Abstract: Physiological variables, metrics, biomarkers, and other data points can be used, in connection with a non-invasive wearable device, to screen for, and predict, mental health issues and cognitive states. In addition to metrics such as heart rate, sleep data, activity level, gamification data, and the like, information such as text message and email data, as well as vocal data obtained through a phone and/or a microphone, may be analyzed, provided user authorization. Applying predictive modeling, one or more of the monitored metrics can be correlated with mental states and disorders. Identified patterns can be used to update the predictive models, such as via machine learning-trained models, as well as to update individual event predictions. Information about the mental state predictions, and updates thereto, can be surfaced to the user accordingly.

Abstract: Physiological variables, metrics, biomarkers, and other data points can be used, in connection with a non-invasive wearable device, to screen for, and predict, mental health issues and cognitive states. In addition to metrics such as heart rate, sleep data, activity level, gamification data, and the like, information such as text message and email data, as well as vocal data obtained through a phone and/or a microphone, may be analyzed, provided user authorization. Applying predictive modeling, one or more of the monitored metrics can be correlated with mental states and disorders. Identified patterns can be used to update the predictive models, such as via machine learning-trained models, as well as to update individual event predictions. Information about the mental state predictions, and updates thereto, can be surfaced to the user accordingly.

Abstract: Various types of data can be collected regarding the physical or mental health of a user, as may relate to sleep of the user over a period of time. Health metrics can be determined from this data that can enable the user to be associated with a particular health type or category. For sleep, this can include associating the user with a sleep animal that has specific characteristics. This can help a user to better understand that user's sleep, and how that sleep compares to sleep of others. In addition to being able to provide health information in a way that is easy to understand, such an approach can also help to make more accurate recommendations or take specific actions to help improve the health of a user, such as to improve sleep. This can include making recommendations to a user or automatically adjusting operation of at least one device.