Assessing cognitive reaction to over-the-air updates

1. A computer-implemented method for determining a cognitive reaction to a software application update, the method comprising:

determining that a software application update is received for a software application executing on a computing device and results in an updated software application;

in response to determining that the software application update has been received, acquiring, via at least one sensor, sensor data associated with a user of the updated software application;

determining, based on the sensor data, at least one of a cognitive workload or an emotional state associated with a user interaction with a feature of the updated software application over a rolling window of time; and

analyzing data over the rolling window of time to determine a change in the at least one of the cognitive workload or the emotional state that occurred after the feature is presented and prior to the user interaction.

2. The computer-implemented method of claim 1 , wherein determining that the software application update has been received comprises determining that an over-the-air update associated with the software application has been installed on the computing device.

3. The computer-implemented method of claim 1 , wherein the sensor data includes at least one image of the user of the software application, and wherein determining the at least one of the cognitive workload or the emotional state comprises analyzing the at least one image of the user of the software application.

4. The computer-implemented method of claim 1 , wherein the sensor data includes at least one of a heartrate, a breathing rate, or a galvanic skin response of the user, and wherein determining the at least one of the cognitive workload or the emotional state comprises analyzing the at least one of the heartrate, the breathing rate, or the galvanic skin response of the user.

5. The computer-implemented method of claim 1 , further comprising:

detecting that a human-machine interface is displaying a graphical element associated with the feature; and

correlating the at least one of the cognitive workload or the emotional state with a time that the graphical element was displayed.

6. The computer-implemented method of claim 1 , further comprising:

detecting that a human-machine interface is displaying a graphical element associated with the feature;

detecting that the user has interacted with the graphical element; and

correlating a time that the graphical element was displayed with a time at which the user interacted with the graphical element.

7. The computer-implemented method of claim 1 , further comprising causing the at least one of the cognitive workload or the emotional state to be transmitted via a telemetrics system via a communications network.

8. The computer-implemented method of claim 1 , wherein the emotional state comprises an emotional arousal level and an emotional valence level.

9. The computer-implemented method of claim 1 , further comprising determining that the user has interacted with one or more features included in the updated software application that are tagged for measurement, wherein acquiring the sensor data occurs in response to determining that the user has interacted with the one or more features.

10. One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to determine a cognitive reaction to a software application update, by performing the steps of:

determining that a software application update is received for a software application executing on a computing device and results in an updated software application;

in response to determining that the software application update has been received, acquiring, via at least one sensor, sensor data associated with a user of the updated software application;

determining, based on the sensor data, at least one of a cognitive workload, an emotional arousal level, or an emotional valence level associated with a user interaction with a feature of the updated software application over a rolling window of time; and

analyzing data over the rolling window of time to determine a change in the at least one of the cognitive workload, the emotional arousal level, or the emotional valence level that occurred after the feature is presented and prior to the user interaction.

11. The one or more non-transitory computer-readable storage media of claim 10 , wherein determining that the software application update has been received comprises determining that an over-the-air update associated with the software application has been installed on the computing device.

12. The one or more non-transitory computer-readable storage media of claim 10 , wherein the sensor data includes at least one image of the user of the software application, and wherein determining the at least one of the cognitive workload, the emotional arousal level, or the emotional valence level comprises analyzing the at least one image of the user of the software application.

13. The one or more non-transitory computer-readable storage media of claim 10 , wherein the sensor data includes at least one of a heartrate, a breathing rate, or a galvanic skin response of the user, and wherein determining the at least one of the cognitive workload, the emotional arousal level, or the emotional valence level comprises analyzing the at least one of the heartrate, the breathing rate, or the galvanic skin response of the user.

14. The one or more non-transitory computer-readable storage media of claim 10 , further comprising:

detecting that a human-machine interface is displaying a graphical element associated with the feature; and

correlating the at least one of the cognitive workload, the emotional arousal level, or the emotional valence level with a time that the graphical element was displayed.

15. The one or more non-transitory computer-readable storage media of claim 10 , wherein the steps further comprise:

detecting that a human-machine interface is displaying a graphical element associated with the feature;

detecting that the user has interacted with the graphical element; and

correlating a time that the graphical element was displayed with a time at which the user interacted with the graphical element.

16. The one or more non-transitory computer-readable storage media of claim 10 , wherein the steps further comprise storing the at least one of the cognitive workload, the emotional arousal level, or the emotional valence level in a memory for subsequent retrieval and analysis.

17. The one or more non-transitory computer-readable storage media of claim 10 , wherein the steps further comprise:

detecting that a human-machine interface is displaying a graphical element associated with the feature;

correlating the emotional valence level with a time that the graphical element was displayed;

detecting that the emotional valence level is associated with a positive emotional state; and

in response, retaining the feature of the updated software application.

18. The one or more non-transitory computer-readable storage media of claim 10 , wherein the steps further comprise:

detecting that a human-machine interface is displaying a graphical element associated with the feature;

correlating the emotional valence level with a time that the graphical element was displayed;

detecting that the emotional valence level is associated with a negative emotional state; and

in response, replacing the feature of the updated software application with a previous version of the feature.

19. A system, comprising:

a driver monitoring system; and

a cognition analysis system coupled to the driver monitoring system and configured to perform the steps of:

determining that a software application update is received for a software application executing on a computing device and results in an updated software application;

in response to determining that the software application update has been received, acquiring, via at least one sensor, sensor data associated with a user of the updated software application;

determining, based on the sensor data, at least one of a cognitive workload or an emotional state associated with a user interaction with a feature of the updated software application over a rolling window of time; and

analyzing data over the rolling window of time to determine a change in the at least one of the cognitive workload or the emotional state that occurred after the feature is presented and prior to the user interaction.

20. The system of claim 19 , wherein determining that the software application update has been received comprises determining that an over-the-air update associated with the software application has been installed on the computing device.