstrual cycles 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, to identify a menstrual cycle and a phase within the menstrual cycle for the user based on the heart rate data, to detect prior sleep activity for the user based on the heart rate data, to determine a current recovery level for the user based on the prior sleep activity for the user, and to adjust a recommended strain for a new activity by the user according to the phase within the menstrual cycle; and
a user interface configured to present the recommended strain to the user.
3. The system of claim 2 , wherein the server adjusts the recommended strain by increasing the recommended strain during an early follicular phase of the menstrual cycle and decreasing the recommended strain during a late luteal phase of the menstrual cycle.
4. A method comprising:
acquiring heart rate data for a user from a wearable physiological monitoring device worn by the user over one or more hormonal cycles;
identifying a hormonal cycle and a phase within the hormonal cycle for the user based on the heart rate data;
identifying a prior sleep activity for the user based on the heart rate data;
determining a current recovery level for the user based on the prior sleep activity for the user;
generating a first recommended strain for new training activity by the user based on the current recovery level; and
determining a second recommended strain for the user by adjusting the first recommended strain according to the phase within the hormonal cycle.
5. The method of claim 4 , 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.
6. The method of claim 4 , wherein identifying the phase within the hormonal cycle includes determining a respiratory rate for the user and identifying the phase based on a pattern of change in the respiratory rate.
7. The method of claim 6 , wherein determining the respiratory rate for the user includes determining the respiratory rate based the heart rate data for the user.
8. The method of claim 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.
9. The method of claim 4 , wherein identifying the hormonal cycle and the phase includes identifying the hormonal cycle and the phase based on user input.
10. The method of claim 4 , 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.
11. The method of claim 4 , wherein the current recovery level is based on one or more of a prior strain, a heart rate variability, a resting heart rate, and a respiratory rate for the user.
12. The method of claim 4 , wherein the prior sleep activity for the user includes a duration of sleep for a prior sleep event.
13. The method of claim 4 , wherein the second recommended strain includes a training recommendation.
14. The method of claim 13 , wherein the training recommendation includes a change in training content that adjusts exercise for the user from the first recommended strain to the second recommended strain.
15. The method of claim 4 , wherein the hormonal cycle is a menstrual cycle.
16. The method of claim 15 , wherein adjusting the first recommended strain includes increasing the second recommended strain during an early follicular phase of the menstrual cycle.
17. The method of claim 15 , wherein adjusting the first recommended strain includes reducing the second recommended strain during a late luteal phase of the menstrual cycle.
18. The method of claim 4 , wherein the heart rate data spans at least twenty-eight days for the user.
19. The method of claim 4 , wherein the heart rate data is captured continuously by the wearable physiological monitoring device.
20. The method of claim 4 , further comprising presenting the second recommended strain to the user in a user interface.