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US 12,758,160 B2Granted
Coaching based on reproductive phases
AssigneeWhoop, Inc.
InventorsEmily Rachel Capodilupo, Summer Rose Jasinski
Life of this patent
Estimating the term…
Abstract
Physiological metrics such as respiratory rate, resting heart rate, heart rate variability, temperature, and the like can be measured over time for a user and correlated to reproductive phases. By determining the chronological phase in a hormonal cycle or the like, automated recommendations for sleep, diet, exercise and the like can be provided in a phase-coordinated manner.
Claims20
A computer program product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:
- providing a model that characterizes timewise changes during a model hormonal cycle for each of a heart rate variability, a resting heart rate, a body temperature, and a respiration rate;
- acquiring physiological data for a user from a wearable monitor, wherein the physiological data includes at least heart rate data and body temperature data, and wherein the physiological data is acquired during a hormonal cycle for the user;
- calculating a number of metrics for the user at least daily during the hormonal cycle, the number of metrics including at least the heart rate variability, the resting heart rate, the body temperature, and the respiration rate;
- calculating an ensemble of estimated cycle times for the user relative to the model hormonal cycle, wherein each estimated cycle time in the ensemble of estimated cycle times is a separate estimate of cycle time based on one of the number of metrics independently;
- calculating a probability of accurately estimating a metric-dependent cycle time for each separate estimate of cycle time for one of the number of metrics;
- calculating a cycle time within the hormonal cycle for the user based on a combination of each separate estimate of cycle time in the ensemble of the estimated cycle times and the probability of each separate estimate of cycle time in the ensemble of cycle times accurately estimating the metric-dependent cycle time for one of the number of metrics;
- and
- providing coaching information to the user based on the cycle time.
5 more elements
A method comprising:
- providing a model that characterizes timewise changes during a model hormonal cycle for each of two or more physiological metrics;
- acquiring heart rate data from a wearable monitor worn by a user;
- calculating the two or more physiological metrics for the user at least daily based on the heart rate data;
- calculating an ensemble of estimated cycle times for the user relative to the model hormonal cycle, wherein each estimated cycle time in the ensemble of estimated cycle times is a separate estimate of cycle time based on one of the two or more physiological metrics independently;
- calculating a probability of accurately estimating a metric-dependent cycle time for each separate estimate of cycle time for one of the two or more physiological metrics;
- calculating a cycle time within a hormonal cycle for the user based on a combination of each separate estimate of cycle times in the ensemble of estimated cycle times and the probability of accurately estimating the metric-dependent cycle time for the each separate estimate of cycle time for one of the two or more physiological metrics, each estimated cycle time in the ensemble derived by applying one of the two or more physiological metrics to the model;
- and
- providing coaching information to the user based on the cycle time.
5 more elements
A system comprising:
- a wearable monitor configured to acquire heart rate data from a user;
- a model stored in a memory, the model characterizing timewise changes during a model hormonal cycle for each of two or more physiological metrics;
- and
- a processor configured to generate a recommendation for the user by performing the steps of:
- receiving the heart rate data from the wearable monitor;
- calculating the two or more physiological metrics for the user on a periodic basis based on the heart rate data;
- calculating an ensemble of estimated cycle times for the user relative to the model hormonal cycle, wherein each estimated cycle time in the ensemble of estimated cycle times is a separate estimate of cycle time based on one of the two or more metrics independently;
- calculating a probability of accurately estimating a metric-dependent cycle time for each separate estimate of cycle time based on one of the two or more physiological metrics;
- calculating a cycle time within a hormonal cycle for the user based on a combination of each separate estimate of cycle time in the ensemble of estimated cycle times and the probability of each separate estimate of cycle time in the ensemble of cycle times accurately estimating the metric-dependent cycle time for each of the two or more physiological metrics, each of the estimated cycle times derived by applying one of the two or more physiological metrics to the model;
- and
- providing coaching information to the user based on the cycle time.
8 more elements
Dependencies are inferred from the claim text.