Measuring stress levels and using machine learning techniques to predict high risk behavior

A system comprising one or more processors and one of more non-transitory computer-readable media comprising computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising:

• detecting a first cortisol level of a user from one or more sensors worn by the user, wherein the first cortisol level is detected prior to an activity;
• predicting, using a machine learning (ML) model, a level of risk for the user performing the activity prior to the activity based at least on the first cortisol level of the user;
• transmitting a first notification prior to the activity, wherein the first notification provides the user with instructions for a remediating action based at least on the level of risk for the user performing the activity;
• and
• after transmitting the first notification:
• tracking a behavior of the user during the activity using the one or more sensors;
• detecting a second cortisol level of the user from the one or more sensors worn by the user during the activity;
• adjusting, via the ML model, the level of risk for the user performing the activity based at least on the second cortisol level of the user and the behavior of the user during the activity;
• determining a new remediating action based at least on the level of risk, as adjusted;
• and
• transmitting a second notification to the user, wherein the second notification comprises an alert to display to the user a recommendation for the new remediating action.

One of more non-transitory computer-readable media comprising computing instructions that, when executed on one or more processors, cause the one or more processors to perform operations comprising:

• detecting a first cortisol level of a user from one or more sensors worn by the user, wherein the first cortisol level is detected prior to an activity;
• predicting, using a machine learning (ML) model, a level of risk for the user performing the activity prior to the activity based at least on the first cortisol level of the user;
• transmitting a first notification prior to the activity, wherein the first notification provides the user with instructions for a remediating action based at least on the level of risk for the user performing the activity;
• and
• after transmitting the first notification:
• tracking a behavior of the user during the activity using the one or more sensors;
• detecting a second cortisol level of the user from the one or more sensors worn by the user during the activity;
• adjusting, via the ML model, the level of risk for the user performing the activity based at least on the second cortisol level of the user and the behavior of the user during the activity;
• determining a new remediating action based at least on the level of risk, as adjusted;
• and
• transmitting a second notification to the user, wherein the second notification comprises an alert to display to the user a recommendation for the new remediating action.