Patent Publication Number: US-2018035927-A1

Title: Wearable device for sweat testing administration

Description:
RELATED APPLICATION DATA 
     This application claims the benefit of priority of U.S. Provisional Patent Application Ser. No. 62/130,222, filed on Mar. 9, 2015, and titled “METHODS, SYSTEMS, AND SOFTWARE FOR PROVIDING PERSPIRATION HEALTH DATA TO A USER”, which is incorporated by reference herein in its entirety for all purposes. 
    
    
     TECHNICAL FIELD 
     Various embodiments disclosed herein relate generally to the field of wearable technology. More specifically, but not exclusively, various embodiments are directed to computer implemented methods a machine readable storage medium for assisting a user with administering a sweat test using a sweat test strip and a wearable device comprising a plurality of physiological sensors. 
     BACKGROUND 
     A sweat test may use various types of biosensor strips that rest or stick to the surface of the skin and measure chemicals that may be present in a user&#39;s sweat. In the race to develop highly useful and marketable sweat tests, various biosensor strips have been designed and configured to measure for electrolytes. Such a sweat test may allow a user to determine if they are dehydrated or hydrated. 
     SUMMARY 
     Various embodiments disclosed herein are directed to a computer-implemented method of assisting a user with administering a sweat test using a sweat test strip and a wearable device comprising a plurality of physiological sensors. The method includes receiving, via the wearable device, an indication of a selected sweat-test type from the user, determining, on the wearable device and based on the selected sweat-test type, which one or more of the plurality of physiological sensors to use for sensing one or more test-triggering physiological conditions of the user, collecting, on the wearable device, sensor data using the determined one or more of the plurality of physiological sensors, determining, on the wearable device using the sensor data, whether or not the one or more test-triggering physiological conditions are present in the user, in response to determining that at least one of the one or more test-triggering physiological conditions is present, instructing, by the wearable device, the user to deploy the sweat test strip to a location on the user and to initiate the sweat test; and instructing, by the wearable device, the user to end the sweat test. 
     Various embodiments disclosed herein are directed to a machine-readable storage medium containing machine-executable instructions for assisting a user with administering a sweat test using a sweat test strip and a wearable device comprising a plurality of physiological sensors. The machine-executable instructions include a first set of machine-executable instructions for receiving, via the wearable device, an indication of a selected sweat-test type from the user; a second set of machine-executable instructions for determining, on the wearable device and based on the selected sweat-test type, which one or more of the plurality of physiological sensors to use for sensing one or more test-triggering physiological conditions of the user; a third set of machine-executable instructions for collecting, on the wearable device, sensor data using the determined one or more of the plurality of physiological sensors; a fourth set of machine-executable instructions for determining, on the wearable device using the sensor data, whether or not the one or more test-triggering physiological conditions are present in the user; a fifth set of machine-executable instructions for, in response to determining that at least one of the one or more test-triggering physiological conditions is present, instructing, by the wearable device, the user to deploy the sweat test strip to a location on the user and to initiate the sweat test; and a sixth set of machine-executable instructions for instructing, by the wearable device, the user to end the sweat test. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For the purpose of illustrating the invention, the drawings show aspects of one or more embodiments of the invention. However, it should be understood that the present invention is not limited to the precise arrangements and instrumentalities shown in the drawings, wherein: 
         FIG. 1  illustrates an example of a flow diagram illustrating a method for assisting a user with administering a sweat test using a sweat test strip and a wearable device comprising a plurality of physiological sensors; 
         FIG. 2  illustrates an example of a sweat data matrix; 
         FIG. 3  illustrates an example diagrammatic representation of a wearable sweat analysis (WSA) system in accordance with an embodiment of the invention; 
         FIG. 4  illustrates an example diagrammatic representation of an exemplary wearable computing device that can be used to implement one or more features of the present invention; 
         FIG. 5A  illustrates an example of a sweat test strip in accordance with an embodiment of the invention; 
         FIG. 5B  illustrates the sweat test strip of  FIG. 5A  placed on the forearm of a user; 
         FIG. 6  illustrates an exemplary user start graphical user interface (GUI) in accordance with an embodiment; 
         FIG. 7A  illustrates an exemplary user alert GUI in accordance with an embodiment; 
         FIG. 7B  illustrates an exemplary sweat analysis sensor data GUI in accordance with an embodiment; 
         FIG. 8  illustrates an exemplary network alert database; 
         FIG. 9A  illustrates an exemplary network identification database; 
         FIG. 9B  illustrates an exemplary wearable alert database; 
         FIG. 10A  illustrates an exemplary wearable sensor database; 
         FIG. 10B  illustrates an exemplary wearable sweat analysis sensor database; 
         FIG. 11  is a flow diagram illustrating a wearable software method; 
         FIG. 12  is a flow diagram illustrating a wearable identification software method and a network identification software method; 
         FIG. 13  is a flow diagram illustrating a wearable manual choice software method; 
         FIG. 14A  is a flow diagram illustrating a wearable monitoring software method; 
         FIG. 14B  is a flow diagram illustrating a wearable action software method; 
         FIG. 15  illustrates particular implementations of various steps of a method for providing sweat health data to a user; and 
         FIG. 16  illustrates a block diagram of a computing system that can be used to implement any one or more of the methodologies disclosed herein and any one or more portions thereof. 
     
    
    
     The drawings are not necessarily to scale and may be illustrated by phantom lines, diagrammatic representations and fragmentary views. In certain instances, details that are not necessary for an understanding of the embodiments or that render other details difficult to perceive may have been omitted from the figures. 
     DETAILED DESCRIPTION 
     The description and drawings presented herein illustrate various principles. It will be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described or shown herein, embody these principles and are included within the scope of this disclosure. As used herein, the term, “or,” as used herein, refers to a non-exclusive or (i.e., and/or), unless otherwise indicated (e.g., “or else” or “or in the alternative”). Additionally, the various embodiments described herein are not necessarily mutually exclusive and may be combined to produce additional embodiments that incorporate the principles described herein. 
     As with most burgeoning technologies, sweat tests and related systems have not yet been optimized with regard to cost. Accordingly, it would be desirable to provide improved sweat tests that use biosensor strips at a lower cost generally. Various additional benefits of the system described herein will be apparent in view of the present description. 
     Aspects of the present disclosure are directed to wearable technology devices, for example, smartwatches, health-bands, fitness-bands, and smartphones, among others, and combinations thereof, that are enabled to assist their wearers in preventing and/or treating physiological conditions, such as dehydration, stress, fatigue, muscle fatigue, infection, and/or depression by instructing a user when to take a sweat test. Thus, wearable devices include attachable wearable devices that are attached to the body (e.g., wrist, neck, ankle, waist, ear, etc.) as well as carried devices (e.g., mobile phones). Accordingly, various embodiments described herein are adapted to monitor and decide when a person should test their sweat in accordance with the occurrence of one or more certain physiological conditions. Because some physiological conditions can be highly debilitating and even life-threatening, enabling a wearable device to provide such functionality can allow users of this technology to not only quickly recognize certain physiological states, but also, for example, to take remedial measures as directed by the wearable device. Furthermore, by providing a user with an indication of when to take a sweat test eliminates guesswork that may cost the user money. For example, taking a sweat test when prompted may prevent unnecessary sweat tests and costs associated therewith. As described below in detail, such aspects may be facilitated by various GUI&#39;s, and other software features running on one or more of a variety of devices, including wearable technology devices (or simply “wearable devices”), and web servers, among other devices. These broad aspects of the present invention are described below in connection with a variety of specific examples. That said, those skilled in the art will readily understand that the specific examples described are just that: examples that will inform and instruct those skilled in the art about broad features that they can then implement in a plethora of ways using only routine knowledge and skill in the art. 
     Turning now to the drawings,  FIG. 1  illustrates an exemplary overall method  100  that can be performed by wearable software executed on one or more devices of a WSA, such as exemplary WSA system  300  of  FIG. 3 . Before describing overall method  100  of  FIG. 1 , a sweat data matrix  200  of  FIG. 2  and a WSA system  300  of  FIG. 3  are first described to give the reader an example context in which the overall method  100  may be executed. 
     Referring now to  FIG. 2 , in the embodiment shown, sweat data matrix  200  includes a row  202  containing test-triggering physiological conditions that is crossed with a column  204  containing health conditions. It will be apparent that various alternative data structures may be used to store and use the information (or similar types of information) illustrated in  FIG. 2 . For example, Each health condition in the column  204  may be associated with a rule table, including multiple rules each of which corresponds to one of the physiological conditions in the row  202  and corresponding measurement recommendation. 
     Test-triggering physiological conditions, such as those in row  202 , may include but are not limited to extended exercise, high blood pressure, fever, and/or lack of sleep. In various embodiments, such physiological conditions may be identified in the wearer by analyzing current, recent, or historical sensor data from one or more wearable devices (such as, in some embodiments, a wearable device storing or analyzing the matrix  200 ). Health conditions, such as the health conditions provided in column  204 , may include but are not limited to dehydration, stress, fatigue, muscle fatigue, infection, and depression. In various embodiments, these health conditions may be manually-identified by the wearer, a physician, or caregiver as being exhibited by the user or as being relevant for tracking for the user. Alternatively, in some embodiments, sensor data for the user may be used in conjunction with, e.g., a trained model (e.g., trained according to logistic regression, neural networks, or other machine learning approached) to draw conclusions about health conditions exhibited by the user. In some embodiments, only those rows  204  (or corresponding structures, e.g., rule tables) associated with a health condition exhibited by the wearer or identified as relevant for tracking for the user may be loaded (e.g., in the wearable device) for evaluation. 
     Sweat data matrix  200  provides examples of test-triggering physiological conditions that may indicate if a sweat test, such as a sweat-test type to measure electrolytes of a user, should be taken and/or the health condition, such as dehydration, that may be monitored by taking the sweat test. Extended exercise may be indicated by a user pulse of greater than 120 beats per minute for greater than 30 minutes and may be cause to measure electrolytes to monitor dehydration. Extended exercise may also be cause to measure lactates to monitor muscle fatigue. In another example, high blood pressure may be cause to measure electrolytes to monitor dehydration and/or to measure cortisol and dopamine to monitor stress. In yet another example, fever, such as a temperature greater than 101° F. (38.3° C.), may be cause to measure interleukin six (IL-6) to monitor infection. In another example, lack of sleep, such as sleeping less than 6 hours per night, may be cause to measure cortisol and dopamine to monitor stress and/or fatigue or to measure Proinflammatory cytokines and neuropeptides to monitor depression. Sweat data matrix  200  is provided as an example only and the test-triggering physiological conditions of row  202  and the health conditions of column  204  are not limited to those shown. In addition, sweat-test types are not limited to those shown here. After reading this disclosure in its entirety, a person of ordinary skill in the wearable technology art will appreciate that any appropriate number of test-triggering physiological conditions may indicate sweat-test types that may be capable of monitoring a variety of different health conditions. 
     Referring now to  FIG. 3 , an example of a wearable sweat analysis (WSA) system  300  includes a wearable device  302  and a server  304  that communicate with one another via one or more communications networks  306  such as, for example, a local area network, carrier network, cloud computing environment network, or the Internet. While the server  304  is identified as a singular server in various examples, in other embodiments the various functions described herein as being performed by the server  304  may be distributed among multiple separate servers (e.g., a set of servers forming a service provider network) such as multiple virtual machines in a cloud computing environment. While not shown, those skilled in the art will readily understand that various specific communications systems will be present, such as, for example, wireless data communications systems (e.g., cellular-based communications systems and satellite-based communications systems, WI-FED communications systems, etc.) and wired communications system (e.g., optical fiber based communications systems, copper wire based communications systems, etc.). Such systems may work together to provide the point-to-point communications needed between wearable device  302  and server  304 . Wearable device  302  may be worn by a user on any appropriate part of their body. For example, wearable device  302  may be worn on a wrist, forearm, upper arm, leg, waist, neck, ear, and/or back and may include physiological sensors, such as physiological sensors  308 ( 1 ) to  308 (N) dimensioned and configured for data collection at specific locations on the body. In addition, physiological sensors  308 ( 1 ) to  308 (N) may be in contact with the user. Wearable device  302  may be worn by a person or another entity, and may record data related to the individual and/or the individual&#39;s surroundings. 
     Still referring to  FIG. 3 , WSA system  300  may also include at least a sweat test strip  310 . Sweat test strip  310  may further include a strip ID barcode  312  (or other indicia such as a QR code or textual code capable of optical character recognition). Wearable device  302  includes a wearable clock  312 , a wearable display  314 , a wearable timer  316 , an operating system (OS)  316 , a power  318 , such as a battery or other appropriate power source, a wearable communication interface  320 , shown here as “Wearable Comm”, that may use e.g., BLUETOOTH™ and/or WI-FI™, and an optical scanner  322  (e.g. a camera) that may be used to read strip ID barcode  312  on sweat test strip  310 . Strip ID barcode  312  may be referred to herein interchangeably with strip identification barcode. As noted above, wearable device  302  may also include one or more wearable sensors  308 ( 1 ) to  308 (N) such as, for example, a pulse sensor  308 ( 1 ) and blood pressure sensor  308 (N). Herein, pulse sensor  308 ( 1 ) and blood pressure sensor  308 (N) may be referred to as “physiological sensors.” It is noted that the plurality of physiological sensors  308 ( 1 ) to  308 (N) may include any appropriate number of physiological sensors onboard wearable device  302  and the physiological sensors may not be limited to monitoring a user&#39;s pulse and blood pressure. For example, various ones of physiological sensors  308 ( 1 ) to  308 (N), if provided, may be designed and configured to monitor sleep or temperature. It will be apparent that, in some embodiments, such sensors  308 ( 1 -N) may be used in conjunction with interpretation instructions (not shown) in the memory  328  for execution by the processor (not shown) to extract parameters from the raw data gathered by the hardware sensors  308 ( 1 -N). For example, the pulse sensor  308 ( 1 ) may include an optical sensor for capturing a color or other value of the user&#39;s skin underlying the sensor; software executed by the processor (not shown) may then process this raw data (e.g., the variations in color over time) to estimate a user&#39;s pulse. 
     In some embodiments, the sweat test strip may be held by the wearable device  302  prior to and during use. In particular, the body of the wearable device  302  may include a slot or other cavity for holding the sweat test strip  310  against the body of the user. In some embodiments, such as those described with regard to  FIGS. 5A-B , the sweat test strip may include a pulltab or other structure for enabling the user to activate the test strip (e.g., by allowing sweat to come into contact with a testing pad). In some such embodiments, the body of the wearable device may include an aperture for allowing the activation structure to extend from the body of the wearable device such that the activation structure may be accessed by the user. In other embodiments, the wearable device may include mechanical components (specific examples of which will be apparent to those of skill in the art) for removing a protective cellophane layer or for otherwise activating a sweat test strip. Upon use of the test strip, the user may be able to remove and dispose of the test strip and insert a new, unused test strip into the wearable device (e.g., by sliding the test strips through a slot or by opening a compartment, or removing a frame structure). In such embodiments, variations to the example test strip of  FIGS. 5A-B  will be apparent; for example, in some such embodiments the test strip need not be provided with an adhesive layer because the wearable device may sufficiently hold the strip against the skin of the user. 
     Wearable device  302  may further include a wearable memory  328  that contains a wearable sweat analysis sensor database  330 , a wearable sensor database  332 , and a wearable alert database  334 . Wearable sweat analysis database  330  may be used to store sensor data collected by one or more of physiological sensors  308 ( 1 ) to  308 (N) during a sweat test. Wearable sensor database  332  may be used to store sensor data collected by one or more of physiological sensors  308 ( 1 ) to  308 (N) when a sweat test is not being conducted. Wearable alert database  334  may be used to store test-triggering physiological conditions, instructions to deploy sweat test strip  310  to a location on the user, and instructions to end the sweat test. Further discussion of wearable alert database  334 , wearable sensor database  332 , and wearable sweat analysis sensor database  330  is provided herein in the context of  FIGS. 9B to 10B , respectively. 
     Wearable device  302  may further include wearable software  336 , which may comprise wearable identification software  340  as described further herein in the context of  FIG. 12 . Wearable software  336  may control the overall operation of WSA system  300 . Wearable identification software  340  may also include a user start GUI  342 , as described further herein in the context of  FIG. 6 . Wearable identification software  340  may identify a specific sweat test strip and is described in more detail herein in the context of  FIG. 12 . Wearable software  336  may further comprise a wearable manual choice software  344 , a wearable monitoring software  346 , and a wearable action software  348 , which may include a sweat analysis sensor data GUI  350  and a user alert GUI  352 , as described further herein in the context of  FIGS. 7A and 7B . Wearable manual choice software  344  may allow the user to begin a manual sweat test or to close user start GUI  342 , which may prompt the execution of wearable monitoring software  346  that may monitor the sensor data to see if there is a match with one or more test triggering physiological conditions contained in wearable alert database  334 . Wearable manual choice software  344  is discussed in detail below in the context of  FIG. 13 . Wearable monitoring software  346  is discussed in detail below in the context of  FIG. 14A . Wearable action software  348  is discussed in greater detail below in the context of  FIG. 14B . 
     It will be apparent that while various embodiments are described in terms of the wearable software  336 , portions thereof, or other software or instructions “performing” various functionalities, such functionalities will in fact be performed by hardware components, such as a processor. As such, the wearable device  302  and server  304  may each include respective processors. As used herein, the term processor will be understood to encompass microprocessors, field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and other hardware devices capable of processing data in accordance with the described functionalities. In various embodiments wherein one or more ASICs are hard-wired to perform one or more of the functionalities described herein, software or instructions for defining such functionalities may be omitted. Further, as used herein, the term “memory” will be understood to encompass both volatile memories (e.g., L1/L2/L3 cache which may be implemented in SRAM, or system memory which may be implemented in DRAM) and nonvolatile memories (e.g., storage which may be implemented in flash, magnetic, or optical memories) but to exclude transitory signals per se. 
     Still referring to  FIG. 3 , server  304  of WSA system  300  may include a server alert database  354 , server identification software  356 , a server identification database  358 , and a server communications interface  360 , shown here as “Server Comm.” Server alert database  354  may store a plurality of alert databases specific to a sweat-test type, such as an electrolyte sweat-test type. Server alert database  354  is discussed in detail below in the example of  FIG. 8 . Server communications interface  360  may be communicatively connected via the communication network  306  to wearable device  302 . Server identification software  356  may receive strip identification barcode  312  data from wearable identification software  340  on wearable device  302  and may compare the strip identification barcode data to data in server identification database  358  to identify the sweat test strip  310  and, when the sweat test strip is identified, may provide information regarding the sweat test strip to the wearable identification software. It is noted that sweat test strip  310  may be configured for any one or more of a number of different sweat-test types. Exemplary sweat-test types may include, but not be limited to, sweat-test types that measure electrolyte levels, cortisol levels, interleukin six levels, dopamine levels, and lactate levels of a user. 
     In various embodiments, the wearable device  302  may not defer to the server  304  for the functions described herein. For example, in some embodiments, the wearable device  302  itself may include one or more of the components  354 - 360  for performing these functions locally. As another alternative, the wearable device  302  may instead communicate with a mobile device, tablet, personal computer, or other device of the user which may include one or more of the components  354 - 360  for performing these functions to serve the wearable device  302 . 
     Referring again to  FIG. 1 , overall method  100  of  FIG. 1  is described with reference to elements of WSA system  300  of  FIG. 3  described above. At step  105 , wearable device  302  receives an indication of a selected sweat-test type. This indication may be provided, for example, by a user manually entering the sweat-test type via user start GUI  342 , by scanning strip ID barcode  312  with optical scanner  322 , or by communicating via short range wireless communication (e.g., NFC or Bluetooth) with a chip attached to or otherwise associated with (e.g., on packaging of) the test strip. Identifying the sweat-test type may be performed via wearable identification software  340 , server identification database  358 , and server identification software  356 . Server identification database  358  stores sweat-test type identification data that may be compared to user indicated sweat-test type data to match a sweat-test type. At step  110 , determine which one or more of a plurality of physiological sensors to use for sensing one or more test-triggering physiological conditions. Step  110  may be performed by modules of wearable software  338 . Test-triggering physiological conditions, test-trigger data, as well as other data stored in server alert database  354  are copied by server identification software  356  for a matching entry in server identification database  358  and sent to wearable identification software  340 . Wearable identification software  340  may also download a test-specific algorithm from server  304 , based on the selected sweat-test type, for determining which one or more of the plurality of physiological sensors to use based on the selected sweat-test type. At step  115 , wearable device  302  collects sensor data using the one or more determined physiological sensors. There are two different methods for initiating collection of sensor data. A user, through interaction with user start GUI  342  may manually begin a sweat test or close the user start GUI  342  to initiate monitoring of sensor data until a test-triggering physiological condition is detected, at which point a user is instructed to begin a sweat test. Wearable manual choice software  344  monitors whether or not user start GUI  342  is closed or not and if a user selects to begin a sweat test manually or not. If it is determined by wearable manual choice software  344 , that user start GUI  342  has been closed, then wearable monitoring software  346  is executed. If it is determined by wearable manual choice software  344  that a user has selected to begin a sweat test, then wearable action software  348  may be executed. Execution of either wearable monitoring software  346  or wearable action software  348  includes collection of sensor data using one or more determined physiological sensors. 
     Continuing through overall method  100  of  FIG. 1 , at step  120 , it may be determined whether the one or more test-triggering physiological conditions are present in the user. Wearable monitoring software  346  may make this determination by comparing sensor data to test-trigger data to determine if one or more test-triggering physiological conditions are present. At step  125 , the user may be instructed to deploy sweat test strip  310  at a location on the user and to initiate the sweat test in response to determining that at least one of the one or more test-triggering physiological conditions is present. Wearable action software  348 , when executed, may display at user alert GUI  352  instructions for when and where to deploy sweat test strip  310 . In an embodiment, user alert GUI  352  may also display the one or more test-triggering physiological conditions determined to be present in the user. Proceeding through overall method  100 , at step  130 , the user is provided instructions to end the sweat test. Wearable action software  348 , when executed, may determine the instructions that may be displayed on user alert GUI  352 . In an embodiment, instructions for processing results of a sweat test may also be displayed on user alert GUI  352 . 
       FIG. 4  is a block diagram of an exemplary wearable computing device  400  that may be configured to implement any one or more of various features and/or processes of the present disclosure, such as the features and processes illustrated in other figures of this disclosure, as well as features and processes that would be apparent to those of ordinary skill in the art after reading this entire disclosure. As shown, computing device  400  may include a memory interface  404 , one or more data processors, image processors and/or central processing units  408 , and a peripherals interface  412 . Memory interface  404 , one or more processors  408 , and/or peripherals interface  412  may be separate components or may be integrated in one or more integrated circuits. The various components in computing device  400  may be coupled by one or more communication buses or signal lines. 
     Sensors, devices, and subsystems may be coupled to peripherals interface  412  to facilitate one or more functionalities. For example, a motion sensor  416 , a light sensor  420 , and a proximity sensor  424  may be coupled to peripherals interface  412  to facilitate orientation, lighting, and/or proximity functions. Other sensors  428  may also be connected to peripherals interface  412 , such as a global navigation satellite system (GNSS) (e.g., GPS receiver), a temperature sensor, a biometric sensor, and/or one or more other sensing devices, to facilitate related functionalities. 
     A camera subsystem  432  and an optical sensor  436 , e.g., a charged coupled device (CCD) or a complementary metal-oxide semiconductor (CMOS) optical sensor, may be utilized to facilitate camera functions, such as recording images and/or video. Camera subsystem  432  and optical sensor  436  may be used to collect images of a user to be used during authentication of a user, e.g., by performing facial recognition analysis. 
     Communication functions may be facilitated through one or more wireless communication subsystems  440 , which may include radio frequency receivers and transmitters and/or optical (e.g., infrared) receivers and transmitters. The specific design and implementation of communication subsystem  440  may depend on the communication network(s) over which computing device  400  is intended to operate. For example, computing device  400  may include communication subsystems  440  designed to operate over a GSM network, a GPRS network, an EDGE network, a WI-FI™ or WiMax™ network, and/or a BLUETOOTH™ network. In particular, wireless communication subsystems  440  may include hosting protocols such that one or more devices  400  may be configured as a base station for other wireless devices. 
     An audio subsystem  444  may be coupled to a speaker  448  and a microphone  452  to facilitate voice-enabled functions, such as speaker recognition, voice replication, digital recording, and/or telephony functions. Audio subsystem  444  may be configured to facilitate processing voice commands, voice-printing, and voice authentication. 
     I/O subsystem  456  may include a touch-surface controller  460  and/or other input controller(s)  464 . Touch-surface controller  460  may be coupled to a touch surface  468 . Touch surface  468  and touch-surface controller  460  may, for example, detect contact and movement or a lack thereof using one or more of any of a plurality of touch sensitivity technologies, including but not limited to capacitive, resistive, infrared, and/or surface acoustic wave technologies, optionally as well as other proximity sensor arrays and/or other elements for determining one or more points of contact with touch surface  468 . 
     Other input controller(s)  464  may be coupled to other input/control devices  472 , such as one or more buttons, rocker switches, thumb-wheel, infrared port, USB port, and/or a pointer device such as a stylus. One or more related buttons or other controls (not shown) may include one or more sets of up/down buttons for volume and/or amplitude control of speaker  448  and/or microphone  452 . Using the same or similar buttons or other controls, a user may activate a voice control, or voice command, module that enables the user to speak commands into microphone to cause device  400  to execute the spoken command. The user may customize functionality of one or more buttons or other controls. Touch surface  468  may, for example, also be used to implement virtual or soft buttons and/or a keyboard. 
     In some implementations, computing device  400  may present recorded audio and/or video files, such as MP3, AAC, and/or MPEG files. In some implementations, computing device  400  may include the functionality of an MP3 player, such as an iPod™. Computing device  400  may, therefore, include a 36-pin connector that is compatible with related iPod™ hardware. Other input/output and control devices may also be used. 
     As shown, memory interface  404  may be coupled to one or more types of memory  476 . Memory  476  may include high-speed random access memory and/or non-volatile memory, such as one or more magnetic disk storage devices, one or more optical storage devices, and/or flash memory (e.g., NAND, NOR). Memory  476  may store an operating system  480 , such as Darwin™ RTXC, LINUX, UNIX, OS X™, WINDOWS™, and/or an embedded operating system such as VxWorks. Operating system  480  may include instructions for handling basic system services and/or for performing hardware dependent tasks. In some implementations, operating system  480  may comprise a kernel (e.g., UNIX kernel). Further, in some implementations, operating system  480  may include instructions for performing voice authentication. 
     Memory  476  may also store communication instructions  482  to facilitate communicating with one or more additional devices, one or more computers, and/or one or more servers. Additionally or alternatively, memory  476  may include: graphical user interface instructions  484  to facilitate graphic user interface processing; sensor processing instructions  486  to facilitate sensor-related processing and functions; phone instructions  488  to facilitate phone-related processes and functions; electronic messaging instructions  490  to facilitate electronic-messaging related processes and functions; web browsing instructions  492  to facilitate web browsing-related processes and functions; media processing instructions  494  to facilitate media processing-related processes and functions; GNSS/Navigation instructions  496  to facilitate GNSS and navigation-related processes and instructions; and/or camera instructions  497  to facilitate camera-related processes and functions. Memory  476  may store other software instructions  498  to facilitate other processes and functions. For example, other software instructions  498  may include instructions for counting steps the user takes when device  400  is worn. 
     Memory  476  may also store other software instructions (not shown), such as web video instructions to facilitate web video-related processes and functions and/or web shopping instructions to facilitate web shopping-related processes and functions. In some implementations, media processing instructions  494  may be divided into audio processing instructions and video processing instructions to facilitate audio processing-related processes and functions and video processing-related processes and functions, respectively. An activation record and International Mobile Equipment Identity (IMEI)  499  or similar hardware identifier may also be stored in memory  476 . 
     Each of the above identified instructions and applications may correspond to a set of instructions for performing one or more functions described herein. These instructions need not necessarily be implemented as separate software programs, procedures, or modules. Memory  476  may include additional instructions or fewer instructions. Further, various functions of computing device  400  may be implemented in hardware and/or in software, including in one or more signal processing and/or application specific integrated circuits. 
       FIG. 5A  illustrates an exemplary embodiment of sweat test strip  310  of  FIG. 3 . As shown, sweat test strip  310  may include a sweat permeable adhesive layer  500 , a cellophane layer  502 , a sweat absorbing patch  504 , a top protective textile layer  506 , and strip identification barcode  312 . Sweat permeable adhesive layer  500  may allow sweat test strip  310  to stick to the user&#39;s skin while simultaneously allowing sweat to permeate therethrough. Cellophane layer  502  may substantially prevent sweat from permeating through to sweat absorbing patch  504 , as the cellophane layer itself is impermeable to sweat, and may have an integrated pull tab  510  to allow a user to remove the cellophane layer when the user desires to test their sweat. Once cellophane layer  502  is removed, sweat absorbing patch  504  may be able to absorb sweat. In some embodiments, sweat absorbing patch  504  may further include color change functionality. For example, sweat absorbing patch  504  may turn a particular color or shade when a user&#39;s sodium content is too high or too low. Top protective textile layer  506  may prevent any other moisture or contaminants from the surrounding environment from coming into contact with sweat absorbing patch  504  and may include strip ID barcode  312 , which may enable optical scanner  322  ( FIG. 3 ) to identify sweat test strip  310 .  FIG. 5B  illustrates exemplary sweat test strip  310  applied to forearm  508  of a user, although it is emphasized that the sweat test strip may be fastened to any appropriate part of the user&#39;s body. As noted above, pull-tab  510  of cellophane layer  502  accommodates for quick and easy testing, as the user may simply pull on pull-tab  510  of cellophane layer  502  to initiate a sweat test in accordance with an embodiment of the current invention. 
     Referring now to  FIG. 6 , and also to  FIG. 3 ,  FIG. 6  illustrates an exemplary embodiment of user start GUI  342  of  FIG. 3  to be displayed, for example, on a display device (which, in some embodiments, is coupled with a touchscreen input device) of the wearable device or of another device (e.g., a mobile phone, tablet, or pc) of the user configured to control the wearable device. Various alternative GUIs for performing the functionality described herein will be apparent. Those skilled in the art will readily appreciate the types of features common to wearable devices that can be implemented in user start GUI  342 . Those skilled in the art will also understand the myriad of common user-interactive graphical soft controls and elements that can be used to receive inputs from a user, solicit responses from the user, and otherwise communicate relevant information to the user. Therefore, these controls and elements need not be described herein for those skilled in the art to understand how to make and use the claimed invention to the fullest scope claimed. In this embodiment, user start GUI  342  includes a “Scan Sweat Test Strip” button  600 , which when actuated allows the user to use optical scanner  322  to scan strip identification barcode  312 . Sweat identification barcode data may be sent to server  304 , which may execute network identification software  356  to compare the data from scan strip identification barcode  312  with data from the network identification database  358 , and then send related sweat test strip data to wearable device  302 , such as the name of the sweat test strip to be displayed on user start GUI  342 , for example. User start GUI  342  may then display sweat test strip name as displayed in window  602 . As shown in  FIG. 6 , in this example, the sweat test strip name displayed in window  602  is “ElectrolyteTS”. User start GUI  342  includes an “Accept” button  604 , which allows a user to confirm that the sweat test strip name displayed in window  602 , is the sweat test strip they would like to use. User start GUI  342  may further include a “Strip ID Barcode” window  606 . Through user interaction, a user manually enters a sweat test strip ID barcode using a soft keypad  608  or by scanning strip identification barcode  312  with optical scanner  322 . Once strip identification barcode  312  has populated window  606 , through user interaction with a “Send” button  610 , wearable device  302  may send the barcode data to server  304 , where network identification software  356  may compare it with appropriate data in network identification database  358 . Server  304  may then return the sweat test strip name as displayed in window  602 , shown here as “ElectrolyteTS”, for display on user start GUI  342 . In this example, user start GUI  342  also includes a “Begin Sweat Test” button  612  for allowing a user to manually begin a sweat test and a “Close” button  614  for allowing the user to initiate wearable monitoring software  346 . 
     With continuing occasional reference to  FIG. 3 ,  FIG. 7A  illustrates an exemplary embodiment of user alert GUI  352  of  FIG. 3 . Those skilled in the art will readily appreciate the types of features common to wearable devices that can be implemented in user alert GUI  352 . Those skilled in the art will also understand the myriad of common user-interactive graphical soft controls and elements that can be used to receive inputs from a user, solicit responses from the user, and otherwise communicate relevant information to the user. Therefore, these controls and elements need not be described herein for those skilled in the art to understand how to make and use the claimed invention to the fullest scope claimed. In this embodiment, user alert GUI  352  may include a display  702  for displaying instructions to take a sweat test. User alert GUI  352  may further include a “Triggering Data” window  704 , which displays test-triggering data, such as “Blood Pressure 88 mmHG,” for example. User alert GUI  352  may further include a “Cellophane Layer Has Been Removed” button  706 , that a user may select after they have physically removed cellophane layer  502  from sweat test strip  310 . After engaging “cellophane layer has been removed” button  706 , wearable device  302  receives data from sweat test strip  310  indicating that the sweat test strip is now absorbing and testing sweat. User alert GUI  352  may also include a “Sweat Analysis Sensor Data” button  708  and a “Close” button  710 . If “Sweat Analysis Sensor Data” button  708  is selected, sweat analysis sensor data GUI  350  opens. 
       FIG. 7B  illustrates an exemplary embodiment of sweat analysis sensor data GUI  350  of  FIG. 3 , which may include the date and time and sensor data collected by one or more of physiological sensors  308 ( 1 ) to  308 (N) identified for use in performing method  100  of  FIG. 1 . Those skilled in the art will understand the myriad of common user-interactive graphical soft controls and elements that can be used to receive inputs from a user, solicit responses from the user, and otherwise communicate relevant information to the user. Therefore, these controls and elements need not be described herein for those skilled in the art to understand how to make and use the claimed invention to the fullest scope claimed. In this embodiment, sweat analysis sensor data GUI  350  includes a date and a time as well as one or more sensor readings, which, as shown in  FIG. 7B , may include pulse, blood pressure, sleep total in the past 24 hours, and body temperature readings, among others. As shown in  FIG. 7B , sensor data displayed on sweat analysis sensor data GUI  350  in this example are taken at ten second intervals. Sweat analysis sensor data GUI  350  may include a scroll bar  712  to scroll through sensor data during or after a sweat analysis test. Sweat analysis sensor data GUI  350  may also include a “Close” button  714  that through user interaction closes the sweat analysis sensor data GUI. 
       FIG. 8  illustrates an exemplary embodiment of network alert database  354  of  FIG. 3 . Network alert database  354  includes one or more databases corresponding to a sweat-test type. For example, as shown in  FIG. 8 , a first database may be an ElectrolyteTS Database  800  including an ElectrolyteTS Alert Database  802 . As shown, ElectrolyteTS Alert Database  802  includes wearable sensor types (physiological sensors), wearable sensor alert levels (test-trigger data), and alert actions and finish actions. Wearable sensor alert levels are referred to interchangeably herein with test-trigger data. Alert actions may be instructions to deploy sweat test strip  310  of  FIG. 3 . Finish actions may include instructions to end the sweat test or instructions for sweat test processing following a sweat test. Physiological sensor data collected is compared to data in network alert database  354  to determine whether one or more test-triggering physiological conditions are present in the user. For example, for a sensor capable of measuring pulse, if a user&#39;s pulse is above 120 beats per minute (bpm) for 30 minutes, then an alert action is displayed on user alert GUI  352  of  FIG. 3 . A corresponding finish action is displayed after a sweat test has completed on user alert GUI  352 . Network alert database  354  may include period  804 , which represents the length of time for a particular sweat test. For example, here period  804  is “120 seconds” for ElectrolyteTS Alert Database  802  indicating that a sweat test length may be 120 seconds. Network alert database  354  may include a scroll bar  806  for scrolling through the plurality of databases included in the network alert database. In some embodiments, network alert database  354  may contain test-specific algorithms (not shown) that, when executed, determine which one or more of the plurality of physiological sensors to use and compare the sensor data to the test-trigger data so as to determine whether or not the one or more test-triggering physiological conditions are present in the user. 
       FIG. 9A  illustrates an exemplary embodiment of network identification database  358  of  FIG. 3 . Network identification database  358  may, for example, store three types of data including one or more sweat test strip names (displayed in window  602 ), strip identification barcodes  606 , and related network alert databases  354 . Network identification database  358  is used in identification of sweat-test type.  FIG. 9B  illustrates an exemplary embodiment of wearable alert database  334  of  FIG. 3 . Wearable alert database  334  may be a specific database found in network alert database  354 , such as that of  FIG. 8 , for a sweat test type. 
       FIGS. 10A and 10B  illustrate exemplary embodiments of wearable sensor database  332  of  FIG. 3  and exemplary wearable sweat analysis sensor database  330  of  FIG. 3 , respectively. Wearable sensor database  332  and wearable sweat analysis sensor database  330  may store similar or identical data, as shown here. As shown, they may both contain date and time information, as well as one or more sensor data readings, such as pulse, blood pressure, sleep, sleep total in the past 24 hours, and body temperature. A distinguishing factor between these two databases is that wearable sensor database  332  stores sensor data collected during execution of wearable monitoring software  346 , while wearable sweat analysis sensor database  330  stores sensor data collected during execution of wearable action software  348 . In some embodiments, data stored in wearable sweat analysis sensor database  330  is displayed to a user via sweat analysis sensor data GUI  350  like that of  FIGS. 3 and 7B . 
       FIG. 11  illustrates an exemplary embodiment of wearable software method  1100  which may be executed, for example, by the wearable device  302  executing the wearable software  336 . As shown, at step  1105 , wearable identification software  340  is executed, and at step  1110 , the wearable manual choice software  344  is executed after the strip ID barcode  312  has been sent to network identification software  356 , and a matching sweat test strip name  602  and/or sweat-test type and network alert database  354  data have been sent back to wearable device  302 . At step  1115 , if the user has, for example, selected “Begin Sweat Test” button  612  on user start GUI  342 , then wearable action software  348  is executed. If a user has not selected “Begin Sweat Test” button  612  on user start GUI  342 , then at step  1120  user executes wearable monitoring software  346 , which keeps collecting sensor data until one or more test-triggering physiological conditions are present in the user, as determined by comparison with test-trigger data. Once it is determined that one or more test-triggering physiological conditions are present in the user, at step  1125  user executes wearable action software  348 , and the method ends. 
       FIG. 12  illustrates an exemplary embodiment of wearable identification software method  1200  (which may be performed by the wearable device  302  executing the wearable identification software  340 ) and a server identification software method  1202  (which may be performed by the server  304  executing the server identification software  356 ). Wearable identification software method  1200  and network identification software method  1202  work in parallel. Steps of wearable identification software method  1200  and network identification software method  1202  will be described herein together. At step  1205  of wearable identification software method  1200  user is allowed to identify strip identification barcode  312  of sweat test strip  310 . For example, a user may either manually enter strip identification barcode  312  using keyboard  608 , such as that of user start GUI  342  or initiate “Scan Sweat Test Strip” button  600  of the wearable device user start GUI  342 , which allows the user to use optical scanner  322  to read strip identification barcode  312  on sweat test strip  310 . Next, after strip identification barcode  312  data has been either scanned by optical scanner  322  or manually entered, related data is sent to network identification software  356  at step  1210 . At step  1215 , and now referring to network identification software method  1202 , strip identification barcode  324  receives data from wearable identification software  340 , and then, at step  1220 , compares the strip identification barcode data with data stored in network identification database  358 . Network identification database  358  may contain information regarding various sweat-test types, such as identifying barcode data and one or more network alert databases related to a particular sweat test type. At step  1225  of network identification software method  1202 , if a match is found in network identification database  358  that matches the sweat test strip name identified in window  602 , the method may proceed by sending that data to wearable identification software  340 . At step  1230  of wearable identification software method  1200 , wearable identification software  340  receives and displays the matching sweat test strip name on user start GUI  342 . At step  1235  of wearable identification software method  1200 , the user confirms that the matching sweat test strip name displayed on user start GUI  342  is for correct sweat test strip  310 . This data is then sent back to network identification software  356 . At step  1240  of network identification software method  1202 , network identification software  356  receives a notification of the user confirmation from wearable identification software  340  and then retrieves and/or copies network alert database  354  specific to the matching entry (sweat-test type) in network identification database  358  at step  1245 . Network alert database  358  may then be sent to wearable identification software  340 . At step  1250  of wearable identification software method  1200 , wearable identification software  340  may receive network alert database  358  specific to that sweat-test type, save the specific network alert database to wearable alert database  334 , and then may execute wearable device wearable manual choice software  344 , which ends methods  1200 ,  1202 , respectively. 
       FIG. 13  illustrates an exemplary embodiment of wearable manual choice software method  1300  (which may be performed by the wearable device  302  executing the wearable manual choice software  344 ). As shown, at step  1305  of wearable manual choice software method  1300  wearable device  302  user start GUI  342  is polled to determine whether the user has closed the user start GUI (step  1310 ). If the user did close user start GUI  342 , then wearable manual choice software  344  may execute wearable monitoring software  346  at step  1315  to start collecting sensor data and compare sensor data with wearable alert database  334  to determine whether or not one or more test-triggering physiological conditions are present in the user. If one or more physiological condition are present in the user, wearable action software  348  may be executed. If the user has not closed user start GUI  342 , then at step  1320  of wearable manual choice software method  1300 , wearable device  302  user start GUI  342  is polled to detect, at step  1325 , if user selected a “Begin Sweat Test” button  612 . If the user has not selected to manually begin the sweat test, then wearable manual choice software method  1300  loops back to step  1305  of polling user start GUI  342  to determine whether the user has closed the user start GUI. If a user has selected to manually begin a sweat test, then at step  1330  of wearable manual choice software method  1300 , wearable action software  348  is executed, and the method ends. 
       FIG. 14A  illustrates an exemplary embodiment of wearable monitoring software method  1400  (which may be performed by the wearable device  302  executing the wearable monitoring software  346 ). At step  1405  of wearable monitoring software method  1400 , sensor and wearable clock data is collected. At step  1410 , that data may be saved to wearable sensor database  332 . At step  1415 , the most recent sensor data entry from wearable sensor database  332  is retrieved, and then at step  1420 , that most recent data entry from the wearable sensor database is compared with wearable alert database  334  to determine whether there is a match (step  1425 ). If there is a match, at step  1430 , wearable action software  348  is executed. If there is no match, wearable monitoring software method  1400  loops back to step  1405 . In summary, wearable monitoring software method  1400  may collect sensor data and compare the most recent sensor data with one or more test-triggers to determine whether one or more test-triggering physiological conditions are present in the user. 
       FIG. 14B  illustrates an exemplary embodiment of wearable action software method  1435  (which may be performed by the wearable device  302  executing the wearable action software  348 ). As shown, at step  1440  of wearable action software method  1435 , user alert GUI  342  is displayed, and at step  1445 , the appropriate alert action for the matching data entry stored in wearable alert database  334  is executed. An example of an alert action is information and instruction that may be sent to user alert GUI  352  to provide an indication to a user when, e.g., their temperature is too high and/or to take a sweat test. An indication may include a message and related instructions. For example, the message and related instructions may include that the user is running a fever and that the user should test for interleukin 6 to test for a possible infection. At step  1450 , user places sweat test strip  310  as instructed by user alert GUI  352  and selects “Cellophane Layer Has Been Removed” button  706  of the user alert GUI once the user has removed the cellophane layer from sweat test strip  310 . At step  1455 , user starts wearable timer  316 , and then, at step  1460 , data from sensors and wearable clock  312  is collected via wearable action software  348 . At step  1465 , data is saved to wearable sweat analysis sensor database  330 , and then sent and displayed on sweat analysis sensor data GUI  350 . Through user interaction with sweat analysis sensor data GUI  350 , a user may review sensor data as well as wearable device  302  data. At step  1470 , if wearable timer  316  has reached a time equal to the period that was set for a sweat-test type, then at step  1475  an appropriate finish action for the matching data entry in wearable alert database  336  is executed. If the period of time as defined in wearable alert database  334  has not been reached at step  1470 , then wearable action software method  1435  loops back to step  1460 . 
       FIG. 15  illustrates an exemplary embodiment of a method  1500  of providing sweat health data to a user. Steps of method  1500  for providing sweat health data to a user are self-explanatory given the disclosure above. It is noted that this particular method is provided only for example and that the steps of method  1500  may occur in a different order and some steps may be omitted. 
     It is to be noted that any one or more of the aspects and embodiments described herein may be conveniently implemented using one or more machines (e.g., one or more computing devices that are utilized as a user computing device for an electronic document, one or more server devices, such as a document server, etc.) programmed according to the teachings of the present specification, as will be apparent to those of ordinary skill in the computer art. Appropriate software coding can readily be prepared by skilled programmers based on the teachings of the present disclosure, as will be apparent to those of ordinary skill in the software art. Aspects and implementations discussed above employing software and/or software modules may also include appropriate hardware for assisting in the implementation of the machine executable instructions of the software and/or software module. 
     Such software may be a computer program product that employs a machine-readable storage medium. A machine-readable storage medium may be any medium that is capable of storing and/or encoding a sequence of instructions for execution by a machine (e.g., a computing device) and that causes the machine to perform any one of the methodologies and/or embodiments described herein. Examples of a machine-readable storage medium include, but are not limited to, a magnetic disk, an optical disc (e.g., CD, CD-R, DVD, DVD-R, etc.), a magneto-optical disk, a read-only memory “ROM” device, a random access memory “RAM” device, a magnetic card, an optical card, a solid-state memory device, an EPROM, an EEPROM, and any combinations thereof. A machine-readable medium, as used herein, is intended to include a single medium as well as a collection of physically separate media, such as, for example, a collection of compact discs or one or more hard disk drives in combination with a computer memory. As used herein, a machine-readable storage medium does not include transitory forms of signal transmission. 
     Such software may also include information (e.g., data) carried as a data signal on a data carrier, such as a carrier wave. For example, machine-executable information may be included as a data-carrying signal embodied in a data carrier in which the signal encodes a sequence of instruction, or portion thereof, for execution by a machine (e.g., a computing device) and any related information (e.g., data structures and data) that causes the machine to perform any one of the methodologies and/or embodiments described herein. 
     Examples of a computing device include, but are not limited to, an electronic book reading device, a computer workstation, a terminal computer, a server computer, a handheld device (e.g., a tablet computer, a smartphone, etc.), a web appliance, a network router, a network switch, a network bridge, any machine capable of executing a sequence of instructions that specify an action to be taken by that machine, and any combinations thereof. In one example, a computing device may include and/or be included in a kiosk. 
       FIG. 16  shows a diagrammatic representation of one embodiment of a computing device in the exemplary form of a computer system  1600  within which a set of instructions for causing a control system, such as the WSA system  300  of  FIG. 3 , to perform any one or more of the aspects and/or methodologies of the present disclosure may be executed. It is also contemplated that multiple computing devices may be utilized to implement a specially configured set of instructions for causing one or more of the devices to perform any one or more of the aspects and/or methodologies of the present disclosure. Computer system  1600  includes a processor  1604  and a memory  1608  that communicate with each other, and with other components, via a bus  1612 . Bus  1612  may include any of several types of bus structures including, but not limited to, a memory bus, a memory controller, a peripheral bus, a local bus, and any combinations thereof, using any of a variety of bus architectures. 
     Memory  1608  may include various components (e.g., machine-readable media) including, but not limited to, a random access memory component, a read only component, and any combinations thereof. In one example, a basic input/output system  1616  (BIOS), including basic routines that help to transfer information between elements within computer system  1600 , such as during start-up, may be stored in memory  1608 . Memory  1608  may also include (e.g., stored on one or more machine-readable media) instructions (e.g., software)  1620  embodying any one or more of the aspects and/or methodologies of the present disclosure. In another example, memory  1608  may further include any number of program modules including, but not limited to, an operating system, one or more application programs, other program modules, program data, and any combinations thereof. 
     Computer system  1600  may also include a storage device  1624 . Examples of a storage device (e.g., storage device  1624 ) include, but are not limited to, a hard disk drive, a magnetic disk drive, an optical disc drive in combination with an optical medium, a solid-state memory device, and any combinations thereof. Storage device  1624  may be connected to bus  1612  by an appropriate interface (not shown). Example interfaces include, but are not limited to, SCSI, advanced technology attachment (ATA), serial ATA, universal serial bus (USB), IEEE 1394 (FIREWIRE), and any combinations thereof. In one example, storage device  1624  (or one or more components thereof) may be removably interfaced with computer system  1600  (e.g., via an external port connector (not shown)). Particularly, storage device  1624  and an associated machine-readable medium  1628  may provide nonvolatile and/or volatile storage of machine-readable instructions, data structures, program modules, and/or other data for computer system  1600 . In one example, software  1620  may reside, completely or partially, within machine-readable medium  1628 . In another example, software  1620  may reside, completely or partially, within processor  1604 . 
     Computer system  1600  may also include an input device  1632 . In one example, a user of computer system  1600  may enter commands and/or other information into computer system  1600  via input device  1632 . Examples of an input device  1632  include, but are not limited to, an alpha-numeric input device (e.g., a keyboard), a pointing device, a joystick, a gamepad, an audio input device (e.g., a microphone, a voice response system, etc.), a cursor control device (e.g., a mouse), a touchpad, an optical scanner, a video capture device (e.g., a still camera, a video camera), a touchscreen, and any combinations thereof. Input device  1632  may be interfaced to bus  1612  via any of a variety of interfaces (not shown) including, but not limited to, a serial interface, a parallel interface, a game port, a USB interface, a FIREWIRE interface, a direct interface to bus  1612 , and any combinations thereof. Input device  1632  may include a touch screen interface that may be a part of or separate from display  1636 , discussed further below. Input device  1632  may be utilized as a user selection device for selecting one or more graphical representations in a graphical interface as described above. 
     A user may also input commands and/or other information to computer system  1600  via storage device  1624  (e.g., a removable disk drive, a flash drive, etc.) and/or network interface device  1640 . A network interface device, such as network interface device  1640 , may be utilized for connecting computer system  1600  to one or more of a variety of networks, such as network  1644 , and one or more remote devices  1648  connected thereto. Examples of a network interface device include, but are not limited to, a network interface card (e.g., a mobile network interface card, a LAN card), a modem, and any combination thereof. Examples of a network include, but are not limited to, a wide area network (e.g., the Internet, an enterprise network), a local area network (e.g., a network associated with an office, a building, a campus or other relatively small geographic space), a telephone network, a data network associated with a telephone/voice provider (e.g., a mobile communications provider data and/or voice network), a direct connection between two computing devices, and any combinations thereof. A network, such as network  1644 , may employ a wired and/or a wireless mode of communication. In general, any network topology may be used. Information (e.g., data, software  1620 , etc.) may be communicated to and/or from computer system  1600  via network interface device  1640 . 
     Computer system  1600  may further include a video display adapter  1652  for communicating a displayable image to a display device, such as display device  1636 . Examples of a display device include, but are not limited to, a liquid crystal display (LCD), a cathode ray tube (CRT), a plasma display, a light emitting diode (LED) display, and any combinations thereof. Display adapter  1652  and display device  1636  may be utilized in combination with processor  1604  to provide graphical representations of aspects of the present disclosure. In addition to a display device, computer system  1600  may include one or more other peripheral output devices including, but not limited to, an audio speaker, a printer, and any combinations thereof. Such peripheral output devices may be connected to bus  1612  via a peripheral interface  1656 . Examples of a peripheral interface include, but are not limited to, a serial port, a USB connection, a FIREWIRE connection, a parallel connection, and any combinations thereof. 
     It should be apparent from the foregoing description that various example embodiments of the invention may be implemented in hardware or firmware. Furthermore, various exemplary embodiments may be implemented as instructions stored on a machine-readable storage medium, which may be read and executed by at least one processor to perform the operations described in detail herein. A machine-readable storage medium may include any mechanism for storing information in a form readable by a machine, such as a personal or laptop computer, a server, or other computing device. Thus, a machine-readable storage medium may include read-only memory (ROM), random-access memory (RAM), magnetic disk storage media, optical storage media, flash-memory devices, and similar storage media. 
     It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative circuitry embodying the principles of the invention. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in machine readable media and so executed by a computer or processor, whether or not such computer or processor is explicitly shown. 
     Although the various exemplary embodiments have been described in detail with particular reference to certain exemplary aspects thereof, it should be understood that the invention is capable of other embodiments and its details are capable of modifications in various obvious respects. As is readily apparent to those skilled in the art, variations and modifications can be affected while remaining within the spirit and scope of the invention. Accordingly, the foregoing disclosure, description, and figures are for illustrative purposes only and do not in any way limit the invention, which is defined only by the claims.