title: A multichannel time-frequency and multi-wavelet toolbox for uterine electromyography processing and visualisation.
abstract: The uterine electromyogram, also called electrohysterogram (EHG), is an electrical signal generated by the uterine contractile activity. The EHG has been considered a promising biomarker for labour and preterm labour prediction, for which there is a demand for accurate estimation methods. Preterm labour is a significant public health concern and one of the major causes of neonatal mortality and morbidity [1]. Given the non-stationary properties of the EHG signal, time-frequency domain analysis can be used. For real life signals it is not generally possible to determine a priori the suitable quadratic time-frequency kernel or the appropriate wavelet family and relative parameters, regarding, for instance, the adequate detection of the signal frequency variation in time. There has been a lack of a comprehensive software tool for the selection of the appropriate time frequency representation of a multichannel EHG signal and extraction of relevant spectral and temporal information. The presented toolbox (Uterine Explorer) has been specifically designed for the EHG analysis and exploration in view of the characterisation of its components. The starting point is the multichannel scalogram or spectrogram representation from which frequency and time marginals, instantaneous frequency and bandwidth are obtained as EHG features. From this point the detected components undergo parametric and non-parametric spectral estimation and wavelet packet analysis. Intrauterine pressure estimation (IUP) is obtained using the Teager, RMS, wavelet marginal and Hilbert operators over the EHG. This toolbox has been tested to build up a dictionary of 288 EHG components [2], useful for research in preterm labour prediction.
authors.affiliation: UNINOVA, Campus de Caparica, 2829-516 Caparica, Portugal; Faculty of Sciences and Technology of the Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal. Electronic address: agb@fct.unl.pt.
authors.forename: Arnaldo G
authors.initials: AG
authors.lastname: Batista
authors.affiliation: UNINOVA, Campus de Caparica, 2829-516 Caparica, Portugal.
authors.forename: Shirin
authors.initials: S
authors.lastname: Najdi
authors.affiliation: Faculty of Sciences and Technology of the Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal.
authors.forename: Daniela M
authors.initials: DM
authors.lastname: Godinho
authors.affiliation: Faculty of Sciences and Technology of the Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal.
authors.forename: Catarina
authors.initials: C
authors.lastname: Martins
authors.affiliation: Nova Medical School /Faculty of Medical Sciences, Universidade Nova de Lisboa, Portugal.
authors.forename: Fátima C
authors.initials: FC
authors.lastname: Serrano
authors.affiliation: UNINOVA, Campus de Caparica, 2829-516 Caparica, Portugal; Faculty of Sciences and Technology of the Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal.
authors.forename: Manuel D
authors.initials: MD
authors.lastname: Ortigueira
authors.affiliation: UNINOVA, Campus de Caparica, 2829-516 Caparica, Portugal; Escola Superior de Tecnologia do Instituto Politécnico de Setúbal, 2910-761 Setúbal, Portugal.
authors.forename: Raul T
authors.initials: RT
authors.lastname: Rato
mesh_terms: D004576:Electromyography / Q000379:methods*; D005260:Female; D006801:Humans; D007752:Obstetric Labor, Premature / Q000175:diagnosis; D011247:Pregnancy; D012815:Signal Processing, Computer-Assisted; D012984:Software; D018590:Uterine Monitoring / Q000379:methods*
keywords: Feature extraction; Multi-channel electrohysterogram; Preterm labour; Spectral modelling; Time–frequency analysis; Wavelet analysis