The potential of using the information of uterine contractions (UCs) derived from electrohysterogram (EHG) has been recognized in early detection of preterm delivery. A better understanding of the conduction property of EHG is clinically useful for developing advanced methods to achieve a reliable prediction of preterm delivery. In this paper, a method to analyze the destination of EHG propagation has been proposed via the estimation of directed information (DI) between each pair of neighboring channels with a novel propagation terminal zone (PTZ) identification algorithm. The proposed method was applied to experimental data from the Icelandic 16-electrode EHG database. The results demonstrated that for more than 81.8% participants, the PTZ was identified along the medial axis of uterus, among which more than half have their PTZ determined in the center between the uterine fundus and public symphysis, which indicated a great probability of propagation of EHG signals towards the center of uterus plane.Clinical relevance - This study makes a fundamental contribution for predicting preterm delivery, which can provide improvement in obstetric care towards pregnancy monitoring.
|Title of host publication||42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society|
|Subtitle of host publication||Enabling Innovative Technologies for Global Healthcare, EMBC 2020|
|Number of pages||5|
|Publication status||Published - 27 Aug 2020|
|Event||42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society - EMBS Virtual Academy|
Duration: 20 Jul 2020 → 24 Jul 2020
|Name||Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS|
|Conference||42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society|
|Period||20/07/20 → 24/07/20|
Bibliographical note© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics