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A distributed microprocessing system for laboratory computing

J R Bourne

    Medical Instrumentation
    |November 1, 1980
    PubMed
    Summary
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    This study introduces a distributed processing system for biomedical research, enhancing microprocessor efficiency and cost-effectiveness. The system utilizes a minicomputer host and microcomputer slaves for data acquisition, processing, and display in medical labs.

    Area of Science:

    • Biomedical Engineering
    • Computer Science
    • Laboratory Automation

    Background:

    • Traditional laboratory systems often face limitations in processing power and cost-efficiency.
    • Integrating microcomputers with a central host offers a scalable solution for complex research tasks.
    • The need for efficient data handling in biomedical research drives the development of advanced computing architectures.

    Purpose of the Study:

    • To present the design and implementation of a distributed processing system for biomedical research.
    • To demonstrate the increased efficiency and cost-effectiveness of microprocessor utilization in research settings.
    • To provide practical methods for programming microcomputers in the C language for laboratory applications.

    Main Methods:

    • A hardware architecture comprising a minicomputer host and remote microcomputer slaves was developed.

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  • The Unix operating system and the C programming language were employed for system software.
  • Specific programming techniques for laboratory data acquisition, processing, and display on microcomputers were outlined.

    • Main Results:

    • The distributed system effectively manages data acquisition, processing, and display tasks.
    • Implementation demonstrated enhanced efficiency and cost savings in microprocessor use.
    • The system facilitates the use of a high-level language (C) for laboratory microcomputer programming.

    Conclusions:

    • Distributed microprocessor systems offer a practical and efficient solution for biomedical research laboratories.
    • The described system architecture and software approach enhance laboratory workflow and resource management.
    • This approach supports advanced data handling capabilities essential for modern medical research.