In this study, an attempt has been made to analyze uterine Electromyography (uEMG) signals during Term conditions (pregnancy duration more than 37 weeks of gestational age) using Empirical Mode Decomposition based Detrended Fluctuation Analysis (EMD-DFA). The Term delivery signals are considered from a publicly available database, grouped as T1 (<26 weeks gestational age) and T2 (≥26 weeks gestational age) based on the time of recording, and are subjected to an EMD-DFA algorithm. The double logarithmic plot of the detrended fluctuation function against the scale is analyzed, and the Hurst exponent feature is computed for both groups. The features are statistically analyzed using the Student s t-test. Results show that the EMD-DFA method is able to capture the variations in the fluctuations of uEMG signals under these conditions. The Hurst exponent feature is found to be statistically significant (p-value < 0.005) for both groups. There is an increase in the Hurst exponent feature value in the T2 group, which indicates that T2 signals possess smoother characteristics than T1 signals. Hence, it appears that the proposed approach could aid in investigating variations in the fluctuations of Term delivery signals, differentiating T1 and T2 conditions.. © 2020 Institute of Electronics and Information Engineers. All rights reserved.