Human interface device with illumination pattern

Abstract

Changing lighting modes of a human-machine interface device is described herein. A first lighting mode can be initiated for a human-machine interface device. Keys on the human-machine interface device can be selected with a frequency within a defined range for a period of time. A second lighting mode of the human-machine 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 lighting schemes for light sources in the human-machine interface device that reflect user emotions. The first lighting mode can be switched to the second lighting mode.

Description

BACKGROUND

[0001] A human interface device, such as a computer keyboard, can provide received input to a computing device. A computer keyboard can include an arrangement of buttons or keys that can be pressed to produce letters, numbers, or symbols (characters). A computer keyboard can be illuminated so that the buttons or keys can be illuminated from behind to facilitate use of the keyboard in dark environments. BRIEF DESCRIPTION OF DRAWINGS

[0002] Figure 1 FIGURE illustrates an example of a computing system including a computing device and a human interface device according to this disclosure;

[0003] Figure 2 FIGURE illustrates an example of a machine learning model that outputs an illumination pattern based on received input according to this disclosure;

[0004] Figure 3 FIGURE illustrates an example of a predefined set of keys on a keyboard according to this disclosure;

[0005] Figure 4 FIGURE illustrates an example of a timeline for changing between illumination patterns of a human interface device according to this disclosure;

[0006] Figure 5 is a flowchart illustrating an example method of changing an illumination pattern of a human interface device according to this disclosure;

[0007] Figure 6 is a flowchart illustrating an example method of changing an illumination pattern of a computer keyboard according to this disclosure; and

[0008] Figure 7 is a block diagram providing an example illustration of a computing device that can be employed in this disclosure. DETAILED DESCRIPTION

[0009] A human interface device, such as a keyboard, can feature different illumination patterns. In one example, a user can open a command interface to manually switch the illumination pattern of the human interface device. For example, a computing device can include a display to show a command interface that can allow a user to manually switch the illumination pattern. However, with this approach, the user would minimize or close the application that is currently being executed in order to open the command interface and change the illumination pattern. In the case of this disclosure, the illumination pattern can be automatically switched while an application is being executed on a computing device based on various factors, such as the frequency of keys or buttons on the human interface device being pressed or selected, the type of application being executed on the computing device, user actions performed using the computing device, and the like.

[0010] The present disclosure describes a non-transitory machine-readable storage medium, and systems and methods related to a human-machine interface device with lighting modes. Examples of the present disclosure can include a non-transitory machine-readable storage medium comprising instructions that, when executed by a processor, can cause the processor to initiate a first lighting mode of a human-machine interface device. The instructions, when executed by the processor, can cause the processor to determine that a key on the human-machine interface device is selected at a frequency within a defined range for a time period. The instructions, when executed by the processor, can cause the processor to identify a second lighting mode of the human-machine interface device 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 a light source in the human-machine interface device that reflects a user emotion. The instructions, when executed by the processor, can cause the processor to switch from the first lighting mode to the second lighting mode.

[0011] In one example, the lighting scheme can define a color, animation, pattern, intensity level, or a combination thereof for the light source in the human-machine interface device. In another example, the non-transitory machine-readable storage medium can include instructions that, when executed by the processor, cause the processor to provide the frequency at which the key is selected for the time period to a machine learning model; provide an application type to the machine learning model, where the application type corresponds to an application executing on a computing device that receives input from the human-machine interface device; and identify the second lighting mode based on the machine learning model.

[0012] In one example, the key can be included in a predefined set of keys. In another example, the non-transitory machine-readable storage medium can include instructions that, when executed by the processor, cause the processor to switch from the first lighting mode to the second lighting mode when a gaming application is executing on a computing device that receives input from the human-machine interface device. In yet another example, the non-transitory machine-readable storage medium can include instructions that, when executed by the processor, cause the processor to initiate the first lighting mode when a non-gaming application is executing on a computing device that receives input from the human-machine interface device.

[0013] In one example, the first lighting mode can be a calm lighting mode that reflects a user emotion. In another example, the first lighting mode can be an excited lighting mode that reflects a user emotion. In yet another example, the non-transitory machine-readable storage medium can include instructions that, when executed by the processor, cause the processor to switch back to the first lighting mode from the second lighting mode when the frequency at which the key is selected for the time period moves outside of a defined threshold. In another example, the human-machine interface device can be a computer keyboard.

[0014] Another example of the present disclosure can include a computing system. The computing system can include a computer keyboard comprising keys and light sources. The computing system can include a computing device to receive input from the computer keyboard. The computing device can include a processor to initiate a first lighting mode of the computer keyboard, where the first lighting mode can define a first configuration of the light sources in the computer keyboard, and the first lighting mode can reflect a first user emotion. The processor can monitor the keys of the human interface device to determine that the keys are selected over a time period, where the keys monitored over the time period can be included in a predefined set of keys. The processor can determine that a frequency that the keys are selected over the time period is within a defined range. The processor can identify a second lighting mode of the computer keyboard based in part on the frequency being within the defined range, where the second lighting mode can define a second configuration of the light sources in the computer keyboard, and the second lighting mode can reflect a second user emotion. The processor can switch from the first lighting mode to the second lighting mode.

[0015] In one example, the first lighting mode and the second lighting mode can define a lighting scheme of the computer keyboard, where the lighting scheme can define a color, animation, pattern, intensity level, or a combination thereof for the light sources of the human interface device. In another example, the computing device can include additional light sources, where the first lighting mode and the second lighting mode define a lighting scheme of the additional light sources of the computing device.

[0016] Another example of the present disclosure can be a method of changing a lighting mode of a computer keyboard. The method can include initiating a first lighting mode of the computer keyboard, where the first lighting mode can reflect a first user emotion. The method can include monitoring keys selected on the computer keyboard over a time period, where the keys monitored over the time period can be included in a predefined set of keys. The method can include determining that a frequency that the keys are selected over the time period is within a defined range. The method can include identifying a second lighting mode of the computer keyboard based in part on the frequency being within the defined range using a machine learning model, where the second lighting mode can reflect a second user emotion. The method can include switching from the first lighting mode to the second lighting mode. The method can include determining that the frequency that the keys are selected over a subsequent time period moves outside of a defined threshold. The method can include reverting back to the first lighting mode.

[0017] In these examples, it is noted that when discussing a storage medium, method, or system, any such discussion can be considered to apply to the other examples, whether or not they are explicitly discussed in the context of that example. Thus, for example, when discussing details of an audio signal in the context of a storage medium, such discussion also relates to the methods and systems described herein, and vice versa.

[0018] Turning now to FIG. Figure 1 An example of a computing system 100 including a computing device 110 and a human interface device 150 is illustrated. The computing device 110 can implement different lighting modes 132 of the human interface device 150, which can correspond to different lighting schemes or lighting configurations of light sources 154 in the human interface device 150. The lighting mode(s) 132 can correspond to an emotion of a user using the computing device 110 and / or the human interface device 150. As discussed in further detail below, the lighting mode 132 can be identified based on a particular key 152 (or button) that is pressed on the human interface device 150 at a given frequency, as well as additional factors such as a type of application 140 executing on the computing device 110 (e.g., a game application, a word processing application), a user action performed on the computing device 110, and the like.

[0019] In one example, the human interface device 150 can be a type of computer device that takes input from a human and / or provides output to a human. The human interface device 150 that is capable of receiving input can include, but is not limited to, a computer keyboard, a computer mouse, or a game controller that includes light sources 154 at various locations within the human interface device 150.

[0020] In one example, the light sources 154 can be positioned at different locations in the human interface device 150. For example, the light sources 154 can be behind the keys 152 to illuminate the keys 152, which is useful when using the human interface device 150 in a dark room or environment. As another example, the light sources 154 can be integrated with a housing or exterior of the human interface device 150 such that the light sources 154 are visible to a user using the human interface device 150.

[0021] In one example, the light source(s) 154 can implement various lighting technologies suitable for inclusion in the human interface device 150. For example, the light source(s) 154 can be light emitting diodes (LEDs), organic LEDs, polymer LEDs, active matrix organic light emitting diodes (AMOLEDs), light emitting electrochemical cells, electroluminescent wires, etc. In another example, the light source(s) 154 can include fluorescent lamps, neon lamps, plasma lamps, xenon flash lamps, etc. Moreover, the light source(s) 154 can be capable of producing various colors (e.g., red, green, blue, orange, yellow, black, white, purple) at various intensity levels.

[0022] In one example, the computing device 110 can include a non-transitory machine- readable storage medium 370 to store the defined illumination pattern(s) 132 and associated user emotion 134. The illumination pattern 132 can define an illumination scheme for the light source 154 in the human interface device 150 that reflects the user emotion 134. The illumination scheme can define colors, animations, patterns, intensity levels (e.g., bright versus dim), etc. for the light source 154 in the human interface device 150. For example, a defined illumination pattern 132 can be associated with defined color(s), defined intensity level(s), defined animation(s) or pattern(s), etc., and the defined illumination pattern 132 can be associated with a particular user emotion 134, such as calm, excited, angry, sad, humorous, romantic, happy, etc.

[0023] In one example, the illumination pattern 132 can include a default illumination pattern for the human interface device 150. The default illumination pattern can be associated with defined color(s), defined intensity level(s), etc. that correspond to default illumination settings for the human interface device 150. The default illumination pattern can be associated with a default user emotion or no user emotion.

[0024] As a non-limiting example, a sad or calm illumination pattern can be associated with a gray or blue light color, no animation, a relatively low light intensity, etc. As another non-limiting example, a happy or excited illumination pattern can be associated with a bright color, an upbeat animation including flashing lights, a high light intensity, etc. As yet another non-limiting example, a romantic illumination pattern can be associated with a red or pink light color, no animation, a relatively low light intensity, etc. As another non-limiting example, a default illumination pattern can be associated with a white light, no animation, a reduced light intensity, etc., or alternatively, the default illumination pattern can correspond to no illumination.

[0025] In alternative examples, the defined lighting modes 132 can be associated with an application 140 or a type of application 140 executing on the computing device 110. In other words, different lighting modes 132 can be initiated depending on the application 140 and / or the type of application 140 executing on the computing device 110. Non-limiting examples of applications 140 can include gaming applications, word processing applications, video applications, photo editing applications, social networking applications, and the like.

[0026] As a non-limiting example, a first lighting mode having a first lighting scheme can correspond to a gaming application and / or a type of gaming application. In this example, the first lighting mode can have predefined colors, intensity levels, and the like that are customized for gaming applications and / or the type of gaming application. As another non-limiting example, a second lighting mode having a second lighting scheme can correspond to a word processing application. In this example, the second lighting mode can have predefined colors, intensity levels, and the like that are customized for word processing applications. As yet another example, a third lighting mode having a third lighting scheme can correspond to a video application for viewing videos. In this example, the third lighting mode can have predefined colors, intensity levels, and the like that are customized for video applications.

[0027] In one configuration, the computing device 110 can include a default lighting mode module 112 that can initiate a default lighting mode. For example, the default lighting mode module 112 can initiate the default lighting mode when the computing device 110 and / or the human-machine interface device 150 is started / powered on or after the human-machine interface device 150 has not been used for a period of time. In one example, the default lighting mode can be used prior to executing a certain application 140 on the computing device 110, such as a gaming application, a word processing application, a media application, and the like.

[0028] In one configuration, the computing device 110 can include a key selection monitoring module 114 to monitor keys 152 that are pressed or selected on the human-machine interface device 150 for a period of time. In one example, the key selection monitoring module 114 can monitor keys 152 that are included in a predefined key set(s) 136, which can be stored in the non-transitory machine-readable storage medium 130. The predefined key set 136 can indicate a group of keys 152 of particular interest and can indicate a user emotion. In other words, in one configuration, the key selection monitoring module 114 can detect when keys 152 that are included in the predefined key set 136 are pressed or selected and can not detect when keys 152 that are not included in the predefined key set 136 are pressed or selected.

[0029] In one example, the key(s) 152 on the human interface device 150 can represent letters (e.g., A, B, C), numbers (e.g., 1, 2, 3), symbols (e.g.,!, @, #), functions (e.g., F1, Backspace, Shift), and the like.

[0030] As a non-limiting example, the first predefined set of keys can include "Q," "W," "E," "R," "A," "S," "D," "F," and "space bar." The first predefined set of keys can correspond to keys 152 that are typically pressed or selected when a user is playing a game application. As another non-limiting example, the second predefined set of keys can include "space bar," "enter," "up arrow," "down arrow," "M," "F," "left arrow," and "right arrow." The second predefined set of keys can correspond to keys 152 that are typically pressed or selected when a user is watching a video on a video application.

[0031] In one example, the key selection monitoring module 114 can determine a key frequency 115 (or rate) at which keys 152 included in the predefined set of keys 136 are pressed or selected over the time period. For example, the key selection monitoring module 114 can determine a key frequency 115 at which keys 152 included in the predefined set of keys 136 are pressed or selected over a 15 second, 30 second, 1 minute, 2 minute, 3 minute, 5 minute, and the like, time period.

[0032] In one configuration, the computing device 110 can include an illumination mode determination module 116 to determine an illumination mode 132 of the human interface device 150 based in part on a key frequency 115 at which keys 152 included in the predefined set of keys 136 are pressed or selected over the time period. In one example, the illumination mode determination module 116 can compare the key frequency 115 to frequency range(s) 138 (or frequency threshold(s)) stored in the non-transitory machine-readable storage medium 130. The frequency ranges 138 can be associated with illumination modes 132. For example, a first frequency range can be associated with a first illumination mode, a second frequency range can be associated with a second illumination mode, and so on. The illumination mode determination module 116 can compare the key frequency 115 to the frequency ranges 138 to identify a frequency range 138 in which the key frequency 115 is included. Based on the identified frequency range 138, the illumination mode determination module 116 can determine an illumination mode 132 associated with the frequency range 138. Thus, based on the key frequency 115 compared to the frequency ranges 138, the illumination mode determination module 116 can determine an illumination mode 132 of the human interface device 150 that is most relevant or most applicable to the user's current activity on the computing device 110.

[0033] In one example, the lighting mode determination module 116 can determine the user emotion 134 based in part on the key frequency 115 of the keys 152 included in the predefined key set 136 being pressed or selected within the time period. For example, certain frequency ranges 138 can be associated with particular user emotions 134. After determining the user emotion 134, the lighting mode determination module 116 can determine the lighting mode 132 corresponding to the user emotion 134.

[0034] As a non-limiting example, a first frequency range between 0-15 key presses / selections per minute can be associated with a calm lighting mode, a second frequency range between 30-60 key presses / selections per minute can be associated with a focused lighting mode, and a third frequency range between 90-120 key presses / selections per minute can be associated with an excited lighting mode. In this non-limiting example, the lighting mode determination module 116 can determine that the frequency of the keys 152 included in the predefined key set 136 being pressed or selected within a one minute time period is 50 key presses / selections per minute. Accordingly, the lighting mode determination module 116 can determine that the focused lighting mode is to be applied or implemented using the light source 154, the human interface device 150.

[0035] In one configuration, the lighting mode determination module 116 can use a machine learning model 118 to determine the lighting mode 132. For example, the key frequency 115 of the keys 152 included in the predefined key set 136 being pressed or selected within the time period can be provided to the machine learning model 118. Based on the received input of the key frequency 115, the machine learning model 118 can produce an output of the lighting mode 132. In addition, the machine learning model 118 can use additional factors to determine the lighting mode 132, such as the type of application 140 being executed on the computing device 110 (e.g., a gaming application, a word processing application), user actions being performed on the computing device 110 (e.g., accessing an electronic web page, listening to music, electronic chatting), and the like. In other words, the key frequency 115, the type of application 140, user actions, and other information can be provided to the machine learning model 118, and the lighting mode determination module 116 can use the machine learning model 118 to determine the lighting mode 132 of the human interface device 150 that is most relevant or most applicable to the user’s current activity on the computing device 110.

[0036] As an example, the machine learning model 118 can be generated using supervised learning, unsupervised learning, or reinforcement learning. The machine learning model 118 can apply feature learning, sparse dictionary learning, anomaly detection, decision trees, association rules, heuristic rules, etc. to enhance the performance of the machine learning model 118 over time. In addition, the machine learning model 118 can incorporate a statistical model (e.g., regression), principal component analysis, a deep neural network, or some type of artificial intelligence (AI).

[0037] In one configuration, the computing device 110 can include a lighting mode switching module 120 to switch between lighting modes 132. For example, the lighting mode switching module 120 can switch between a first lighting mode (e.g., a calm lighting mode) and a second lighting mode (e.g., an excited lighting mode), or between a default lighting mode or no lighting mode and a specific lighting mode (e.g., a sad lighting mode). The lighting mode switching module 120 can initiate the lighting mode 132 being switched to by controlling the light sources 154 in the human-machine interface device 150 to produce a certain color, a certain animation, a certain intensity level, etc. in accordance with the lighting mode 132 being switched to.

[0038] In one configuration, the key selection monitoring module 114, the lighting mode determination module 116, and the lighting mode switching module 120 can operate while the application 140 is executing on the computing device 110. In other words, while the application 140 (e.g., a game application) is executing on the computing device 110, the keys 152 included in the predefined key set 136 can be monitored and the key frequency 115 can be determined, the lighting mode 132 can be determined based in part on the key frequency 115, and the switch to the lighting mode 132 can be initiated.

[0039] In one configuration, the key frequency 115 can be determined continuously, and the check as to whether to switch the lighting mode 132 can be performed continuously. For example, the key frequency 115 can be recomputed at defined periods (e.g., every minute, every two minutes). When the key frequency 115 is within a different frequency range 138 or less than or greater than a predetermined threshold, the lighting mode 132 can be switched for the human-machine interface device 150.

[0040] In one example, a user can open a separate command interface to manually switch the lighting mode of the human interface device 150. For example, the computing device 110 can include a display (not shown) to show a command interface that can allow a user to manually switch the lighting mode. For example, a user can manually select a calm lighting mode or an excited lighting mode of the human interface device 150. However, with this approach, the user would minimize or close the application that is currently being executed in order to open the command interface and change the lighting mode. If the user has to close a gaming application to change the lighting mode, a user who feels excited while playing the gaming application can not feel that same emotion, which makes manually changing the lighting mode pointless. In the case of the present disclosure, the lighting mode can be automatically switched while the application 140 is executing based on various factors, such as the key frequency related to the frequency range or threshold, the type of application 140 that is being executed on the computing device 110, the user actions performed using the computing device 110, etc.

[0041] In one configuration, the computing device 110 can include a light source 145 that can be separate from the light source 154 included in the human interface device 150. For example, the computing device 110 can include a light source 145 on the housing of the computing device 110. In this configuration, the lighting mode determination module 116 can determine the lighting mode 132 based in part on the key frequency 115. The lighting mode switching module 120 can initiate the lighting mode 132 being switched to by controlling the light source 145 in the computing device 110 and / or the light source 154 in the human interface device 150 to produce a particular color, a particular animation, a particular intensity level, etc. in accordance with the lighting mode 132 being switched to. Thus, in this configuration, both the computing device 110 and the human interface device 150 can produce lighting that reflects the user emotion 134.

[0042] Figure 2An example of a machine learning model 220 that outputs a lighting pattern 230 based on received inputs is illustrated. The machine learning model 220 can run on a computing device 210. The received inputs can include a specific key frequency 212, an application type 214, and a user action 216. The specific key frequency 212 can indicate a frequency at which a specific key is pressed or selected within a duration of time. A non-limiting example of a specific key frequency 212 can be 72 key presses or selections every 5 seconds. The specific keys can be predefined, such as “Q,” “W,” “E,” and “R.” In this example, the frequency can be related to these specific predefined keys and can not apply to other keys. The application type 214 can indicate a name and / or type of an application that is being executed on the computing device 210. Non-limiting examples of an application type include a gaming application, a word processing application, a video application, a photo editing application, a social networking application, and the like. In another example, the application type 214 can indicate a specific sub-type of an application. For example, the application type 214 can indicate that a specific gaming application is related to a first person shooter game, a sports game, a strategy game, and the like. The user action 216 can indicate a specific action being performed by a user using the computing device 210. Non-limiting examples of a user action 216 can include accessing an electronic webpage, such as a shopping webpage, listening to music, electronic chatting, watching a video, and the like.

[0043] In one configuration, the specific key frequency 212, the application type 214, and the user action 216 can be provided as inputs to the machine learning model 220. The machine learning model 220 can be trained to identify an appropriate lighting pattern 230 based on various specific key frequencies 212, application types 214, and / or user actions 216. In this example, the machine learning model 220 can determine a lighting pattern 230 that is most relevant or most applicable to the user’s current activity on the computing device 210.

[0044] Figure 3 An example keyboard 310 with a set or collection of keys 312 is illustrated. In this example, the set or collection of keys 312 can include “Q,” “W,” “E,” “R,” “A,” “S,” “D,” “F,” and “space bar.” It is noted that in this example, the space bar is not spatially located by other keys, but is still grouped with them. For example, the predefined set of keys 312 can correspond to keys that are typically pressed or selected when a user is playing a gaming application. When a key included in the predefined set of keys on the keyboard 310 is pressed or selected at a key frequency within a range of frequencies or greater than a defined threshold, the lighting pattern of the keyboard 310 can be changed.

[0045] Figure 4An example of a timeline 400 for changing lighting modes of a human- machine interface device is illustrated. At a first time (TO), a default lighting mode can be initiated at the human-machine interface device. For example, the default lighting mode can be no lighting, or alternatively, the default lighting mode can be defined by a lighting scheme consisting of a particular combination of color, animation, pattern, and / or intensity of light of a light source in the human-machine interface device. At a second time (Tl), the key frequency can be within a first defined range corresponding to a calm user emotion, and in response, the default lighting mode can be switched to a calm lighting mode. The calm lighting mode can be defined by a lighting scheme consisting of a particular combination of color, animation, pattern, and / or intensity of light of a light source in the human-machine interface device. At a third time (T2), the key frequency can be recalculated, and a determination can be made that the key frequency is now within a second defined range corresponding to an excited user emotion. In response, the calm lighting mode can be switched to an excited lighting mode. The excited lighting mode can be defined by a lighting scheme consisting of a particular combination of color, animation, pattern, and / or intensity of light of a light source in the human-machine interface device. At a fourth time (T3), the key frequency can be recalculated, and a determination can be made that the key frequency is now within the first defined range corresponding to a calm user emotion. In response, the excited lighting mode can be switched back to the calm lighting mode.

[0046] Figure 5 A flowchart illustrating one example method 500 of changing lighting modes of a human-machine interface device is shown. The method can be performed as instructions on a machine, where the instructions can be included on a non-transitory machine-readable storage medium. The method can include initiating a first lighting mode of a human-machine interface device, as in block 510. The method can include determining that a key on the human-machine interface device is selected within a time period at a frequency that exceeds a defined threshold, as in block 520. The method can include identifying a second lighting mode of the human-machine interface device based in part on the frequency exceeding the defined threshold, where the first and second lighting modes define a lighting scheme of a light source in the human-machine interface device that reflects a user emotion, as in block 530. The method can include switching from the first lighting mode to the second lighting mode, as in block 540. In one example, the method 500 can be performed using the computing system 100, although the method 500 is not limited to being performed using the computing system 100.

[0047] Figure 6is a flowchart illustrating one example method 600 of changing a lighting mode of a computer keyboard. The method can be performed as instructions on a machine, where the instructions can be included on a non-transitory machine-readable storage medium. The method can include initiating a first lighting mode of a computer keyboard, where the first lighting mode is a default lighting mode, as in block 610. The method can include monitoring keys selected on the computer keyboard over a time period, where the keys monitored over the time period are included in a predefined set of keys, as in block 620. The method can include determining that a frequency of the keys being selected over the time period exceeds a defined threshold, as in block 630. The method can include identifying, using a machine learning model, a second lighting mode of the computer keyboard based in part on the frequency exceeding the defined threshold, where the second lighting mode reflects a user emotion, as in block 640. The method can include switching from the first lighting mode to the second lighting mode, as in block 650. The method can include determining that the frequency of the keys being selected over a subsequent time period is below the defined threshold, as in block 660. The method can include reverting back to the first lighting mode, as in block 670. In one example, the method 600 can be performed using the computing system 100, although the method 600 is not limited to being performed using the computing system 100.

[0048] Figure 7 Computing device 710 is illustrated that can execute modules of the present disclosure. Computing device 710 is illustrated that can execute high-level examples of the present disclosure. Computing device 710 can include processor(s) 712 in communication with memory device 720. The computing device can include local communication interface 718 for components in the computing device. For example, the local communication interface can be a local data bus and / or related address or control bus, as can be desired.

[0049] Memory device 720 can include modules 724 executable by processor(s) 712, as well as data for modules 724. Modules 724 can perform the functionality described earlier, such as: initiating a first lighting mode of a human-machine interface device; determining that keys on the human-machine interface device are selected over a time period with a frequency that exceeds a defined threshold; identifying a second lighting mode of the human-machine interface device based in part on the frequency exceeding the defined threshold, where the first lighting mode and the second lighting mode define a lighting scheme for light sources in the human-machine interface device that reflects a user emotion; and switching from the first lighting mode to the second lighting mode.

[0050] A data store 722 can also be located in the memory device 720 for storing data related to the modules 724 and other applications, as well as the operating system that is executable by the processor(s) 712.

[0051] Other applications can also be stored in the memory device 720 and executable by the processor(s) 712. The components or modules discussed in this description can be implemented in the form of non-transitory machine-readable software using a high-level, programmed language that uses a mixture of these methods to compile, interpret, or execute.

[0052] The computing device can also have access to I / O (input / output) devices 714 that can be used by the computing device. An example of an I / O device is a display screen that can be used to display output from the computing device. Networking devices 716 and similar communication devices can be included in the computing device. The networking devices 716 can be wired or wireless networking devices that connect to the Internet, a local area network (LAN), a wide area network (WAN), or other computing network.

[0053] The components or modules shown as being stored in the memory device 720 can be executable by the processor 712. The term "executable" can mean a program file in a format that can be executed by the processor 712. For example, a program in a higher-level language can be compiled into a machine code in a format that can be loaded into a random access portion of the memory device 720 and executed by the processor 712, or the source code can be loaded by another executable program and interpreted to generate instructions in a random access portion of memory that are executed by the processor. The executable program can be stored in a portion or component of the memory device 720. For example, the memory device 720 can be a random access memory (RAM), read only memory (ROM), flash memory, solid state drive, memory card, hard disk drive, optical disk, floppy disk, tape, or other memory component.

[0054] The processor 712 can represent multiple processors, and the memory 720 can represent multiple memory units operating in parallel with the processing circuitry. This can provide parallel processing channels for processes and data in the system. The local interface 718 can act as a network to facilitate communication between the multiple processors and the multiple memory units. The local interface 718 can use additional systems designed to coordinate communication such as load balancing, bulk data transfer, and similar systems.

[0055] While the flow diagrams presented herein can suggest a particular order of execution, the order of execution can differ from that which is depicted. For example, two blocks shown in succession can in fact be executed substantially concurrently or in the reverse order that suggested. Additionally, one or more blocks illustrated can be skipped or omitted entirely. Various other blocks can be added. For example, additional blocks can be added for enhancing the utility, accounting, performance, metering, or fault diagnosis of the implementation. Counters, state variables, warning semaphores or messages can be added for these or similar purposes.

[0056] Some of the functional units described in this specification have been labeled as modules, in order to more particularly emphasize their implementation independence. For example, a module can be implemented as a hardware circuit comprising custom very-large-scale integration (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A module can also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like.

[0057] Modules can also be implemented in non- transitory machine-readable software for execution by various types of processors. An identified module of executable code can, for instance, comprise a single instruction, or many instructions, and can be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data can be identified within an module and can be

[0058] Indeed, a module of executable code can be a single instruction, or many instructions, and can even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data can be identified within an module and can be

[0059] The disclosures described herein also can be stored on computer-readable storage media, which include volatile and non-volatile, removable and non-removable media implemented in a method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer-readable storage media can include, but is not limited to, RAM, ROM, electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disks (DVD), or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which has been described in the described disclosures.

[0060] The devices described herein also can include communication connections or networking apparatus and networking connections that allow the devices to communicate with other devices. Communication connections can be an example of communication media. Communication media can embody computer readable instructions, data structures, program modules and other data in a modulated data signal such as a carrier wave or other transport mechanism and can include information delivery media. As an example, and not by way of limitation, communication media can include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency, infrared and other wireless media. The term computer readable media as used herein can include communication media.

[0061] Reference is made to the examples illustrated in the drawings and specific language will be used herein to describe the same. It will, however, be understood that no limitation of the scope of the disclosure is intended by the specific language used herein. Alterations and further modifications of the features illustrated herein, and additional applications of the principles illustrated herein, are contemplated as would normally occur to one of ordinary skill in the art to which the disclosure pertains.

[0062] Also, the described features, structures, or characteristics can be combined in suitable ways. In the preceding description, numerous specific details were provided, such as examples of various configurations, to provide a thorough understanding of examples of the described disclosure. The disclosure can be practiced without some or all of the specific details, or with other methods, components, materials, and so forth. In some instances, some structures or operations were not described in detail in order to avoid obscuring the aspects of the disclosure.

[0063] Although the subject matter has been described in language specific to structural features and / or operations, it is to be understood that the subject defined in the appended claims is not necessarily limited to the specific features and / or operations described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. Many modifications and other arrangements can be designed and incorporated without departing from the scope of the described disclosures.

Claims

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 of a human interface device; determine that a key on the human interface device is selected at a frequency over a time period; compare the frequency to a defined range associated with a second lighting mode; identify a second lighting mode of the human interface device if the frequency is within the defined range, wherein the first lighting mode and the second lighting mode define a lighting scheme for a light source in the human interface device that reflects a user emotion; and switch from the first lighting mode to the second lighting mode; provide the frequency at which the key is selected over the time period to a machine learning model; provide an application type to the machine learning model, wherein the application type corresponds to an application executing on a computing device that receives input from the human interface device; and identify the second lighting mode based on the machine learning model.

2. The non-transitory machine-readable storage medium of claim 1, wherein the lighting scheme defines a color, animation, pattern, intensity level, or a combination thereof for the light source in the human interface device.

3. The non-transitory machine-readable storage medium of claim 1, wherein the key is included in a predefined set of keys.

4. The non-transitory machine-readable storage medium of claim 1, comprising instructions that, when executed by a processor, cause the processor to switch from the first lighting mode to the second lighting mode when a gaming application is executing on a computing device that receives input from the human interface device.

5. The non-transitory machine-readable storage medium of claim 1, comprising instructions that, when executed by a processor, cause the processor to initiate the first lighting mode when a non-gaming application is executing on a computing device that receives input from the human interface device.

6. The non-transitory machine-readable storage medium of claim 1, wherein the first lighting mode is a calm lighting mode that reflects a user emotion.

7. The non-transitory machine-readable storage medium of claim 1, wherein the first lighting mode is an excited lighting mode that reflects a user emotion.

8. The non-transitory machine-readable storage medium of claim 1, comprising instructions that, when executed by a processor, cause the processor to switch from the second lighting mode back to the first lighting mode when the frequency at which the key is selected over the time period moves outside of the defined range.

9. The non-transitory machine-readable storage medium of claim 1, wherein the human interface device is a computer keyboard.

10. A computing system comprising: a computer keyboard comprising a key and a light source; and a computing device to receive input from the computer keyboard, the computing device comprising a processor to: initiate a first lighting mode of a human interface device; determine that a key on the human interface device is selected at a frequency over a time period; compare the frequency to a defined range associated with a second lighting mode; and identify a second lighting mode of the human interface device if the frequency is within the defined range, wherein the first lighting mode and the second lighting mode define a lighting scheme for a light source in the human interface device that reflects a user emotion. ​ ​ if the frequency is within the defined range, identifying a second lighting mode of the human interface device, wherein the first lighting mode and the second lighting mode define a lighting scheme for light sources in the human interface device, the lighting scheme reflecting a user emotion; and switching from the first lighting mode to the second lighting mode; providing the frequency with which the key was selected over the time period to a machine learning model; providing an application type to the machine learning model, wherein the application type corresponds to an application executing on a computing device that receives input from the human interface device; and identifying the second lighting mode based on the machine learning model.

11. The computing system of claim 10, wherein the first lighting mode and the second lighting mode define a lighting scheme for a computer keyboard, wherein the lighting scheme defines a color, animation, pattern, intensity level, or combination thereof for light sources of the human interface device.

12. The computing system of claim 10, wherein the computing 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 the computing device.

13. A method of changing a lighting mode of a computer keyboard, comprising: initiating a first lighting mode of a computer keyboard, wherein the first lighting mode is a default lighting mode; monitoring a frequency with which a key is selected on the computer keyboard over a time period, wherein the keys monitored over the time period are included in a predefined set of keys; comparing the frequency to a defined range associated with a second lighting mode; if the frequency is within the defined range, identifying the second lighting mode of the computer keyboard using a machine learning model, wherein the second lighting mode reflects a user emotion; switching from the first lighting mode to the second lighting mode; determining that the frequency with which the key is selected over a subsequent time period moves outside of a defined threshold; and resuming back to the first lighting mode.

14. The method of claim 13, wherein the first lighting mode and the second lighting mode define a lighting scheme for the computer keyboard, wherein the lighting scheme defines a color, animation, pattern, intensity level, or combination thereof for light sources of the computer keyboard. ​

Images