Characterization and automatic classification of preterm and term uterine records

被引:56
作者
Jager, Franc [1 ]
Libensek, Sonja [1 ]
Gersak, Ksenija [2 ]
机构
[1] Univ Ljubljana, Fac Comp & Informat Sci, Dept Software, Ljubljana, Slovenia
[2] Univ Ljubljana, Fac Med, Dept Obstet & Gynecol, Ljubljana, Slovenia
来源
PLOS ONE | 2018年 / 13卷 / 08期
关键词
ELECTRICAL-ACTIVITY; APPROXIMATE ENTROPY; ELECTROMYOGRAPHY; SIGNAL; PREGNANCY; DELIVERY; UTERUS; IDENTIFICATION; CONTRACTIONS; MUSCLE;
D O I
10.1371/journal.pone.0202125
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Predicting preterm birth is uncertain, and numerous scientists are searching for noninvasive methods to improve its predictability. Current researches are based on the analysis of ElectroHysteroGram (EHG) records, which contain information about the electrophysiological properties of the uterine muscle and uterine contractions. Since pregnancy is a long process, we decided to also characterize, for the first time, non-contraction intervals (dummy intervals) of the uterine records, i.e., EHG signals accompanied by a simultaneously recorded external tocogram measuring mechanical uterine activity (TOCO signal). For this purpose, we developed a new set of uterine records, TPEHGT DS, containing preterm and term uterine records of pregnant women, and uterine records of non-pregnant women. We quantitatively characterized contraction intervals (contractions) and dummy intervals of the uterine records of the TPEHGT DS in terms of the normalized power spectra of the EHG and TOCO signals, and developed a new method for predicting preterm birth. The results on the characterization revealed that the peak amplitudes of the normalized power spectra of the EHG and TOCO signals of the contraction and dummy intervals in the frequency band 1.0-2.2 Hz, describing the electrical and mechanical activity of the uterus due to the maternal heart (maternal heart rate), are high only during term pregnancies, when the delivery is still far away; and they are low when the delivery is close. However, these peak amplitudes are also low during preterm pregnancies, when the delivery is still supposed to be far away (thus suggesting the danger of preterm birth); and they are also low or barely present for non-pregnant women. We propose the values of the peak amplitudes of the normalized power spectra due to the influence of the maternal heart, in an electro-mechanical sense, in the frequency band 1.0-2.2 Hz as a new biophysical marker for the preliminary, or early, assessment of the danger of preterm birth. The classification of preterm and term, contraction and dummy intervals of the TPEHGT DS, for the task of the automatic prediction of preterm birth, using sample entropy, the median frequency of the power spectra, and the peak amplitude of the normalized power spectra, revealed that the dummy intervals provide quite comparable and slightly higher classification performances than these features obtained from the contraction intervals. This result suggests a novel and simple clinical technique, not necessarily to seek contraction intervals but using the dummy intervals, for the early assessment of the danger of preterm birth. Using the publicly available TPEHG DB database to predict preterm birth in terms of classifying between preterm and term EHG records, the proposed method outperformed all currently existing methods. The achieved classification accuracy was 100% for early records, recorded around the 23rd week of pregnancy; and 96.33%, the area under the curve of 99.44%, for all records of the database. Since the proposed method is capable of using the dummy intervals with high classification accuracy, it is also suitable for clinical use very early during pregnancy, around the 23rd week of pregnancy, when contractions may or may not be present.
引用
收藏
页数:49
相关论文
共 62 条
  • [1] Automated detection of premature delivery using empirical mode and wavelet packet decomposition techniques with uterine electromyogram signals
    Acharya, U. Rajendra
    Sudarshan, Vidya K.
    Rong, Soon Qing
    Tan, Zechariah
    Lim, Choo Min
    Koh, Joel E. W.
    Nayak, Sujatha
    Bhandary, Sulatha V.
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2017, 85 : 33 - 42
  • [2] A Multivariate Multiscale Fuzzy Entropy Algorithm with Application to Uterine EMG Complexity Analysis
    Ahmed, Mosabber U.
    Chanwimalueang, Theerasak
    Thayyil, Sudhin
    Mandic, Danilo P.
    [J]. ENTROPY, 2017, 19 (01):
  • [3] Comparison of Different EHG Feature Selection Methods for the Detection of Preterm Labor
    Alamedine, D.
    Khalil, M.
    Marque, C.
    [J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2013, 2013
  • [4] The Icelandic 16-electrode electrohysterogram database
    Alexandersson, Asgeir
    Steingrimsdottir, Thora
    Terrien, Jeremy
    Marque, Catherine
    Karlsson, Brynjar
    [J]. SCIENTIFIC DATA, 2015, 2
  • [5] [Anonymous], 2012, BORN TOO SOON GLOBAL
  • [6] [Anonymous], 2002, MACH LEARN
  • [7] [Anonymous], 2007, INT J COMPUTATIONAL
  • [8] Baker PN, 2011, OBSTET 10 TEACHERS, P436
  • [9] A multichannel time-frequency and multi-wavelet toolbox for uterine electromyography processing and visualisation
    Batista, Arnaldo G.
    Najdi, Shirin
    Godinho, Daniela M.
    Martins, Catarina
    Serrano, Fatima C.
    Ortigueira, Manuel D.
    Rato, Raul T.
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2016, 76 : 178 - 191
  • [10] BISHOP EH, 1964, OBSTET GYNECOL, V24, P266