Sensorimotor assessment and training
Disclosed herein are system, method, and computer program product embodiments for assessing performance of a player of a game. An embodiment operates by monitoring for an input from the player of the game, receiving the input from the player of the game, and determining a characteristic of the game resulting from the input from the player. Based on the input from the player, a performance of the player is assessed. The performance of the player relating to one or more metrics of the game is monitored, and is assessed by comparing the input from the player during the period of time to an optimal input during the period of time in the game.
1. A computer-implemented method for sensorimotor training used by a player of a game, the method comprising:
monitoring, by at least one computer processor, inputs in a game by a player using a computer input device, the inputs comprising movements and shots;
determining a metric of the inputs, wherein the metric comprises at least one of: a distance between a projectile and a center of a target; and a distance between a movement and the center of a target; and
adjusting, by the at least one processor, a relationship between an input received via the computer input device and the movement of a virtual object within the virtual environment of the game based on the metric to train the player to adjust the player's movements of the input device.
2. The method of claim 1 , wherein the computer input device comprises a device selected from the group consisting of: a mouse; a joystick; an accelerometer; a pointing device; a motion capture device; a Wii remote controller; an eye tracker; and a computer vision system.
3. The method of claim 1 , wherein the relationship is the sensitivity of the computer input device.
4. The method of claim 1 , comprising setting the sensitivity of the computer input device.
5. The method of claim 1 , wherein the metric comprises the distance between a movement and the center of a target, and the metric is computed based on a statistical analysis of the movement error for a plurality of movements.
6. The method of claim 1 , wherein determining the metric comprises fitting a statistical model to a distribution of errors.
7. The method of claim 1 , wherein the metric comprises at least one of the group consisting of: precision, variability and accuracy.
8. The method of claim 1 , wherein the metric is a performance metric of movement trajectories.
9. A device for sensorimotor training used by a player of a game, the device comprising:
a memory; and
a processor to:
monitor inputs in a game by a player using a computer input device, the inputs comprising movements and shots;
determine a metric of the inputs, wherein the metric comprises at least one of: a distance between a projectile and a center of a target; and a distance between a movement and the center of a target; and
adjust a relationship between an input received via the computer input device and the movement of a virtual object within the virtual environment of the game based on the metric to train the player to adjust the player's movements of the input device.
10. The device of claim 9 , wherein the computer input device comprises a device selected from the group consisting of: a mouse; a joystick; an accelerometer; a pointing device; a motion capture device; a Wii remote controller; an eye tracker; and a computer vision system.
11. The device of claim 9 , wherein the relationship is the sensitivity of the computer input device.
12. The device of claim 9 , wherein the processor is to set the sensitivity of the computer input device.
13. The device of claim 9 , wherein the metric comprises the distance between a movement and the center of a target, and the metric is computed based on a statistical analysis of the movement error for a plurality of movements.
14. The device of claim 9 , wherein determining the metric comprises fitting a statistical model to a distribution of errors.
15. The device of claim 9 , wherein the metric comprises at least one of the group consisting of: precision, variability and accuracy.
16. A computer-implemented method for sensorimotor training in a virtual environment, the method comprising, using a computer processor:
determining a metric of inputs to the virtual environment by a user using a computer input device, wherein the metric comprises at least one of: a distance between a projectile and a center of a target; and a distance between a movement and the center of a target; and
adjusting, by the at least one processor, a mapping between an input received via the computer input device and movement within the virtual environment based on the metric to train a player to adjust the player's movements of the computer input device.
17. The method of claim 16 , wherein the computer input device comprises a device selected from the group consisting of: a mouse; a joystick; an accelerometer; a pointing device; a motion capture device; a Wii remote controller; an eye tracker; and a computer vision system.
18. The method of claim 16 , comprising setting the sensitivity of the computer input device.
19. The method of claim 16 , wherein the metric comprises the distance between a movement and the center of a target, and the metric is computed based on a statistical analysis of the movement error for a plurality of inputs.
20. The method of claim 16 , wherein determining the metric comprises fitting a statistical model to a distribution of errors.
21. The method of claim 16 , wherein the metric comprises at least one of the group consisting of: precision, variability and accuracy.