Personalizing application interfaces based on usage

1. A system for personalizing an application, the system comprising:

an application server for hosting an application that is executed on a wireless device; and

a processor coupled to the application server, the processor being configured to perform operations comprising:

transmitting, via the application, a first user interface element to the wireless device, wherein the first user interface element comprises at least one of a prompt, a question, and a menu for an input;

displaying the first user interface element on the wireless device;

monitoring a usage of the first user interface element, wherein the monitoring comprises monitoring an interaction between a user of the application and the first user interface element, and wherein the monitoring further comprises detecting a first input to the prompt, measuring a time of the first input, measuring a length of the first input, determining a type of the first input, or determining that there is no input;

initiating a timer as soon as the first user interface element is displayed;

classifying said user into one or more stages based on a first input provided to the first user interface element and an elapsed time measured by the timer for the first input, wherein the one or more stages are related to at least one of a proficiency level, an interest level, and a behavioral level, and wherein a level of each stage ranges from a minimum value to a maximum value;

determining, using a trained machine learning algorithm, one or more additional user-interface elements, based on both the monitoring and the classifying;

transmitting the one or more additional user-interface elements to the wireless device; and

displaying the one or more additional user interface elements on the wireless device,

wherein the one or more additional user interfaces are dynamically modified via real-time updating of user-interface elements,

wherein the machine learning algorithm is a modified Q-learning algorithm comprising a plurality of Q-value (s, a) state-action pairs, and

wherein a reward for each Q-value (s, a) state-action pair is based on user feedback for choosing action a in state s, and wherein the action corresponds to classifying said user into a stage and the state corresponds to the first user interface element.

2. The system of claim 1 , wherein the type of the first input comprises one or more of a keypress, a button, an alphanumeric string, or a selection from a list.

3. The system of claim 1 , wherein the one or more stages comprise one or more levels on a scale.

4. The system of claim 1 , wherein the one or more additional user-interface elements are determined based on the one or more stages.

5. The system of claim 4 , wherein the stages are arranged in a hierarchical order, and the one or more additional user-interface elements are grouped in a corresponding hierarchical order.

6. The system of claim 4 , wherein the one or more additional user-interface elements comprise one or more of a second prompt, a notifier, a question, or an instruction.

7. The system of claim 1 , wherein the machine learning algorithm is invoked upon a number of inputs meeting a threshold, the threshold including the first input.

8. The system of claim 1 , further comprising a medical device in communication with the wireless device.

9. The system of claim 8 , wherein operations further comprise:

receiving sensor data from a sensor coupled to the medical device; and determining the one or more additional user-interface elements based on a combination of the usage of the application and the sensor data.

10. The system of claim 9 , wherein the operations further comprise transmitting commands to the medical device based on the sensor data and the usage of the application, wherein the commands comprise one or more of a calibration command to calibrate the sensor, a measurement command to the medical device to perform a measurement, an alert command to the medical device to generate an alert, or an action command to administer a treatment.

11. The system of claim 10 , wherein transmitting commands to the medical device is performed by the application server via the wireless device.

12. A method for personalizing an application, the method comprising:

transmitting, by an application server, a first user interface to a wireless device via an application hosted on the application server and executed on the wireless device, wherein the first user interface element comprises at least one of a prompt, a question, and a menu for an input;

displaying the first user interface element on the wireless device;

monitoring, by the application server, a usage of the first user interface, wherein the monitoring comprises monitoring an interaction between a user of the application and the first user interface, and wherein the monitoring further comprises detecting a first input to the prompt, measuring a time of the first input, measuring a length of the first input, determining a type of the first input, or determining that there is no input;

initiating a timer as soon as the first user interface element is displayed;

classifying said user into one or more stages based on input provided to the first user interface element and an elapsed time measured by the timer for the first input, wherein the one or more stages are related to at least one of a proficiency level, an interest level, and a behavioral level, and wherein a level of each stage ranges from a minimum value to a maximum value;

determining, using a trained machine learning algorithm, a second user interface based on both the monitoring and the classifying;

transmitting, by the application server, the second user interface to the wireless device via the application; and

displaying the second user interface on the wireless device,

wherein the second user interface is dynamically modified via real-time updating of user-interface elements,

wherein the machine learning algorithm is a modified Q-learning algorithm comprising a plurality of Q-value (s, a) state-action pairs, and

wherein a reward for each Q-value (s, a) state-action pair is based on user feedback for choosing action a in state s, and wherein the action corresponds to classifying said user into a stage and the state corresponds to the first user interface element.

13. The method of claim 12 , wherein the first user interface comprises a first plurality of user-interface elements, and the second user interface comprises a second plurality of user-interface elements.

14. The method of claim 12 , further comprising determining the second plurality of user-interface elements of the second user interface based in part on the one or more stages.

15. The method of claim 12 , further comprising determining the second plurality of user-interface elements of the second user interface based on a combination of the usage and data received from a sensor in communication with the wireless device.

16. The method of claim 15 , wherein:

the sensor further comprises a medical device,

the data comprises a physiological measurement, and

the method further comprises determining the second plurality of user-interface elements based in part on the physiological measurement.