Patent Document

PRIORITY CLAIM 
     This application claims priority from co-pending provisional application Serial No. 60/162,876 filed on Nov. 1, 1999 which is incorporated by reference herein. 
     Reference to Related Applications 
     This application relates to the following applications U.S. Ser. No. 09/603,604, entitled “Web Simulator”, filed Jun. 26, 2000; U.S. Ser. No. 09/603,045 entitled “Patient Simulator”, filed Jun. 26, 2000; U.S. Ser. No. 09/603,422, entitled “Morphing”, filed Jun. 26, 2000. 
    
    
     BACKGROUND 
     Desktop computer programs such as flight simulators, word-processors, and spreadsheets quickly respond to user input. Providing this kind of inter-activity over the Internet, however, has posed something of a challenge. This challenge stems, in part, from the simple communication model that describes most Internet traffic: clients (e.g., web-browsers) request pre-written web pages from servers, and the servers send the requested pages back for display. 
     Programmers have developed a number of different techniques to make web pages more inter-active. For example, some web pages include, or refer to, programs known as “applets.” When a browser receives a web-page featuring an applet, the browser executes the applet instructions, for example, to receive user input, change a browser GUI (Graphical User Interface) display, and communicate with the server providing the web-page. Some applets, however, include a large number of instructions and can require a significant amount of time to travel over the Internet to a user&#39;s browser. 
     Another technique for making web pages more responsive to users involves dynamic generation of web pages by servers. For example, PHP (Personal Home Page), ASP (Active Server Page), and CGI (Common Gateway Interface) scripts can dynamically produce a web page based on script instructions and variables. Script processing, however, adds yet another task to web-servers faced with handling large bursts of browser requests for information. 
     SUMMARY 
     In an aspect, the invention features a method of simulating an encounter with a virtual patient including displaying an image of the virtual patient, receiving user selection of an area of the image of the virtual patient, and transmitting signals that associated with the user selected area of the image, the signals being based on the state of the virtual patient. 
     Advantages of the invention will become apparent in view of the following description, including the figures, and the claims. 
    
    
     The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims. 
     DESCRIPTION OF DRAWINGS 
     Brief Description of the Drawings 
     FIGS. 1 to  5  are diagrams illustrating a network application architecture. 
     FIG. 6 is a flowchart of a server process for providing an application to different network users. 
     FIG. 7 is a flowchart of a client process for presenting a user interface to network users. 
     FIGS. 8-14 are screenshots of a user interface that presents a virtual patient. 
     FIGS. 15A and 15B are listings of statements associating multimedia files with different virtual patient characteristics. 
     FIG. 16 is a flowchart of a process for providing a virtual patient. 
     FIG. 17 is a diagram of a virtual patient simulator. 
     FIG. 18 is a flowchart of a process for evolving a medical condition. 
     FIG. 19 is a listing of statements defining an evolution. 
     FIG. 20 is a listing of statements defining a migration. 
     FIG. 21 is a flowchart of a process for changing multimedia presentations associated with a virtual patient. 
     FIG. 22 is a diagram illustrating a change of a multimedia presentation associated with a virtual patient. 
     FIG. 23 is a flowchart of a process for morphing a virtual patient. 
     FIG. 24 is a listing of statements defining a morphing operation. 
     FIG. 25 is a flowchart of a process for providing virtual patient responses to questions. 
     FIG. 26 is a listing of statements defining virtual patient answers to questions. 
     FIG. 27 is a listing of statements defining a response to a lab test. 
     FIG. 28 is a listing of statements defining an action. 
     FIG. 29 is a listing of statements defining a response to physical examination. 
     FIG. 30 is a listing of statements defining a computation. 
     FIG. 31 is a diagram of a virtual patient simulator using the network application architecture. 
    
    
     Like reference symbols in the various drawings indicate like elements. 
     DETAILED DESCRIPTION 
     I. Network Architecture 
     A. Introduction 
     FIG. 1 shows a system  100  that uses the Internet  104  as a vehicle for providing complex, interactive applications to a large number of network users operating ordinary web-browsers  102   a ,  102   b  (e.g., Microsoft™ Internet Explorer™). The architecture  100  provides each user with a different “instance” of the application. That is, each user perceives an application program responsive to that user&#39;s input, much like an ordinary program residing on the user&#39;s personal computer. In the scheme shown in FIG. 1, the web-browsers  102   a - 102   b  need not receive the actual application instructions, but instead receive interface instructions for constructing a browser display and presenting different user interface controls. The interfaces are like application facades with the real application instructions residing on a remote system. 
     As shown in FIG. 1, the system  100  includes a network server  106  that stores the “state”  112  of each application instance. State data  112  can include the current values of different variables used by an application. A single application can handle more than one “instance.” For example, an application can read an instance&#39;s state data  112 , perform some processing, update and store the instance&#39;s state data  112 , and move on to another instance&#39;s state data. 
     Conceptually, state data  112  represents the intersection between local area network computers  118   a - 118   c  running different copies of an application  120   a - 120   d  and a process  108  that dynamically constructs web pages for each application instance. Applications  120   a - 120   d  continually operate and update the state data  112 . Independently, the server  106  can process user input and prepare browser instructions (e.g., HTML (Hypertext Markup Language)) for each instance. 
     For example, in one embodiment, the applications  120   a - 120   d  provide users with a simulation of a patient medical exam (i.e., simulation of a medical exam to a “virtual” patient). The simulation enables network users to interact with web-page controls (e.g., buttons, icons, and text fields) to examine, diagnose, and attempt to return a virtual patient to health. For this application, the state data  112  can include a virtual patient&#39;s vital signs (e.g., heart rate, pulse, and weight), images or references to images of the virtual patient&#39;s current appearance, medical orders and queries received from the user, and other information. The medical simulation applications  120   a - 120   d  continually update the state data  112  for a patient to reflect the virtual patient&#39;s health. For example, the medical simulation applications  120   a - 120   d  may slowly decrease a virtual patient&#39;s weight over time when a user prescribes a diet. While the medical simulation applications  120   a - 120   d  run behind the scenes, an interface generator  110  uses the state data  112  to construct browser instructions that display an appearance of the user&#39;s virtual patient and provide information (e.g., a medical history) requested by the user. 
     The network system of FIG. 1 can handle the large numbers of users that typically visit popular web sites. For example, pooling the computational resources of the LAN computers  118   a - 118   c  enables the system  100  to support a large number of application instances. Additionally, the system  100  enables a network administrator to add computers to a local area network to further increase system “horse-power”. Additionally, the server  106  does not need to deliver copies of the application  120   a - 120   d  to each network user. This can reduce network traffic. Keeping the application instructions on local area network machines also enables a site manager to easily replace and modify the applications, for example, to fix bugs or provide new features. This also prevents users from easily copying the programs. The system  100  also separates interface generation (server  106 ) from the actual “number crunching” (i.e., execution) of the application  120   a - 120   d . This separation enables the server  106  to easily customize each user&#39;s interface. For example, more sophisticated computers or computers featuring faster network connections can receive interface instructions for more elaborate multimedia presentations. 
     B. Illustration of Operation 
     FIGS. 2-4 illustrate operation of the system  100 . In FIG. 2, a user navigates browser  102   a  to the server  106 , for example, by specifying the server&#39;s URL (Universal Resource Locator) (e.g., www.medicalsimulator.com). In response, as shown in FIG. 3, the server  106  initializes state data  112  for a new application instance. Initializing the state data  112  may include generating an identifier for the instance, for example, an identifier based on the IP (Internet Protocol) address of the user. The server  106  also selects an application  120   a - 120   d  to handle the instance. For example, the server  106  may select a particular application  120   a - 120   d  based on the current load of the different applications (e.g., load-balance based on how many different instances each application currently handles), the speed of the local area network computer running the application, and so forth. 
     As shown in FIG. 4, after initialization, communication with the user and execution of the application can proceed independently of one another, for the most part. For example, an application  120   b  can read and update state data  112  regardless of how frequently the server  106  transmits or receives data from application  120   a . Thus, even if a user directs their browser to a different site, the application instance can persist and, potentially, continue. To continue the patient simulation example, even though a user visits a different site to check on stock prices, their patient&#39;s ailment will progress. The system does not strictly impose this independence. For example, the server  106  can control the application speed based on the speed of a users connection or how frequently the user interacts with an interface. The server  106  can also store the state data  112  to freeze an application instance for later use. 
     The server process  108  that handles user interaction can communicate with the “back-end” via the server  106  database  112 . For example, the process  108  and application  120   b  can communicate using a technique known as “handshaking.” Thus, a user may interact with an interface control (e.g., a form field on an HTML page) displayed by their browser to send user input to the server  106 . The server  106  can write this input into the state data  112  for the user&#39;s application instance and set a handshake flag indicating the input requires application  120   b  processing. After the application  120   b  finishes its processing it can reset the handshake flag. The interface generator  110  may wait for the application  120   b  to reset the handshake flag before constructing a new interface. 
     State data  112  may be distributed across different LAN computers  108   a - 108   c  instead of residing solely on the server  106 . For example, as shown in FIG. 5, each application copy may maintain information for each instance locally. The interface generator  110  can retrieve the state data  112  from the LAN computers when constructing an interface. 
     C. Client/Server Operation 
     FIG. 6 shows a flowchart of a server operation  130 . As shown, the server identifies  132  different applications running on the LAN computers. For example, the server may run a process or thread that establishes a connection (e.g., a “socket” connection) with each application that announces itself to the server. Though shown in FIG. 6 as initial activity of the server, identifying  132  available applications on the LAN computers can continue over time as different applications and LAN computers go on and off-line. 
     After receiving  134  a request from a user for an instance of an application, the server  106  selects  136  an application to handle the instance and initializes  138  the state data for that instance. Thereafter, the application can read and/or update the state data, for example, by issuing database commands over an ODBC (Open Database Connectivity) connection. The server also uses the state data to generate interface instructions that control the appearance of the application on a user&#39;s browser  142 ,  144 . 
     The server  106  can construct an interface using a variety of techniques. For example, the interface generator can use PHP (Personal Home Page), ASP (Active Server Page), or CGI (Common Gateway Interface) scripts to dynamically generate HTML or XML (Extensible Markup Language) interface instructions. Typically, these pages will include instructions that read state data for an instance (e.g., by looking up the instance identifier), and, based on the state data values, construct a page of sounds, graphics, and user interface controls. The user interface controls may include “form field” controls and/or a “submit” button that receives user input and transmits  146  this input to the server for processing (e.g., www.medicalsimulator.com? action=CPR). The interface may also include instructions that periodically issue a request to the server  106  for an update. 
     As shown in FIG. 7, a browser (or other client) receives and processes the generated instructions or data  152  to present the specified pictures, text, or sounds to a user. Though the browser receives discrete sets of web-page instructions, the resulting sequence of displays is nearly indistinguishable from that of an ordinary desktop application. The instructions may also feature applets  154 , ActiveX controls, or other programmatic instructions. These instructions can provide fast, direct updating of multimedia elements of an interface. For example, instead of requesting reconstruction of an entire new set of interface instructions, an applet may establish a JDBC (Java Database Connectivity) connection to the data stored on the server  106  and continually replace an image on the interface with a new image. For example, the applet may quickly present a series of images of a patient when the patient&#39;s health rapidly improves. 
     The system  100  described in FIGS. 1-7 can be used to provide a wide variety of applications. For example, the system  100  can be used to provide a simulation of a virtual patient to different users on the Internet. 
     II. Virtual Patient Simulation 
     A. User Interface 
     FIGS. 8-14 show screenshots of a user interface presented by a virtual patient simulator. The simulator provides an interactive, multimedia simulation of a medical examination. The user, acting as a doctor, can examine and interview the virtual patient, track vital signs, enter orders and recommendations, and conduct other simulated activities. Chronic and acute conditions evolve and disappear over time as the virtual patient&#39;s health responds to a user&#39;s treatments or lack thereof. 
     The simulator provides extensive medical education and reference information such as pharmacological references (e.g., PDR (Physician&#39;s Desk Reference) notes), videos and images illustrating proper use of products and procedures, medical dictionary entries (e.g., from Gray&#39;s Anatomy), and links to medical information on the Internet. 
     The virtual patient and reference information provide an engaging education experience for medical students, medical professionals seeking continuing medical education, and other consumers. The simulation enables users to experiment with different patient treatments and quickly witness the impact of their recommendations on the virtual patient. 
     As shown in FIG. 8, a user interface  800  provides a graphic model  802  of a virtual patient. The simulation changes depiction of the model  802  based on the virtual patient&#39;s state. For example, the model image may show the hips of the model  802  growing as the virtual patient&#39;s weight increases. Similarly, the model&#39;s  802  complexion color may sallow due to some illness. 
     Interface  800  controls  808   a - 808   b  enable a user to view both the front and back sides of the virtual patient. Other controls  808   c - 808   d  enable the user to select whether the virtual patient model  802  appears clothed or unclothed. The user interface  800  also displays vital statistics  806  such as blood pressure, pulse rate, temperature and so forth. 
     As shown, the interface  800  provides a palette  810  of controls  810   a - 810   h  that correspond to different examination techniques. As shown, the palette  810  includes controls  810   a - 810   h  that present a cardiology EKG  810   a  of the virtual patient, representations of the virtual patient&#39;s extremities  810   c  (e.g., hands and feet), radiology images  810   d , microscopy images  810   f , and neurological information  810   e  such as images showing the virtual patient&#39;s gait or a “recording” of the virtual patient&#39;s voice. 
     As shown, a user has selected a virtual stethoscope tool  810   g  from the palette  810 . For virtual stethoscope  810   g  use, the interface  800  presents front  812  and back  814  images of the virtual patient&#39;s torso. As shown, the interface  800  also displays “hot spots”  816 ,  818 , and  820 . Each hot spot  816   a - 816   d ,  818   a - 818   d ,  820   a - 820   d  maps to a particular location on the virtual patient&#39;s torso. Selecting (e.g., using a mouse) one of the hot spots  816   a - 816   d ,  818   a - 818   d ,  820   a - 820   d  simulates placement of a stethoscope on the hot spot and produces corresponding sounds on a computer&#39;s audio output (e.g., speakers). Just as in a real-life medical exam, use of the virtual stethoscope can identify breathing or cardiac abnormalities. For example, using the virtual stethoscope to listen at hot spots  816   a - 816   d  produces sounds of the virtual patient&#39;s heart. More particularly, hot spot  816   a  corresponds to the second right intercostal space. Thus, selecting hot spot  816   a  causes the simulator to produce sounds corresponding the virtual patient&#39;s aortic valve. Other hot spots “listen” to other bodily functions. For example, hot spots  818   a - 818   d  correspond to the virtual patient&#39;s renal arteries while hot spots  820   a - 820   d  correspond to the virtual patient&#39;s lungs. The sounds produced vary according to the state of the virtual patient. That is, the cardiac rhythms presented by the simulator can depend on the blood pressure, pulse, and age of the virtual patient. 
     Instead of “listening” to the virtual patient using the virtual stethoscope  810   g , a user may choose to virtually percuss (i.e., simulate a gentle thumping of a patient&#39;s body) the virtual patient. Medical professionals often use percussion to identify abnormal masses. Selecting the percussion tool  810   h  may display a different collection of hot spots than those shown in FIG.  8 . Selecting one of the hot spots causes the simulator to produce sounds corresponding to percussion of the corresponding area. Again, the sounds produced depend on the state of the virtual patient. For example, percussion of a healthy virtual patient&#39;s abdomen often produces a resonant echo while percussion of the abdomen of a virtual patient having a swollen liver may sound flatter. 
     As shown in FIG. 9, the interface palette also includes a fundascope/odoscope tool  810   b  for viewing images of the virtual patients eyes  902 , retina  904 , ears  906   a - 906   b , nose (not shown), and throat  908 . Descriptions  910  may accompany these images. Again, the virtual patient images  902 - 908  are not the same for each virtual patient, but are instead based on the virtual patient&#39;s current health. For example, a virtual patient suffering from retinopathy may cause display of a retinal image  904  depicting strands of white fibrous tissue? Similarly, a virtual patient suffering from an inner ear infection may cause display of an ear image  906   a - 906   b  depicting a reddened tympanic membrane. 
     As shown in FIG. 10, a user can view graphs  1000  of a virtual patient&#39;s vital statistics and lab tests over time. The graphs  1000  enable the user to quickly grasp the effects their treatment has had on the virtual patient and identify correlations between movements of different charted variables. 
     As shown in FIG. 11, the simulator provides each virtual patient with a patient history  1100 . The history  1100  may include clues to potential ailments. The history  1100  also may chronicle changes in the virtual patient&#39;s health over time. 
     As shown in FIG. 12, the interface  1200  enables a user to ask the virtual patient a question, for example, by typing questions into a text field  1204 . Just as in real-life, questioning a patient can quickly yield information needed to formulate and confirm a diagnosis. The simulator generates a virtual patient response  1206  for each question asked  1204 . Additionally, the simulator can adjust the facial expression  1202  of the virtual patient to portray a patient&#39;s emotional response to a question  1204 . Potentially, the virtual patient&#39;s expression  1202  may be as telling as their actual response. As shown, the questions  1204  and answers  1206  take the form of text, however, in other embodiments, speech recognition and speech synthesis handle question input and answer output. Again, the response of the virtual patient can depend on state data. For example, the patient&#39;s response to “How&#39;s your vision” can differ for a healthy patient and a patient suffering from diabetes. 
     As shown in FIG. 13, the interface  1300  enables a user to make different interventions. For example, the user can make a diagnosis  1302 . The simulator may provide feedback when a user correctly diagnoses a virtual patient ailment. The user may also order different lab tests  1306 . The simulator returns lab results based on state data of the virtual patient. The lab results can provide clues to ailments afflicting the virtual patient. 
     A user may also prescribe an over-the-counter or prescription medication  1304  or order a lifestyle change such as a change in diet. Such interventions can alter the state of the virtual patient. Of course, as in real-life, such interventions can have beneficial and/or problematic results and can cause predictable and unpredictable side-effects. 
     As shown in FIG. 14, the interface permits users to control “virtual time”. That is, a user can speed up the simulation to see a long-term illness unfold in a matter of minutes or slow down the simulation to see a quick-striking illness slowly unfold. 
     FIGS. 8-14 illustrate an interface that provides users with techniques for monitoring and treating a virtual patient. The screenshots shown, however, are merely an example of one possible interface. A wide variety of other user interface presentations can take advantage of the techniques described herein. 
     B. Multimedia Presentation of a Virtual Patient 
     FIGS. 15A-15B show data structures  1502 - 1538  that control multimedia presentations provided by the interface. For example, the “Patient Views” data structure defines different patent model images. The multimedia fields MMFile 1 , MMFile 2 , MMFile 3 , and MMFile 4  of the “Patient Views” data structure specify the file locations of previously generated model images corresponding to clothed-front-side, clothed-back-side, unclothed-front-side, and unclothed-back-side model views, respectively. These images correspond to controls  808   a - 808   d  in FIG.  8 . Changing the files referred to can change the presentation of the virtual patient. For example, changing the file associated with MMFile 1  from aprime.jpg to slim_prime.jpg can cause the user interface to present a slimmer clothed-front-side image of the virtual patient. 
     Similarly, the Chest “Front Auscultation” data structure  1510  defines multimedia presentations for use of the virtual stethoscope (see FIG.  8 ). Data structure elements Sound 1 , Sound 2 , Sound 3 , and Sound 4  correspond to the sounds produced by selecting hot spots  816  in FIG.  8 . Again, changing the sound files associated with Sound 1 , Sound 2 , Sound 3 , or Sound 4  change the sound file played. 
     As shown, the data structures specify multimedia presentations for front auscultation  1506  and percussion  1508  of the virtual patient&#39;s abdomen, front  1510  and back  1512  auscultation of the virtual patient&#39;s chest, and percussion of the virtual patient&#39;s back  1514 . The data structures also specify multimedia presentations for a virtual patient EKG  1516 , examination of extremities  1518 - 1522 , examination of head, eyes, ears, nose, and throat  1524 - 1530 , neurological examination such as speech  1532  and gait  1534 , and radiology images of the virtual patient&#39;s chest  1536  and skull  1538 . 
     Though the data structures listed in FIGS. 15A and 15B include the term “objects”, the data structures need not be implemented using an object-oriented methodology. 
     C. Generating a Virtual Patient 
     In some embodiments, the simulator operates by interpreting data structures encoding different virtual patient characteristics. For example, a developer can code data structures that define the progression of different medical conditions. Procedures interpret the data structures to present a virtual patient. Interpretation of the data structures can include accessing and modifying virtual patient state data. Such state data can include vital statistic variables (e.g., pulse rate, age, gender, weight, systolic blood pressure, diastolic blood pressure, respiration, and temperature), laboratory test variables, the state of different conditions, and other developer defined variables. 
     With some exceptions, described below, different virtual patient characteristics can proceed independently of one another. For example, different medical conditions may read and update the state data of the virtual patient and act without knowledge of other conditions. Thus, a virtual patient can suffer from a strange mix of symptoms caused by different conditions. To successfully treat the patient, the user learns to untangle the different symptoms into individual, treatable illnesses. 
     FIG. 16 shows a process  1600  for providing a virtual patient. Initially, a developer defines  1602  a domain of potential virtual patient characteristics. For example, the developer can define data structures for different ailments that evolve over time (“evolutions”) that are computed by mathematical modeling of other variables (“computations”), for random fluctuations in variables (“migrations”), and for different treatments (e.g., drugs) a user can prescribe. 
     A patient generation process generates  1604  a virtual patient by selecting virtual patient characteristics from the domain of potential virtual domain characteristics. For example, the patient generator process  1604  may generate one patient that has the potential for diabetes and may later generate another patent that has the potential for osteoporosis. Patients are not limited to a single characteristic but can instead have different mixes of potential ailments. 
     Patient generation  1604  may feature interpretation of a patient generation script that specifies different probabilities of virtual patient characteristics occurring in the virtual patient. Patient generation  1604  may also initialize variables to specific values. The script may identify a particular medical area. For example, a script that generates a virtual patient having osteoporosis and cataracts may belong to a “geriatric” medical area. Additionally, the script may differ for men and women. 
     The script used to generate a patient may be randomly selected from all scripts. Alternatively, a user may specify a medical area and restrict patient generation to those scripts belonging to that area. Patient generation  1604 , however, can occur without a script. For example, a patient generator can produce a virtual patient having a random selection of medical characteristics. 
     After generating  1604  the virtual patient, a simulator presents  1606  the virtual patient to the user based on virtual patient state data (e.g., vital statistic variables and lab test variables) and updates  1608  the state data by interpreting the data structures defining virtual patient characteristics. 
     FIG. 17 shows a diagram of a simulator  1700 . In addition to the user interface  1722  (see FIGS.  8 - 14 ), the simulator  1700  includes procedures  1701  that interpret data structures defining the virtual patient. The procedures  1701  handle questioning  1702  of the virtual patient (e.g., review of systems (ROS) questions), responding to lab test  1704  requests from the user, responding to physical examinations  1706  requested by the user, and responding to orders  1708  issued by the user. 
     The procedures  1701  also modify state data of the virtual patient by interpreting evolution  1712  and migration  1714  data structures, and computation  1715  data structures. Evolutions  1712  control variables to reflect some condition. For example, a diabetes evolution will cause the virtual patient to gain weight. By contrast, migrations  1714  randomly vary variables within specified bounds. The combination of migrations  1714  and evolutions  1712  force a user to distinguish between significant and insignificant variations in vital signs and lab tests results. Computations  1715  allow mathematical modeling of system variables based on value(s) of other system variable(s). 
     As shown, the simulator  1700  also provides multimedia files  1716  such as video (e.g., MPEG (Motion Pictures Experts Group)) files, sound files, and picture (e.g., JPEG (Joint Photographers Experts Group)) files. These files may include instructional references material and/or multimedia features used to present the virtual patient. The state data  1718  can include references or copies of the multimedia files that reflect the current state of the patient (see FIGS. 15 a  and  15   b ). 
     Trigger and morphing procedures  1710  can update the multimedia files associated with the virtual patient based on logic operating on variables. For example, a trigger  1710  procedure may change an image of a patient&#39;s torso from “normal_torso.jpeg” to “slim_torso.jpeg” if the patient&#39;s weight falls under one-hundred fifty pounds. 
     FIG. 18 depicts evolution  1800  of a medical condition. Evolutions alter variable values and/or lab test results to reflect some condition. The evolution  1800  has several modes: an initial mode  1802  before any events (e.g., treatments by the user and/or other state data) initiate the evolution, an interim mode  1808  when the evolution temporarily lies dormant, and an active mode  1814  when the evolution changes  1818  the virtual patient&#39;s state data. 
     In addition to programming different events or criteria that start an evolution  1804  and the state data affected by an active  1814  condition, a programmer can identify different inhibiting events or criteria  1806 ,  1810  that halt progression of the evolution. For example, an order for “diet and exercise” may halt many different illnesses. Thus, identification of disease warning signs and prompt treatment can prevent the onset of a disease. 
     A programmer can also control the dominance  1816  of an evolution over other evolutions. For example, a first evolution may elevate blood pressure while a second evolution decreases blood pressure. If so desired, a programmer can code the first evolution to cancel the second evolution. 
     FIG. 19 shows a listing of statements defining an evolution  1900  for “Diet and Exercise”. Such an evolution can regulate vital signs in a manner beneficial to a virtual patient&#39;s health. The evolution  1900  begins when a user orders “Diet and Exercise”. After an interim period of four days  1906 , the evolution begins decreasing a virtual patient&#39;s weight  1910   a  and glucose levels  1910   b - 1910   d . While nothing can inhibit  1908  the effects of exercise, the evolution  1900 , as shown, does not directly cancel any other evolutions  1908 . While recommending “Diet and Exercise” does not directly cancel other evolutions, the evolution&#39;s  1900  control over weight and glucose variable values may inhibit a disease triggered by a particular weight or glucose level. 
     FIG. 20 shows a listing of statements that define a migration. Like an evolution, a migration adjusts the values of variables and other state data. Unlike an evolution the migration adjusts the state data in a more random manner to represent ordinary fluctuations in measurements. As shown, the “Activated clotting time” migration maintains the value  2002  of the corresponding “ACT” variable between “114” and “186” from a starting point of “143”. The migration operates once a “virtual” minute  2004 . The migration is not purely random, but instead implements a “random walk” having changes that amount to, in this case, a 4% increase or decrease  2006  at most. 
     FIG. 21 shows a process  2100  for producing a trigger. Triggers implement conditional statements. Triggers can not affect variables but rather affect multimedia or text objects based on the values of variables. Typically, a programmer can use triggers to substitute different multimedia presentations of a virtual patient based on satisfaction of some criteria. As shown, the process  2100  tests for satisfaction of some criteria  2102 . For example, the trigger may test the variables and/or the issuance of some order by the user (e.g., prescribing a drug). If satisfied, a trigger makes a specified alteration  2104 . 
     FIG. 22 shows data structure statements  2202  that define the sounds associated with virtual percussion of the back of the virtual patient. Each sound corresponds to one of the hot spots (see FIG.  7 ). A trigger  2204  can change the sound of one of the hot spots. As shown, the trigger substitutes references to Wav Files/Percussion/percussThin.wav for the previous value of Sound 1  (“PercusResonant.wav”) if the weight of the patient falls between “100” and “120” pounds. 
     Like triggers, morphing can alter the image used to portray the virtual patient. FIG. 23 shows a flowchart  2300  of a process for morphing an image of a patient. Based on a specified maximum and minimum variable value, the process  2300  uses a current value of a variable to determine an offset into a video file, such as a file slowly morphing the image of a virtual patient from a slim to heavyset appearance. The process presents the image corresponding to the offset. The video file provides a fine gradation of images thus can present smooth and gradual changes in the virtual patient. 
     FIG. 24 shows a listing of statements defining a morph. The “weight” morph is based on the weight variable and extends from a minimum weight of 164 to a maximum weight of 184. Thus, if a patient weights “174”, the corresponding offset would index halfway through a video file and present the corresponding image. 
     FIG. 25 shows a flowchart of a process  2500  that provides virtual patient responses to different questions posed by the user (see FIG.  12 ). After receiving a question  2502 , the process searches  2502  for a corresponding entry in a collection of questions. For example, the process may identify key words in the question by eliminating articles and prepositions and search for a stored question having the identified key words. The keywords may also include Boolean criteria (e.g., this is the response when the query includes word a AND word b but NOT word c. The process  2500  may alternatively use other natural language processing techniques to match a user&#39;s question with a particular response. After finding an entry, the process presents  2506  the response corresponding to the question. 
     FIG. 26 shows a listing of statements used to define a “Review of Systems” response. The statements include a question, answer, keywords identifying the entry, an entry for the log, and a facial expression. 
     FIGS. 27-29 show data structures for lab tests, user orders, and physical examinations, respectively. FIG. 30 shows a data structure for a computation, where the MethodName “ComputeBPDiastolic” refers to a compiled function in a DLL. 
     A computation enables the simulator to use complex mathematical models of a virtual patient. The computation enables a programmer to specify condition statements (e.g., if (temperature&gt;100)) and/or relationships between variables (e.g., systolic pressure=diastolic pressure). 
     All components of the virtual patient simulator may reside on the same computer. In other embodiments, the virtual patient simulator uses the architecture shown in FIGS. 1 to  7  to provide different Internet users with a simulation of a patient medical exam. 
     Briefly, the simulator procedures  120  operate on different state data and different data structures for different virtual patients. Each virtual patient has an entry in a patient table  3110 . Each virtual patient can correspond to a single application instance, though many different clients can simultaneously engage the same patient for group treatment, discussion, and education. A patient identifier may key each patient table entry  3110 . 
     As shown the database  106  includes tables that track the current loads  3112  of different LAN virtual patient simulators, vital statistic variables  3120 , lab variables  3126 , pending physician orders  3116  and questions  3118  and their corresponding responses  3122 ,  3124 . The database  106  can also store the data structures identifying the images and sounds  2904  that portray the virtual patient&#39;s current health. 
     Embodiments 
     The techniques described here are not limited to any particular hardware or software configuration; they may find applicability in any computing or processing environment. The techniques may be implemented in hardware or software, or a combination of the two. Preferably, the techniques are implemented in computer programs executing on programmable computers that each include a processor, a storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and one or more output devices. Program code is applied to data entered using the input device to perform the functions described and to generate output information. The output information is applied to one or more output devices. 
     Each program is preferably implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. 
     Each such computer program is preferable stored on a storage medium or device (e.g., CD-ROM, hard disk or magnetic diskette) that is readable by a general or special purpose programmable computer for configuring and operating the computer when the storage medium or device is read by the computer to perform the procedures described in this document. The system may also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner. 
     Other embodiments are within the scope of the following claims.

Technology Category: g