Methods Inf Med 2007; 46(02): 186-190
DOI: 10.1055/s-0038-1625404
Original Article
Schattauer GmbH

Comparison between Fetal Heart Rate Standard Parameters and Complexity Indexes for the Identification of Severe Intrauterine Growth Restriction

M. Ferrario
1   Dipartimento di Bioingegneria, Politecnico di Milano, Milano, Italy
,
M. G. Signorini
1   Dipartimento di Bioingegneria, Politecnico di Milano, Milano, Italy
,
G. Magenes
2   Dipartimento di Informatica e Sistemistica, Università di Pavia, Pavia, Italy
› Author Affiliations
Further Information

Publication History

Publication Date:
11 January 2018 (online)

Summary

Objectives : The intrauterine growth restriction (IUGR) is a pathological state: the fetus is at risk of hypoxia and this condition is associated with increased perinatal morbidity and mortality. However, evidence-based guidelines for clinical surveillance are poor and lack reliable indexes. This study introduces new procedures to extract parameters from the fetal heart rate signal in order to identify severe intrauterine growth restricted (IUGR) fetuses

Methods : Standard parameters (time domain and frequency domain indexes) are compared to a new parameter, the Lempel Ziv complexity, and to two regularity estimators (approximate entropy and sample entropy). The paper analyzes the robustness of the indexes coming from the parameter extraction procedure.

Results and Conclusions : The results show that the LZ complexity is a stable parameter and it is able to significantly discriminate the severe IUGR (preterm delivered) from moderate IUGR (at term delivered) and from healthy fetuses.

 
  • References

  • 1. Malcus P. Antenatal fetal surveillance. Current opinion in Obstetrics and Gynaecology 2004; 16: 123-128.
  • 2. Baschat AA. Integrated fetal testing in growth restriction: combining multivessel Doppler and biophysical parameters. Ultrasound Obst Gyn 2003; 21: 1-8.
  • 3. Lempel A, Ziv J. On the complexity of finite sequences. IEEE Trans. on Inf Th 1976; 22 (01) 75-81.
  • 4. Signorini MG, Magenes G, Cerutti S, Arduini D. Linear and Nonlinear Parameters for the Analysis of Fetal Heart Rate Signal from Cardiotoco-graphic Recordings. IEEE Trans Biom Eng 2003; 50 (03) 365-375.
  • 5. Lawson GW, Belcher R, Dawes GS, Redman C. A comparison of ultrasound (with autocorrelation) and direct electrocardiogram fetal heart rate detector systems. Amer J Obstet Gynecol 1983; 147 (06) 721-722.
  • 6. De Haan J. et al. Quantitative evaluation of fetal heart rate. I. Processing methods. Eur J Obstet Gyn 1971; 3: 95-103.
  • 7. Pincus SM. Approximate entropy (ApEn) as complexity measure. Chaos 1995; 5 (01) 110-117.
  • 8. Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am JpH Circ Physiol 2000; 278: H2039-2049.
  • 9. Ferrario M, Signorini MG, Cerutti S. Complexity Analysis of 24 Hours Heart Rate Variability Time Series. Proc of the EMBC 04 Conference. IEEE Press; 2004
  • 10. Kaspar F. SchusterHG. Easilycalculable measure for the complexity of spatiotemporal patterns. Physical Review A 1987; 36 (02) 842-848.
  • 11. Yang A-C. et al. Linguistic Analysis of the human heartbeat using frequency and rank order statistics. Phys Rev Letters 2003; 90: 10 108103-1-108103-4.
  • 12. Zhang XS, Roy RJ, Jensen E. EEG complexity as a measure of depth of anesthesia for patients. IEEE Trans on BME 2001; 48 (12) 424-1432.
  • 13. Zhang XS. etal. Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Trans on BME 1999; 46 (05) 548-555.