Medical and Biological Engineering and Computing

, Volume 23, Issue 5, pp 401–410 | Cite as

Evaluation of the fan method of adaptive sampling on human electrocardiograms

  • D. A. DiPersio
  • R. C. Barr
Article

Abstract

The fan is a method of adaptive sampling that selects samples from electrocardiograms more rapidly during periods of rapid waveform change and more slowly otherwise. One attribute of the fan is the guarantee that the original waveform can be reconstructed within tolerance ε. Many questions about the particulars of the fan's performance on human ECGs have been undocumented, e.g. what ε choice leads to good quality recording, how does the choice of ε affect visual quality, and what average sampling rates occur? The paper provides answers to these and other questions. It is based on retrospective analysis of 20700 human ECG waveforms from subjects of all ages. The results show, for example, that ε=10μV leads to high quality waveforms sampled at an average rate of 266 samples s−1 with maximum errors only 1/24th the maximum errors using uniform sampling at 250 samples s−1, and that ε=30μV leads to waveforms showing all deflections at an average rate of 45 samples s−1 with maximum errors only 1/57th of the maximum errors from uniform sampling at 45 samples s−1.

Keywords

Digital sampling Electrocardiograms Fan algorithm 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Andrews, C. A., Davies, J. M. andSchwarz, G. R. (1967) Adaptive data compression.Proc. IEEE,55, 267–277.Google Scholar
  2. Blanchard, S. M. andBarr, R. C. (1985) Comparison of methods for adaptive sampling of cardiac electrograms and electrocardiograms.Med. & Biol. Eng. & Comput.,23, 377–386.CrossRefGoogle Scholar
  3. Gardenhire, L. W. (1964) Redundancy reduction, the key to adaptive telemetry. Proceedings of the 1964 National Telemetering Conference, Los Angeles, Section 1–5, 1–16.Google Scholar
  4. Gardenhire, L. W. (1965) Data redundancy reduction for biomedical telemetry. InBiomedical telemetry. Caceres, C. A. (Ed.), Academic Press, New York, Chap. 11, 255–298.Google Scholar
  5. Ishijima, M., Shin, S. B., Hostetter, G., andSklansky, J. (1983) Scan-along polygonal approximation for data compression of electrocardiograms.IEEE Trans.,BME-30, 723–729.Google Scholar
  6. Kortman, C. M. (1967) Redundancy reduction—a practical method of data compression.Proc. IEEE,55, 253–263.Google Scholar
  7. Ruttiman, U. E. andPipberger, H. V. (1979) Compression of the ECG by prediction or interpolation and entropy encoding.IEEE Trans.,BME-26, 613–623.Google Scholar
  8. Sklansky, J. andGonzalez, V. (1980) Fast polygonal approximation of digitized curves.Patt. Recog.,12, 327–331.CrossRefGoogle Scholar
  9. Spach, M. S., Barr, R. C., Warren, R. B., Benson, D. W., Jr., Walston, A. andEdwards, S. B. (1979) Isopotential body surface mapping in subjects of all ages: emphasis on low level potentials with analysis of the method.Circulation,59, 805–821.Google Scholar
  10. Womble, M. E., Halliday, J. S., Mitter, S. K., Lancaster, M. C. andTriebwasser, J. H. (1977) Data compression for storing and transmitting ECG's/VCG's.Proc. IEEE,65, 702–706.CrossRefGoogle Scholar

Copyright information

© IFMBE 1985

Authors and Affiliations

  • D. A. DiPersio
    • 1
    • 2
  • R. C. Barr
    • 1
    • 2
  1. 1.Department of Biomedical EngineeringDuke UniversityDurhamUSA
  2. 2.Department of PediatricsDuke UniversityDurhamUSA

Personalised recommendations