Target-based mouse sensitivity recommendations

1. A computer-implemented method for automatically generating mouse sensitivity recommendations, the method comprising:

generating mouse movement data corresponding to one or more mouse movements performed by a user while interacting with a software application;

generating a predicted efficiency for each mouse sensitivity level included in a plurality of mouse sensitivity levels based on the mouse movement data;

determining a size of at least one target associated with the software application; and

determining one or more mouse sensitivity levels to provide to the user based on the predicted efficiencies and the size of the at least one target.

2. The method of claim 1 , wherein generating the mouse movement data comprises segmenting the one or more mouse movements into a plurality of mouse sub-movements.

3. The method of claim 2 , wherein segmenting the one or more mouse movements into the plurality of mouse sub-movements comprises:

calculating, for each timestamp of a plurality of timestamps included in the mouse movement data, a different mouse movement velocity corresponding to the timestamp; and

segmenting the one or more mouse movements based on the plurality of mouse movement velocities.

4. The method of claim 3 , wherein segmenting the one or more mouse movements is further based on a minimum duration associated with the plurality of mouse sub-movements.

5. The method of claim 1 , further comprising generating accuracy data corresponding to the one or more mouse movements, wherein generating the plurality of predicted efficiencies is further based on the accuracy data.

6. The method of claim 5 , wherein generating the plurality of predicted efficiencies comprises:

generating a first function that indicates a correspondence between a plurality of target distances and a plurality of mouse movement and a second function that indicates a correspondence between a plurality of mouse movement speeds and a plurality of error values based on the mouse movement data and the accuracy data; and

for each mouse sensitivity level included in a plurality of mouse sensitivity levels, predicting a mouse movement time associated with selecting a target using the mouse sensitivity level based on at least one of the first function or the second function.

7. The method of claim 1 , wherein generating the predicted efficiency for each mouse sensitivity level included in the plurality of mouse sensitivity levels is further based on a plurality of target distances associated with the software application.

8. The method of claim 1 , further comprising causing a first mouse sensitivity level that is included in the one or more mouse sensitivity levels and has been selected by the user to be applied to the software application.

9. The method of claim 1 , wherein the software application is a video game.

10. The method of claim 9 , further comprising:

generating second mouse movement data corresponding to one or more second mouse movements performed by the user while interacting with the software application using a first mouse sensitivity level;

generating a second predicted efficiency for each mouse sensitivity level included in the plurality of mouse sensitivity levels based on the second mouse movement data; and

determining one or more second mouse sensitivity levels to provide to the user based on the second predicted efficiencies.

11. One or more non-transitory computer-readable media including instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:

generating mouse movement data corresponding to one or more mouse movements performed by a user while interacting with a software application;

generating a predicted efficiency for each mouse sensitivity level included in a plurality of mouse sensitivity levels based on the mouse movement data;

determining a size of at least one target associated with the software application; and

determining one or more mouse sensitivity levels to provide to the user based on the predicted efficiencies and the size of the at least one target.

12. The one or more non-transitory computer-readable media of claim 11 , wherein generating the mouse movement data comprises segmenting the one or more mouse movements into a plurality of mouse sub-movements.

13. The one or more non-transitory computer-readable media of claim 12 , wherein segmenting the one or more mouse movements into the plurality of mouse sub-movements comprises:

calculating, for each timestamp of a plurality of timestamps included in the mouse movement data, a different mouse movement velocity corresponding to the timestamp; and

segmenting the one or more mouse movements based on the plurality of mouse movement velocities.

14. The one or more non-transitory computer readable media of claim 13 , wherein segmenting the one or more movements based on the plurality of mouse movement velocities comprises selecting a subset of timestamps included in the plurality of timestamps as a set of mouse sub-movement starting timestamps, wherein each timestamp included in the subset of timestamps corresponds to a mouse movement velocity that is higher than a threshold velocity.

15. The one or more non-transitory computer readable media of claim 13 , wherein segmenting the one or more movements based on the plurality of mouse movement velocities comprises selecting a subset of timestamps included in the plurality of timestamps as a set of mouse sub-movement ending timestamps, wherein each timestamp included in the subset of timestamps corresponds to a mouse movement velocity that is lower than a threshold velocity.

16. The one or more non-transitory computer-readable media of claim 11 , further comprising generating accuracy data corresponding to the one or more mouse movements, wherein generating the plurality of predicted efficiencies is further based on the accuracy data.

17. The one or more non-transitory computer-readable media of claim 16 , wherein generating the plurality of predicted efficiencies comprises:

generating a first function that indicates a correspondence between a plurality of target distances and a plurality of mouse movement and a second function that indicates a correspondence between a plurality of mouse movement speeds and a plurality of error values based on the mouse movement data and the accuracy data; and

for each mouse sensitivity level included in a plurality of mouse sensitivity levels, predicting a mouse movement time associated with selecting a target using the mouse sensitivity level based on at least one of the first function or the second function.

18. The one or more non-transitory computer-readable media of claim 11 , further comprising determining a plurality of target distances associated with the software application, and wherein generating the predicted efficiency for each mouse sensitivity level included in the plurality of mouse sensitivity levels is further based on the plurality of target distances.

19. The one or more non-transitory computer-readable media of claim 18 , wherein the software application is a video game, wherein the one or more mouse movements are associated with at least one of a role selected by the user while playing the video game or a character selected by the user while playing the video game, and wherein the size of the at least one target and the plurality of target distances are associated with the at least one of the role selected by the user or the character selected by the user.

20. A system comprising:

one or more memories storing instructions; and

one or more processors that are coupled to the one or more memories and, when executing the instructions, perform the steps of:

generating mouse movement data corresponding to one or more mouse movements performed by a user while playing a video game;

generating a predicted efficiency for each mouse sensitivity level included in a plurality of mouse sensitivity levels based on the mouse movement data;

determining a size of at least one target associated with the software application; and

selecting one or more mouse sensitivity levels for the user based on the predicted efficiencies and the size of the at least one target.