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US 2024/0188896 A1Published application
Dynamic stress scoring with probability distributions
AssigneeWhoop, Inc.
InventorsLaura Ware, Emily Rachel Capodilupo
Life of this patent
Estimating the term…
Abstract
A stress score from a physiological monitor provides a local, objective, quantitative measurement of stress in a numerical form that can be used as the basis for real time coaching, decision-making, and so forth.
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:
- creating a first model, the first model including a machine learning model trained to generate a probability distribution of expected heart rate reserve ratios based on a first set of features of training data for a population of users of a type of physiological monitor;
- receiving user data from a wearer of a first physiological monitor of the type of physiological monitor;
- calculating a heart rate reserve ratio for the wearer based on the user data from the first physiological monitor;
- generating the probability distribution of expected heart rate reserve ratios for the wearer based on the first set of features of the user data;
- and
- calculating a stress score for the wearer based on a comparison of the heart rate reserve ratio to the probability distribution of expected heart rate reserve ratios.
3 more elements
A method comprising:
- creating a first model, the first model including a machine learning model trained to generate a probability distribution for a physiological metric based on a first set of features of training data for a population of users of a type of physiological monitor;
- receiving user data from a wearer of a first physiological monitor of the type of physiological monitor;
- calculating a value for the physiological metric for the wearer based on the user data from the first physiological monitor;
- generating the probability distribution for the physiological metric for the wearer based on the first set of features of the user data;
- and
- calculating a stress score for the wearer based on a comparison of the value for the physiological metric to the probability distribution for the physiological metric.
3 more elements
A system comprising:
- a wearable physiological monitor including one or more sensors and a first processor configured to continuously acquire user data including heart rate data for a wearer based on a signal from the one or more sensors;
- a datastore storing a first model, the first model including a machine learning model trained to generate a probability distribution for a physiological metric based on a first set of features of training data for a population of users of a type of physiological monitor;
- one or more processors coupled in a communicating relationship with the wearable physiological monitor, the one or more processors configured by computer executable code to receive data from the wearable physiological monitor and to perform the steps of:
- receiving the user data from the wearable physiological monitor,
- calculating a value for the physiological metric for the wearer based on the user data from the wearable physiological monitor,
- generating the probability distribution for the physiological metric for the wearer based on the first set of features of the user data, and
- calculating a stress score for the wearer based on a comparison of the value for the physiological metric to the probability distribution for the physiological metric;
- and
- a display device in communication with the one or more processors, the display device including a user interface configured to present a value to the user indicative of the stress score.
6 more elements
Dependencies are inferred from the claim text.