Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.

Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.

Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.

Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.

Abstract: The present application is directed towards methods and systems for an interactive cyclist monitoring and crash prevention system. The methods include creating, by a safety sensor, a virtual smart lane around a bike operated by a rider during a cycling session. The virtual smart lane may indicates a safe zone around the bike. The method further includes the safety sensor detecting an object approaching the virtual smart lane during the cycling session and generating an alert to the rider of the bike to notify the rider of the approaching object.

Abstract: The present application is directed towards methods and systems for an add-on smart pedal and computer based application to provide cyclist monitoring and recommendations. The methods include displaying, by a virtual coach, characteristics of a bike in a first virtual cycling session, the characteristics measured by a pedal sensor during a cycling session. The virtual coach may assess a performance of a rider during the cycling session and generate recommendations the first virtual cycling session based on the performance of the rider. Further, the virtual coach may create a second virtual cycling session based on the rider performance and the recommendations.

Abstract: According to an aspect of the invention, a robotic ankle and balance training platform comprises a footplate to support a foot. The footplate is capable of rotation about an inversion/eversion axis and a plantar/dorsiflexion axis. The robotic platform further comprises an actuation system configured to apply an assistive inversion/eversion force and a resistive inversion/eversion force to the footplate and an assistive plantar/dorsiflexion force and a resistive plantar/dorsiflexion force to the footplate.