CYCLE-BASED 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 - 20 . (canceled)
21 . A computer program product for suggesting adjustments to a sleep regimen based on a circadian 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;
identifying a circadian cycle for the user based on the heart rate data;
identifying a current sleep cycle for the user based on a prior sleep history for the user determined from the heart rate data; and
generating a recommendation for the user for adjusting a timing of the circadian cycle based on the current sleep cycle and the circadian cycle.
22 . A system comprising:
a wearable physiological monitor including one or more sensors, a first processor configured to substantially continuously acquire 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, to identify a circadian cycle for the user based on the heart rate data, to identify a current sleep cycle for the user based on a prior sleep history for the user, and to generate a recommendation for the user for adjusting a timing of the circadian cycle based on the current sleep cycle and the circadian cycle; and
a user interface configured to present the recommendation to the user.
23 . The system of claim 22 , wherein the recommendation is a recommended time to fall asleep or wake up.
24 . A method comprising:
acquiring heart rate data for a user from a wearable physiological monitoring device;
identifying a circadian cycle for the user;
identifying a current sleep cycle for the user based on one or both of a prior sleep history for the user or the heart rate data; and
generating a recommendation for the user for adjusting a timing of the circadian cycle based on the current sleep cycle and the circadian cycle.
25 . The method of claim 24 , wherein identifying the circadian cycle includes identifying the circadian cycle based on the heart rate data.
26 . The method of claim 25 , wherein identifying the circadian cycle includes identifying the circadian cycle based on a pattern of change in a heart rate variability for the user over a period of the circadian cycle.
27 . The method of claim 24 , wherein identifying the circadian cycle includes determining a respiratory rate for the user based on a heart rate variability for the user and identifying the circadian cycle based on a pattern of change in the respiratory rate.
28 . The method of claim 24 , wherein identifying the circadian cycle includes training a machine learning model to detect a phase within the circadian cycle based on one or more of a respiratory rate and a resting heart rate for the user.
29 . The method of claim 24 , wherein identifying the circadian cycle includes identifying the circadian cycle based on user input.
30 . The method of claim 24 , wherein identifying the circadian cycle includes identifying the circadian cycle based on a skin temperature measured for the user with the wearable physiological monitoring device.
31 . The method of claim 24 , wherein the sleep cycle for the user includes information related to a duration of sleep for a prior sleep event.
32 . The method of claim 24 , wherein the heart rate data spans at least 24 hours for the user.
33 . The method of claim 24 , wherein the heart rate data is captured substantially continuously by the wearable physiological monitoring device.
34 . The method of claim 24 , further comprising presenting the recommendation to the user in a user interface.
35 . The method of claim 24 , further comprising transmitting the heart rate data to a server for remote processing and transmitting the recommendation from the server to a local device for viewing by the user.
36 . A method comprising:
acquiring heart rate data for a user from a wearable physiological monitoring device;
identifying a circadian cycle for the user based on the heart rate data;
identifying information related to a sleep cycle for the user based on the heart rate data; and
generating a recommendation for the user for adjusting a timing of the circadian cycle.
37 . The method of claim 36 , wherein the recommendation is for the user to fall asleep earlier or later than a prior time associated with the sleep cycle when the user fell asleep.
38 . The method of claim 36 , wherein the recommendation is for the user to wake up earlier or later than a prior time associated with the sleep cycle when the user woke up.
39 . The method of claim 36 , wherein the recommendation is for the user to be exposed to light within a particular amount of time after waking.
40 . The method of claim 36 , wherein the recommendation is for the user to consume caffeine only within a particular amount of time after waking.