Abstract: Systems and methods are provided for continuously monitoring a user to determine when cardiovascular events are likely occurring and to responsively provide a prompt to a user to engage in additional physiological assessment of the putative cardiovascular event. Additional assessment can include the user engaging an additional sensor to provide signals that are more accurate, lower noise, or otherwise improved relative to a continuously-monitoring sensor used to initially detect the cardiovascular event. Detection of cardiovascular events includes using a cardiovascular classifier to determine, based on the output of such a continuously-monitoring sensor, whether the event is likely occurring. Such a classifier can be received from a cloud computing service or other remote system based on sensor outputs sent to such a system.

Abstract: Systems and methods are provided for continuously monitoring a user to determine when cardiovascular events are likely occurring and to responsively provide a prompt to a user to engage in additional physiological assessment of the putative cardiovascular event. Additional assessment can include the user engaging an additional sensor to provide signals that are more accurate, lower noise, or otherwise improved relative to a continuously-monitoring sensor used to initially detect the cardiovascular event. Detection of cardiovascular events includes using a cardiovascular classifier to determine, based on the output of such a continuously-monitoring sensor, whether the event is likely occurring. Such a classifier can be received from a cloud computing service or other remote system based on sensor outputs sent to such a system.

Abstract: To better understand the impact that meals have on the blood glucose level, some individuals with diabetes have begun recording meals consumed over time. However, the relationship between meals consumed by an individual and the glycemic health state of the individual has been difficult to understand. Introduced here are computer programs and associated computer-implemented techniques for utilizing information regarding the meals consumed by an individual to manage the blood glucose level of the individual in a personalized manner. By consistently and properly attributing physiological responses represented as excursions in blood glucose measurements to meals, the relationship between these meals and the glycemic health state can be better understood. For example, by examining this relationship, a diabetes management platform may be able to identify appropriate recommendations for monitoring, managing, and/or improving the glycemic health state of an individual.

Abstract: Systems and methods are provided for continuously monitoring a user to determine when cardiovascular events are likely occurring and to responsively provide a prompt to a user to engage in additional physiological assessment of the putative cardiovascular event. Additional assessment can include the user engaging an additional sensor to provide signals that are more accurate, lower noise, or otherwise improved relative to a continuously-monitoring sensor used to initially detect the cardiovascular event. Detection of cardiovascular events includes using a cardiovascular classifier to determine, based on the output of such a continuously-monitoring sensor, whether the event is likely occurring. Such a classifier can be received from a cloud computing service or other remote system based on sensor outputs sent to such a system.

Abstract: Systems and methods are provided for continuously monitoring a user to determine when cardiovascular events are likely occurring and to responsively provide a prompt to a user to engage in additional physiological assessment of the putative cardiovascular event. Additional assessment can include the user engaging an additional sensor to provide signals that are more accurate, lower noise, or otherwise improved relative to a continuously-monitoring sensor used to initially detect the cardiovascular event. Detection of cardiovascular events includes using a cardiovascular classifier to determine, based on the output of such a continuously-monitoring sensor, whether the event is likely occurring. Such a classifier can be received from a cloud computing service or other remote system based on sensor outputs sent to such a system.

Abstract: Systems and methods are provided for continuously monitoring a user to determine when cardiovascular events are likely occurring and to responsively provide a prompt to a user to engage in additional physiological assessment of the putative cardiovascular event. Additional assessment can include the user engaging an additional sensor to provide signals that are more accurate, lower noise, or otherwise improved relative to a continuously-monitoring sensor used to initially detect the cardiovascular event. Detection of cardiovascular events includes using a cardiovascular classifier to determine, based on the output of such a continuously-monitoring sensor, whether the event is likely occurring. Such a classifier can be received from a cloud computing service or other remote system based on sensor outputs sent to such a system.

Abstract: A system including two or more wearable devices includes at least one sensor in each device to detect signals related to the body of a wearer. User inputs, sensor outputs, or other information are used to determine an activity being performed or otherwise engaged in by the wearer and footsteps, heartbeats, discrete turns of the torso, or other events can be detected, from one or more of the sensor outputs, during a period of time that the user is engaged in the activity. A duration, amplitude, timing, mean value, or other characteristic of each such detected event can be determined, based on the sensor outputs, and used to generate a sample of clinically relevant information about the wearer. This information can then be used to determine the presence, stage, degree, progression, or other information about a disease state of the wearer or some other information about the wearer's body.