IEEE J Biomed Health Inform. 2019 Sep;23(5):1972-1979. doi: 10.1109/JBHI.2018.2878059. Epub 2018 Oct 25.
The objectives of this paper are to examine the source of multifractality in uterine electromyography (EMG) signals and to study the progression of pregnancy in the term (gestation period > 37 weeks) conditions using multifractal detrending moving average (MFDMA) algorithm.
The signals for the study, considered from an online database, are obtained from the surface of abdomen during the second (T1) and third trimester (T2). The existence of multifractality is tested using Hurst and scaling exponents. With the intention of identifying the origin of multifractality, the preprocessed signals are converted to shuffle and surrogate data. The original and the transformed signals are subjected to MFDMA to extract multifractal spectrum features, namely strength of multifractality, maximum, minimum, and peak singularity exponents.
The Hurst and scaling exponents extracted from the signals indicate that uterine EMG signals are multifractal in nature. Further analysis shows that the source of multifractality is mainly owing to the presence of long-range correlation, which is computed as 79.98% in T1 and 82.43% in T2 groups. Among the extracted features, the peak singularity exponent and strength of multifractality show statistical significance in identifying the progression of pregnancy. The corresponding coefficients of variation are found to be low, which show that these features have low intersubject variability.
It appears that the multifractal analysis can help in investigating the progressive changes in uterine muscle contractions during pregnancy.
本文旨在探究子宫肌电图（EMG）信号多重分形的来源，并利用多重分形去趋势移动平均（MFDMA）算法研究足月（妊娠周期>37 周）条件下妊娠的进展。
本研究的信号取自在线数据库，从腹部表面获得，分别来自妊娠第二期（T1）和第三期（T2）。使用赫斯特和标度指数检验多重分形的存在性。为了确定多重分形的起源，预处理后的信号被转换为随机化和替代数据。对原始和转换后的信号进行 MFDMA，以提取多重分形谱特征，即多重分形强度、最大、最小和峰奇异指数。
从信号中提取的赫斯特和标度指数表明，子宫 EMG 信号具有多重分形特性。进一步的分析表明，多重分形的来源主要是由于存在长程相关性，在 T1 组中为 79.98%，在 T2 组中为 82.43%。在所提取的特征中，峰奇异指数和多重分形强度在识别妊娠进展方面具有统计学意义。对应的变异系数较低，表明这些特征具有较低的个体间变异性。
似乎多重分形分析可以帮助研究妊娠期间子宫肌肉收缩的渐进变化。
