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A flexible FFT algorithm for processing biomedical signals using a personal computer.

M Cesarelli1, F Clemente, M Bracale

  • 1Cattedra di Elettronica Biomedica, University of Naples, Italy.

Journal of Biomedical Engineering
|November 1, 1990
PubMed
Summary
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This study shows personal computers can process biomedical signals in real-time using a custom Fast Fourier Transform (FFT) routine. This method efficiently analyzes Doppler ultrasound and electromyography data.

Area of Science:

  • Biomedical Engineering
  • Computer Science
  • Signal Processing

Background:

  • Real-time biomedical signal processing is computationally intensive.
  • Personal computers (PCs) offer a potentially cost-effective platform for such tasks.
  • Efficient algorithms are crucial for enabling real-time analysis on limited hardware.

Purpose of the Study:

  • To demonstrate the feasibility of using PC-DOS based personal computers for quasi real-time biomedical signal processing.
  • To develop and implement an optimized Fast Fourier Transform (FFT) routine for rapid spectral analysis.
  • To validate the approach through practical applications in Doppler ultrasound and electromyography.

Main Methods:

  • Developed an assembly-written, radix-4 based Fast Fourier Transform (FFT) routine.

Related Experiment Videos

  • Implemented an autogenerated algorithm for optimizing FFT routine based on data size.
  • Integrated the FFT routine as a subroutine callable from high-level languages.
  • Utilized a PC with an A/D conversion card and a mathematical coprocessor (XXX87).

    • Main Results:

    • Achieved significant reduction in computational time for Fourier transforms.
    • Successfully applied the routine for spectral analysis of Doppler ultrasound velocimetry data.
    • Demonstrated the utility of the method in analyzing surface electromyography signals.
    • Validated the quasi real-time processing capability on a personal computer.

    Conclusions:

    • Personal computers equipped with appropriate hardware and optimized software routines can perform real-time biomedical signal processing.
    • The autogenerated FFT subroutine offers computational efficiency for spectral analysis tasks.
    • This approach provides a viable and cost-effective solution for biomedical signal analysis in various applications.