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Characterization of abdominally acquired uterine electrical signals in humans, using a non-linear analytic method

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Abstract

The present work seeks to determine if a particular non-linear analytic method is effective at quantifying uterine electromyography (EMG) data for estimating the onset of labor. Twenty-seven patients were included, and their uterine EMG was recorded non-invasively for 30 min. The patients were grouped into two sets: G1: labor, N=14; G2: antepartum, N=13. G1 patients all delivered spontaneously within 24 h of recording while G2 patients did not. The uterine electrical signals were analyzed offline by first isolating the uterine-specific frequency range and then randomly selecting “bursts” of uterine electrical activity (each associated with a uterine contraction) from every recording. Wavelet transform was subsequently applied to each of the bursts’ traces, and then the fractal dimension (FD) of the resulting transformed EMG burst-trace was calculated (Benoit 1.3, Trusoft). Average burst FD was found for each patient. FD means for G1 and G2 were calculated and compared using t test. FD was significantly higher (P<0.05) for G1: 1.27±0.03 versus G2: 1.25±0.02. The wavelet-decomposition-generated fractal dimension can be used to successfully discern between patients who will deliver spontaneously within 24 h and those who will not, and can be useful for the objective classification of antepartum versus labor patients.

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References

  1. Abarbanel HDI (1996) Analysis of observed chaotic data. Springer, Berlin Heidelberg New York esp. see pp 11, 14, 31, 37, 198–202

  2. Bassingthwaighte JB, Liebovitch LS, West BJ (1994) Fractal physiology. Oxford University Press, New York

    Google Scholar 

  3. Buhimschi C, Garfield RE (1998) Uterine activity during pregnancy and labor assessed by simultaneous recordings from the myometrium and abdominal surface in the rat. Am J Obstet Gynecol 178:811–822

    Article  PubMed  Google Scholar 

  4. Devedeux D, Marque C, Mansour S, Germain G, Duchene J (1993) Uterine electromyography: a critical review. Am J Obstet Gynecol 169:1636–1653

    PubMed  Google Scholar 

  5. Figueroa JP, Honnebier MB, Jenkins S, Nathanielsz PW (1990) Alteration of 24-h rhythms in the myometrial activity in the chronically catheterized pregnant rhesus monkey after 6-hours shift in the light-dark cycle. Am J Obstet Gynecol 163:648–654

    PubMed  Google Scholar 

  6. Garfield RE, Yallampalli C (1994) Structure and function of uterine muscle. In: Chard T, Grudzinskas JG (eds) The uterus. Cambridge reviews in human reproduction. Cambridge University Press, Cambridge, UK, pp 54–93, 40–81

  7. Garfield RE, Buhimschi C (1998) Control and assessment of the uterus and cervix during pregnancy and labour (Sep–Oct). Hum Reprod Update 4(5):673–695

    Article  PubMed  Google Scholar 

  8. Garfield RE et al (1998) Instrumentation for the diagnosis of term and pre-term labour. J. Perinat Med 26:413–436

    Article  PubMed  Google Scholar 

  9. Goldberger AL (1997) Fractal variability versus pathologic periodicity: complexity loss and stereotypy in disease. Perspect Biol Med 40:543–561

    PubMed  Google Scholar 

  10. Goldberger A (1999) Nonlinear dynamics, fractals, and chaos theory: implications for neuroautonomic heart rate control in health and disease. Bolis CL, Licinio J (eds) The Autonomic nervous system. World Health Organization, Geneva

    Google Scholar 

  11. Goldenberg RL, Cliver SP, Bronstein J, Cutter GR, Andrews WW, Mennemeyer ST (1994) Bed rest in pregnancy. Obstet Gynecol 84:131–136

    PubMed  Google Scholar 

  12. Karlsson JS, Gerdle B, Akay M (2001) Analyzing surface myoelectric signals recorded during isokinetic contractions. IEEE Eng Med Biol November/December:97–105

    Article  Google Scholar 

  13. Kobayashi M, Musha T (1982) 1/f fluctuation of heartbeat period. IEEE Trans Biomed Eng 29:456–457

    Article  PubMed  Google Scholar 

  14. Kuriyama H, Csapo A (1967) A study of the parturient uterus with the microelectrode technique. Endocrinology 80:748–753

    Article  PubMed  Google Scholar 

  15. Linhart J, Olson G, Goodrum L, Rowe T, Saade G, Hankins G (1990) Pre-term labor at 32 to 34 weeks’ gestation: effect of a policy of expectant management on length of gestation. Am J Obstet Gynecol 178:S179

    Google Scholar 

  16. Maclsaac DT, Parker PA, Scott RN, Englehart KB, Duffley C (2001) Influence of dynamic factors on myoelectric parameters. IEEE Eng Med Biol November/December:82–89

    Article  Google Scholar 

  17. Maner W, Garfield RE, Maul H, Olson G, Saade G (2003) Predicting term and pre-term delivery in humans using transabdominal uterine electromyography. Obstet Gynecol 101(6):1254–1260

    Article  PubMed  Google Scholar 

  18. Mansour S, Devedeux D, Germain G, Marque C, Duchene J (1996) Uterine EMG spectral analysis and relationship to mechanical activity in pregnant monkeys. Med Biol Eng Comput 34(2):115–121

    Article  PubMed  Google Scholar 

  19. Marsh DJ, Osborn JL, Cowley AW (1990) 1/f fluctuations in arterial pressure and regulation of renal blood flow in dogs. Am J Physiol 258:F1394–F1400

    PubMed  Google Scholar 

  20. Marshall JM (1962) Regulation of the activity in uterine muscle. Physiol Rev 42:213–227

    Google Scholar 

  21. Nagarajan R, Eswaran H, Wilson JD, Murphy P, Lowery C, Preibl H (2003) Analysis of uterine contractions: a dynamical approach. J Maternal Fetal Neonatal Med 14:8–21

    Article  Google Scholar 

  22. Nagel J, Schaldach M (1980) Recording of uterine activity from the abdominal lead EMG, in fetal and neonatal physiological measurements. In: Rolfe P (ed) Pitman Medical Limited, Tunbridge Wells pp 177–182

  23. Pan ZS, Zhang Y, Parker PA (1989) Motor unit power spectrum and firing rate. Med Biol Eng Comput 27:14–18

    Article  PubMed  Google Scholar 

  24. Sheridan TB, Meyer JE, Roy SH, Decker KS, Yanagishima T, Yoichi K (1991) Physiological and psychological evaluations of driver fatigue during long term driving. In: International congress and exposition of the engineering society for advancing mobility land sea air and space, Feb 25–March 1

  25. Stief CG, Kellner B, Hartung C, Hauck E, Schlote N, Truss M, Hinrichs H, Jonas U (1997) Computer-assisted evaluation of the smooth-muscle electromyogram of the corpora cavernosa by fast Fourier transformation. Eur Urol 31(3):329–334

    PubMed  Google Scholar 

  26. Struijk PC, Ursem NTC, Mathews J, Clark EB, Keller BB, Wladimiroff JW (2001) Power spectrum analysis of heart rate and blood flow velocity variability measured in the umbilical and uterine arteries in early pregnancy: a comparative study. Ultrasound Obstet Gynecol 17(4):316–321

    Article  PubMed  Google Scholar 

  27. Szeto H, Chen PY, Decena JA, Cheng YI, Wu Dun-L, Dwyer G (1992) Fractal properties of fetal breathing dynamics regulatory interactive comp physiol. Am J Physiol 263 (32):R141–R147

    PubMed  Google Scholar 

  28. Tezuka N, Ali M, Chwalisz K, Garfield RE (1995) Changes in transcripts encoding calcium channel subunits of rat myometrium during pregnancy. Am J Physiol 269:C1008–C1017

    PubMed  Google Scholar 

  29. U.S. Preventive Services Task Force (1989) Guide to clinical preventive services: an assessment of the effectiveness of 169 interventions. Williams & Wilkins, Baltimore

    Google Scholar 

  30. Wolfs GMJA, Van Leeuwen (1979) Electromyographic observations on the human uterus during labor. Acta Obstet Gynecol Scand Suppl 90:1–61

    Article  PubMed  Google Scholar 

  31. Yamada K, Isotani T, Irisawa S, Yoshimura M, Tajika A, Yagyu T, Saito A, Kinoshita T (2004) EEG Global field power spectrum changes after a single dose of atypical antipsychotics in healthy volunteers. Brain Topogr Summer 16(4):281–285

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Division of Reproductive Sciences, University of Texas Medical Branch, 301 University Route 1062, Galveston, TX, 77555, USA

    William L. Maner, Lynette B. MacKay, George R. Saade & Robert E. Garfield

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  1. William L. Maner
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  2. Lynette B. MacKay
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  3. George R. Saade
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  4. Robert E. Garfield
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Correspondence to William L. Maner.

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Maner, W.L., MacKay, L.B., Saade, G.R. et al. Characterization of abdominally acquired uterine electrical signals in humans, using a non-linear analytic method. Med Bio Eng Comput 44, 117–123 (2006). https://doi.org/10.1007/s11517-005-0011-3

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  • DOI: https://doi.org/10.1007/s11517-005-0011-3

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