Technical Centre...

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Online Medical Assistant (OMA):
A Dynamic Collaborative Web-based

Medical Decision-Support Intelligent System

- Prompts the user to type in the data which the web-based system can recognize.
- Acquires users’ requests, and delivers them to the Server.
-  Presents the responses from the Server to the Client in the web pages.

-  Displays the public information of the web-based application.
-  Realizes the purview of functions the applications provide to the different roles of users.
-  Directs the user to walk through the whole web-based medical applications.
-  Provides the platform for the users to communicate with each other.
-  Provides the console for the Administrator and other co-operators to work with.

 The portal in Online Medical Assistant is actually the coordinator who merges the web-pages, medical engines and APIs into one web-based system.

3.1 The Roles

Acknowledgement 1
Preface 2
Figures list 6
Tables list 7
Introduction 8
Brief introduction on GPS 8
Objective of the project 9
Brief introduction of all the chapters 9
Chapter 1: Extracting and parsing the GPS NMEA messages 10
    1.1 GPS receiver 10
        1.1.1 Hardware interface of the Rikaline GPS module 11
        1.1.2 Software interface 11
        1.1.3 Transmitted messages 11
    1.2 NMEA 0183 protocol 11
        1.2.1 The “GPxxx” sentence codes with the short descriptions 12
        1.2.2 An example in “$GPGGA” NMEA sentence message 12
    1.3 Reading GPS strings 13
    1.4 Parsing the GPS message strings 13
        1.4.1 Dissecting the GPS message strings 14
        1.4.2 Software flowchart for extracting the required information 15
        1.4.3 Source code for the identification of the “$GPGGA” message strings 16
            1.4.3.1 The “$GPGGA” message string format 16
            1.4.3.2 The source code to identify the “$GPGGA” message strings 16
        1.4.4 Source code to extract the UTC time 17
            1.4.4.1 The format of the UTC time values in the “$GPGGA” message strings 17
            1.4.4.2 The source code to extract the UTC time values 17
        1.4.5 Source code to extract the latitude information from GPS message strings 18
            1.4.5.1 The format of the latitude values in the “$GPGGA” message strings 18
            1.4.5.2 The source code to extract the latitude values 18
        1.4.6 Source code to extract the latitude cardinal direction values from GPS message strings 19
            1.4.6.1 The format of latitude cardinal direction values in the “$GPGGA” message string 19
            1.4.6.2 The source code to extract the latitude cardinal direction values 19
        1.4.7 Extracting and parsing longitude information from GPS message string 20
            1.4.7.1 The format of longitude values in the “$GPGGA” message strings 20
            1.4.7.2 The source code to extract the longitude values 20
        1.4.8 Source code to extract the longitude cardinal direction values from GPS message strings 21
            1.4.8.1 The format of longitude cardinal direction values in the “$GPGGA” message string 21
            1.4.8.2 The source code to extract the longitude cardinal direction values 21
Chapter 2: Interfacing serially with GPS receiver 22
    2.1 EZ-USB Microcontroller 22
    2.2 UART 23
    2.3 Serial communication 23
        2.3.1 Asynchronous serial transmission 23
        2.3.2 Baud rate 24
    2.4 The RS232 standard 24
        2.4.1 Ports 25
        2.4.2 Devices 25
        2.4.3 Connections 26
    2.5 The reasons to use UART ICs instead of normal I/O ports 26
    2.6 The Intel8251A programmable communication interface 27
        2.6.1 General introduction of Intel 8251A 27
        2.6.2 Functions descriptions of Intel 8251A 28
            2.6.2.1 Data bus buffer block 29
            2.6.2.2 Read/Write control logic block 29
            2.6.2.3 Receiver buffer block 29
            2.6.2.4 Receiver control block 29
    2.7 Connecting the Intel8251A to the EZ-USB MCU 31
        2.7.1 The Intel8251A interface 31
        2.7.2 Programming the Intel8251A 31
            2.7.2.1 Mode instruction definition 32
            2.7.2.2 Asynchronous mode (Receive) 32
            2.7.2.3 Command instruction definition 34
            2.7.2.4 Status read definition 34
        2.7.3 The connection with RS232 35
    2.8 The Philips SC16C2552B serial communication interface 36
        2.8.1 SC16C2552B block diagram 37
           2.8.1.1 Data bus and control logic block 37
           2.8.1.2 Register select logic 37
           2.8.1.3 Internal registers 37
        2.8.2 Programmable baud rate generator 37
        2.8.3 Hardware navigation diagram 38
Chapter 3: Programming the EZ-USB 8051 MCU 40
    3.1 Interrupt for serial communication 41
        3.1.1 Setting up interrupts 41
        3.1.2 Serial interrupts 42
        3.1.3 Serial interrupt service routine 42
    3.2 Timer setting to generate baud rate 43
        3.2.1 TMOD 43
        3.2.2 Baud rate 43
    3.3 Serial port controls 44
        3.3.1 SCON 44
        3.3.2 TMOD 45
        3.3.3 Program routine to initialize serial communication 45
Chapter 4: LCD setting 46
    4.1 Introduction of HD44780-based LCD modules 46
        4.1.1 The HD44780 standard 46
        4.1.2 An example of hardware configuration 47
    4.2 Pin assignment 47
    4.3 Function description 48
        4.3.1 Registers 48
        4.3.2 Instruction set 49
        4.3.3 Visible DDRAM addresses 50
    4.4 Interfacing 51
    4.5 Functions 52
        4.5.1 Checking the busy status of the LCD 52
        4.5.2 Initializing the LCD 53
        4.5.3 Additional functions 54
            4.5.3.1 Cursor positioning 54
            4.5.3.2 Writing a character to LCD 54
            4.5.3.3 Display data on the LCD in the format of 2 lines 55
Chapter 5: The demo 57
    5.1 Description of the simulation process 57
    5.2 The demo’s source code 58
    5.3 Test 61
Conclusion 63
Summary 63
Outlook for further development 63
Bibliography 64

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Acknowledgement 
Preface II
Content V
Chapter 1: Introduction and Motivation 1
Chapter 2: Medical Diagnosis Expert System 4
    2.1 Introduction of Expert System 4
        2.1.1 The Structure of Expert System 4
            2.1.1.1 Knowledge Base 5
            2.1.1.2 Inference Engine 5
            2.1.1.3 Interface 6
        2.1.2 Knowledge Engineering 6
            2.1.2.1 Knowledge Acquisition 6
            2.1.2.2 Knowledge Representation 7
                2.1.2.2.1 Production Rules 7
                2.1.2.2.2 Semantic Networks 7
                2.1.2.2.3 Frame 8
            2.1.2.3 Validation of Expert System 9
                2.1.2.3.1 The concerns of validation 9
                2.1.2.3.2 The Validation Process 9
        2.1.3 Advantages and Limitations of Expert System 10
        2.1.4 Main Areas of Application of Expert System [4] 11
    2.2 Medical Diagnosis Expert System 11
        2.2.1 BBN-based diagnostic models [8] 11
        2.2.2 Relationships between Diagnosis and Symptoms 13
        2.2.3 Medical Diagnosis Expert System 13
        2.2.4 Introduction of the Available Diagnosis Expert System 14
            2.2.4.1 Mycin 14
            2.2.4.2 CADIAG-I/CADIAG-II 16
            2.2.4.3 An Intelligent Medical System for Diagnosis of Bone Diseases 17
                2.2.4.3.1 System Description [32] 17
                2.2.4.3.2 Knowledge Representation in XBONE 19
    2.3 Conclusion 20
Chapter 3: Fuzziness Theories 21
    3.1 Introduction 21
    3.2 Fuzzy set theory 22
    3.3 Linguistic variables 26
    3.4 Fuzzy control 28
    3.5 Fuzzy algorithms 30
    3.6 Fuzzy Expert Systems 32
Chapter 4: Acute Abdominal Pains 34
    4.1 Introduction 34
    4.2 Patient Data 37
        4.2.1 Anamnesis 37
        4.2.2 Physical Examination 38
        4.2.3 Tests 39
    4.3 Medical Knowledge 44
    4.4 Diagnosis 45
Chapter 5: MEDUSA 47
    5.1 Introduction 47
    5.2 Medical Knowledge 48
    5.3 MEUDSA 49
        5.3.1 Overview: 49
        5.3.2 Diagnostic Inference process of MEDUSA 51
            5.3.2.1 Overview 51
            5.3.2.2 Acquisition of Patient Data and Examination of Patient Data 51
            5.3.2.3 Interpretation of Patient Data 52
            5.3.2.4 The Hybrid Concept of the diagnostic inference procedure 52
            5.3.2.5 Display the Report of Diagnostic inference 53
    5.4 Data documentation and interpretation 54
        5.4.1 Membership function of the fuzzy sets 55
        5.4.2 Fuzzy Relations 55
    5.5 Automatic Knowledge Acquisition Component 56
    5.6 Special Case Acquisition Component 57
    5.7 Evaluation of Hypothetical diagnoses 58
    5.8 Hypothetical diagnoses Equations 59
Chapter 6: Online Medical Diagnosis Systems 61
    6.1 Introduction 61
    6.2 The Online medical Diagnosis Systems 61
        6.2.1 The AnalystTM 62
        6.2.2 YourDiagnosis 64
        6.2.3 MyElectronicMD 66
        6.2.4 Online Medical Assistant 68
    6.3 Summary 71
Chapter 7: Overview of Online Medical Assistant 73
    7.1 Introduction 73
    7.2 Technology Overview [53] 74
        7.2.1 The Microsoft .NET 74
        7.2.2 The .NET Framework 75
            7.2.2.1 Introduction of .NET Framework 75
            7.2.2.2 Common Language Runtime 75
            7.2.2.3 Class Libraries 76
    7.3 The 3-Tier architecture of Online Medical Assistant 76
        7.3.1 The Architecture of Online Medical Assistant 76
        7.3.2 The 3-tier architecture 77
        7.3.3 Presentation layer (GUI layer) 78
        7.3.4 Logic Layer 78
        7.3.5 Data Layer 78
            7.3.5.1 ADO.NET [58] 79
            7.3.5.2 The .NET Data Providers 80
            7.3.5.3 Connection strings 81
            7.3.5.4 Namespace Organization [58] 81
            7.3.5.5 The process of a DataSet populated by a DataAdapter object 82
            7.3.5.6 Data Binding 82
    7.4 Options of Client in .NET 83
        7.4.1 Introduction 83
        7.4.2 Win Form UI in C/S (Client and Server) 84
        7.4.3 ASP.NET UI in B/S (Browser and Server) 84
        7.4.4 Hybrid UI 85
    7.5 The Components of Online Medical Assistant 85
        7.5.1 Users 85
            7.5.1.1 Roles 85
            7.5.1.2 Functions 86
        7.5.2 Web-based decision-support expert system “MEDUSA” 87
            7.5.2.1 Architecture & business logic 87
                7.5.2.1.1 Automatic Knowledge Acquisition Component 88
                7.5.2.1.2 Interpretation of Patient Data Component 88
                7.5.2.1.3 Diagnostic Inference Component 88
                7.5.2.1.4 Case Searching Component 89
           7.5.2.2 The functions provided in the web-based MEDUSA 90
                7.5.2.2.1 Overview 90
                7.5.2.2.2 Cases Base 91
                7.5.2.2.3 Fill in 94
                7.5.2.2.4 Case Searching 98
                7.5.2.2.5 MedView 104
                7.5.2.2.6 MEDUSA Config 106   7.5.3  The portal 111
                7.5.3.1 Introduction 111
                7.5.3.2 Login 112
                7.5.3.3 Forum 112
                7.5.3.4 Feedback 114
                7.5.3.5 Website configuration Interface 115
Chapter 8: Implementation of Online Medical Assistant 116
    8.1 Introduction 116
    8.2 Implementation of Online Medical Assistant 117
        8.2.1 Automatic knowledge acquisition component design. 117
        8.2.2 Interpretation of Patient Data Component design. 122
        8.2.3 Diagnostic Inference Component design. 128
        8.2.4 Case Searching Component design 134
        8.2.5 The API for update medical knowledge and system parameters design 137
        8.2.6 The user membership design 140
        8.2.7 Website configuration API design 144
Chapter 9: Conclusion 147
    9.1 Summary 147
    9.2 Outlook 148
Appendix 150
    Appendix-A: Bibliography 150
    Appendix-B: Figures list 153
    Appendix-C: Milestones and Time Flow 157
    Appendix-D: XML files index 158

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