Human interface devices with lighting modes
Changing a lighting mode for a human interface device is described herein. A first lighting mode can be initiated for a human interface device. Keys on the human interface device can be selected over a period of time at a frequency that is within a defined range. A second lighting mode for the human interface device can be identified based in part on the frequency being within the defined range. The first lighting mode and the second lighting mode can define a lighting scheme for light sources in the human interface device that reflect a user mood. The first lighting mode can be switched to the second lighting mode.
1. A non-transitory machine-readable storage medium comprising instructions that, when executed by a processor, cause the processor to:
initiate a first lighting mode for a human interface device;
determine that keys on the human interface device are selected over a period of time at a frequency that is within a first defined range;
provide the frequency of the keys being selected over the period of time to a machine learning model;
identify, using the machine learning model, a second lighting mode for the human interface device based in part on the frequency being within the first defined range, wherein the first lighting mode and the second lighting mode define a lighting scheme for light sources in the human interface device that reflect a user mood; and
switch from the first lighting mode to the second lighting mode,
wherein the first defined range is predetermined, and
wherein a plurality of predetermined ranges are each related to a distinct lighting mode,
such that the first defined range correlates to the second lighting mode and a second
defined range, distinct from the first defined range, correlates to the first lighting mode.
2. The non-transitory machine readable storage medium of claim 1 , wherein the lighting scheme defines colors, animations, patterns, intensity levels, or combinations thereof for the light sources in the human interface device.
3. The non-transitory machine readable storage medium of claim 1 , comprising instructions that, when executed by the processor, cause the processor to:
further provide an application type to the machine learning model, wherein the application type corresponds to an application that is executing on a compute device that receives input from the human interface device; and
identify, based on the machine learning model, the second lighting mode.
4. The non-transitory machine readable storage medium of claim 1 , wherein the keys are included in a predefined set of keys.
5. The non-transitory machine readable storage medium of claim 1 , comprising instructions that, when executed by the processor, cause the processor to: switch from the first lighting mode to the second lighting mode while a gaming application executes on a compute device that receives input from the human interface device.
6. The non-transitory machine readable storage medium of claim 1 , comprising instructions that, when executed by the processor, cause the processor to: initiate the first lighting mode while a non-gaming application executes on a compute device that receives input from the human interface device.
7. The non-transitory machine readable storage medium of claim 1 , wherein the first lighting mode is a calm lighting mode that reflects the user mood.
8. The non-transitory machine readable storage medium of claim 1 , wherein the first lighting mode is an excited lighting mode that reflects the user mood.
9. The non-transitory machine readable storage medium of claim 1 , comprising instructions that, when executed by the processor, cause the processor to: switch from the second lighting mode back to the first lighting mode when the frequency of the keys being selected over the period of time moves outside the first defined range and within the second defined range.
10. The non-transitory machine readable storage medium of claim 1 , wherein the human interface device is a computer keyboard.
11. A computing system, comprising:
a computer keyboard that comprises keys and light sources; and
a compute device to receive input from the computer keyboard, the compute device comprising a processor to:
initiate a first lighting mode for the computer keyboard, wherein the first lighting mode defines a first configuration for the light sources in the computer keyboard, and the first lighting mode reflects a first user mood;
monitor the keys of the human interface device to determine the keys being selected over a period of time, wherein the keys monitored over the period of time are included in a predefined set of keys;
determine that a frequency of the keys being selected over the period of time is within a first defined range;
identify, using a machine learning model, a second lighting mode for the computer keyboard based in part on the frequency being within the first defined range, wherein the second lighting mode defines a second configuration for the light sources in the computer keyboard, and the second lighting mode reflects a second user mood; and
switch from the first lighting mode to the second lighting mode,
wherein the first defined range is predetermined, and
wherein a plurality of predetermined ranges are each related to a distinct lighting mode,
such that the first defined range correlates to the second lighting mode and a second
defined range, distinct from the first defined range, correlates to the first lighting mode.
12. The computing system of claim 11 , wherein the first lighting mode and the second lighting mode define a lighting scheme for the computer keyboard, wherein the lighting scheme defines colors, animations, patterns, intensity levels, or combinations thereof for the light sources of the human interface device.
13. The computing system of claim 11 , wherein the compute device includes additional light sources, wherein the first lighting mode and the second lighting mode define a lighting scheme for the additional light sources of compute device.
14. A method of changing a lighting mode for a computer keyboard, comprising:
initiating a first lighting mode for the computer keyboard, wherein the first lighting mode is a default lighting mode;
monitoring keys being selected on the computer keyboard over a period of time, wherein the keys monitored over the period of time are included in a predefined set of keys;
determining that a frequency of the keys being selected over the period of time is within a defined range;
identifying, using a machine learning model, a second lighting mode for the computer keyboard based in part on the frequency being within the defined range, wherein the second lighting mode reflects a user mood;
switching from the first lighting mode to the second lighting mode;
determining that the frequency of the keys being selected over a subsequent period of time moves outside the defined threshold; and
reverting back to the first lighting mode.
15. The method of claim 14 , wherein the first lighting mode and the second lighting mode define a lighting scheme for the computer keyboard, wherein the lighting scheme defines colors, animations, patterns, intensity levels, or combinations thereof for light sources of the computer keyboard.
16. The method of claim 14 ,
wherein the defined range is predetermined, and
wherein a plurality of predetermined ranges are each related to a distinct lighting mode.