Intelligent detection of wellness events using mobile device sensors and cloud-based learning systems

A system comprising a processing device and a non-transitory machine-readable storage device storing instructions that are executable by the processing device to cause performance of operations comprising:

• obtaining sensor data generated by a plurality of sensors, wherein one or more sensors of the plurality of sensors are integrated in a mobile device of a user;
• generating, by a machine-learning engine, a predictive model configured to identify a plurality of behavioral trends of the user, wherein the predictive model is generated based on a neural network trained to identify patterns representing user trends in the sensor data;
• generating, using the predictive model and based on communications with the mobile device, an activity profile of the user from the plurality of behavioral trends of the user identified by the predictive model;
• detecting, using the predictive model, an abnormal event involving the user when a parameter value of the activity profile exceeds a threshold value;
• and
• in response to detecting the abnormal event, generating a notification directed to assisting the user with alleviating the abnormal event.

A non-transitory machine-readable storage device storing instructions that are executable by a processing device to cause performance of operations comprising:

• obtaining sensor data generated by a plurality of sensors, wherein one or more sensors of the plurality of sensors are integrated in a mobile device of a user;
• generating, by a machine-learning engine, a predictive model configured to identify a plurality of behavioral trends of the user, wherein the predictive model is generated based on a neural network trained to identify patterns representing user trends in the sensor data;
• generating, using the predictive model and based on communications with the mobile device, an activity profile of the user from the plurality of behavioral trends of the user identified by the predictive model;
• detecting, using the predictive model, an abnormal event involving the user when a parameter value of the activity profile exceeds a threshold value;
• and
• in response to detecting the abnormal event, generating a notification directed to assisting the user with alleviating the abnormal event.