Multifractal Analysis of Term and Preterm Uterine EMG Signals Using Wavelet Leaders

Vardhini P1, Punitha Namadurai1, Navaneethakrishna Makaram, Swaminathan Ramakrishnan

  • 1Indian Institute of Technology Madras



Special Session


13:30 - 15:00 | Tue 30 Oct | Ambassador A | B4L-B

EMG Sensing & Signal Processing

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The purpose of this work is to analyze the multifractal features of the uterine Electromyography (EMG) signals and differentiate term, preterm conditions using Wavelet Leaders algorithm. The signals recorded during second (T1 and P1) and third trimester (T2) are considered. Multifractal analysis is applied to compute multifractal spectrum and features are extracted for analyzing the signals in T1, T2 and P1 groups. αmin and αmax are able to differentiate signals in T1-P1 and T1-T2 groups respectively. α0 has statistical significance in discriminating signals in all the considered groups. Hence, it appears that these multifractal features differentiate term and preterm conditions

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