An unsupervised classification method of uterine electromyography signals using wavelet decomposition

The purpose of this study is to classify the uterine contractions in the electromyography (EMG) signal. As the frequency content of the contraction changes from one woman to another and during the pregnancy, wavelet decomposition is used to extract the parameters of each contraction, and an unsupervised statistical classification method based on Fisher test is used to classify events. A principal component analysis projection is then used to evidence the groups resulting from this classification. Results show that uterine contractions may be classified into independent groups according to their frequency content.