Advertisement

Comparison of methods for adaptive sampling of cardiac electrograms and electrocardiograms

  • S. M. Blanchard
  • R. C. Barr
Article

Abstract

Digital sampling of cardiac electrograms and electrocardiograms is usually performed by sampling at uniform intervals with rates high enough to record the fastest signal components. Numerous redundant samples are recorded during slower deflections and baseline intervals, particularly for direct cardiac measurements that include fast Purkinje deflections. In this report, five adaptive sampling methods (voltage triggered, two-point projection, second differences, the fan and CORTES) are compared with uniform sampling for cardiac waveforms. For the electrogram, the results indicated that adaptive sampling based on the fan method might be used effectively to limit average data rates to moderate values during original data acquisition

Keywords

Adaptive sampling Cardiac electrograms Electrocardiograms 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abenstein, J. P. (1978) Algorithms for real-time ambulatory ECG monitoring.Biomed. Sci. Instrum.,14, 73–77.Google Scholar
  2. Abenstein, J. P. andTompkins, W. J. (1982) A new data-reduction algorithm for real-time ECG analysis.IEEE Trans. BME-29, 43–48.Google Scholar
  3. Andrews, C. A., Davies, J. M. andSchwarz, G. R. (1967) Adaptive data compression.Proc. IEEE,55, 267–277.Google Scholar
  4. Barr, R. C. andSpach, M. S. (1977) Sampling rates required for digital recording of intracellular and extracellular cardiac potentials.Circulation,55, 40–48.Google Scholar
  5. Berson, A. S., Wojick, J. M. andPipberger, H. V. (1977) Precision requirements for electrocardiographic measurements computed automatically.IEEE Trans.,BME-24, 382–385.Google Scholar
  6. Blanchard, S. M., Barr, R. C. andSpach, M. S. (1982) A voltagetriggered system for adaptive sampling in body surface mapping.,BME-29, 726–730.Google Scholar
  7. Blanchard, S. M. andBarr, R. C. (1982) Zero, first, and second order adaptive sampling of ECGs.Proc. 35th ACEMB, Philadelphia, PA.Google Scholar
  8. Borjesson, P. O., Einarsson, G. andPahlm, O. (1980) Comments on ‘Compression of the ECG by prediction or interpolation and entropy encoding’.IEEE Trans. BME-27, 674–675.Google Scholar
  9. Cox, J. R., Nolle, F. M., Fozzard, H. A. andOliver, G. C. (1968) AZTEC, a preprocessing program for real-time ECG rhythm analysis.,BME-15, 128–129.Google Scholar
  10. Cox, J. R., Fozzard, H. A., Nolle, F. M. andOliver, G. C. (1974) Some data transformations useful in electrocardiography. InComputers and biomedical research.Stacy, R. W. andWaxman, B. D., (Eds.), Chap. 3, 182–206.Google Scholar
  11. Dower, G. E. (1974) Progress in electrocardiology, Part 2: data display, compression and transmission.J. Biomed. Eng.,9, 296–297.Google Scholar
  12. Evans, A. K. andLux, R. L. (1978) Reduction of temporal redundancy in ECG body surface maps.Proc. 31st ACEMB,31, 168.Google Scholar
  13. Gardenhire, L. W. (1964) Redundancy reduction, the key to adaptive telemetry. Proceedings of the 1964 National Telemetering Conference, Los Angeles, CA, Section 1–5, pp. 1–16.Google Scholar
  14. 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
  15. 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
  16. Kinias, P. andFozzard, H. A. (1979) Rapid ECG analysis and arrhythmia detection. InComputer techniques in cardiology.Cady, L. D. Jr. (Ed.), Biomed. Eng. & Instrumentation Series, Vol. 4, Marcel Dekker, New York, 97–122.Google Scholar
  17. Kortman, C. M. (1967) Redundancy reduction—a practical method of data compression.Proc. IEEE,55, 253–263.Google Scholar
  18. Langner, P. H. Jr., Geselowitz, D. B. andBriller, S. A. (1973) Wide band recording of the electrocardiogram and coronary heart disease.Am. Heart. J.,86, 308–317.CrossRefGoogle Scholar
  19. Marvell, C. J. andKirk, D. L. (1980a) Use of a microprocessor to simulate precise electrocardiograms.J. Biomed. Eng.,2, 61–62.Google Scholar
  20. Marvell, C. J. andKirk, D. L. (1980b) A simple software routine for the reproducible processing of the electrocardiogram.,2, 216–220.Google Scholar
  21. Mueller, W. C. (1978) Arrhythmia detection program for an ambulatory ECG monitor.Biomed. Sci. Instrum.,14, 81–85.Google Scholar
  22. Pahlm, O., Borjesson, P. D. andWerner, O. (1979) Compact digital storage of ECGs.Comput. Programs in Biomedicine,9, 293–300.CrossRefGoogle Scholar
  23. Ruttimann, U. E., Berson, A. E. andPipberger, H. V. (1976) ECG data compression by linear prediction.Computers in Cardiology, IEEE Computer Society, 313–315.Google Scholar
  24. Ruttimann, 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
  25. Shakin, V. V., Breuer, P., Szekely, E., Kobzos, L., Wolf, T. andNemeth, J. (1977) Adaptive compression and filtering for vectorial electrocardiogams.Adv. Card.,19, 169–170.Google Scholar
  26. Shakin, V. V., Csapodi, C., Preda, I., Kenedi, P. andBreuer, P. (1978) Adaptive data reduction in body surface mapping.,21, 40–43.Google Scholar
  27. Shridhar, M. andStevens, M. F. (1979) An analysis of ECG data, for data compression.Int. J. Bio-Med. Comput.,10, 113–128.CrossRefGoogle Scholar
  28. Spach, M. S., Barr, R. C., Johnson, E. A. andKootsey, J. M. (1973) Cardiac extracellular potentials. Analysis of complex wave forms about the Purkinje network in dogs.Circ. Res.,33, 465–473.Google Scholar
  29. Stewart, D., Dower, G. E. andSuranyi, O. (1973) An ECG compression code.J. Electrocardiology,6, 175–176.Google Scholar
  30. Tompkins, W. J. (1978) A portable microcomputer based system for biomedical applications.Biomed. Sci. Instrum.,14, 61–66.Google Scholar
  31. Tompkins, W. J. andAbenstein, J. P. (1979) CORTES—a data reduction algorithm for electrocardiography.Proc. 14th AAMI, Las Vegas, Nevada, 277.Google Scholar
  32. Tompkins, W. J. andWebster, J. G. (Eds.) (1981)Design of microcomputer-based medical instrumentation. Prentice-Hall, Englewood Cliffs, New Jersey, 433–461.Google Scholar
  33. Webster, J. G. (1978) An intelligent monitor for ambulatory ECGs.Biomed. Sci. Instrum.,14, 55–60.Google Scholar
  34. Wolf, H. K., Sherwood, J. D. andKanon, D. J. (1976) The effect of signal noise on the performance of several ECG programs. InComputers in Cardiology, IEEE Computer Society, 303–305.Google Scholar
  35. Womble, M. E., Halliday, J. S., Mitter, S. K., Lancaster, M. C. andTriebwasser, J. H. (1977) Data compression for storing and transmitting ECGs/VCGs.Proc. IEEE,65, 702–706.CrossRefGoogle Scholar

Copyright information

© IFMBE 1985

Authors and Affiliations

  • S. M. Blanchard
    • 1
  • R. C. Barr
    • 1
  1. 1.Department of Biomedical Engineering and PediatricsDuke UniversityDurhamUSA

Personalised recommendations