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dc.contributor.authorMartinek, Radek
dc.contributor.authorKahánková, Radana
dc.contributor.authorNazeran, Homer
dc.contributor.authorKonečný, Jaromír
dc.contributor.authorJeżewski, Janusz
dc.contributor.authorJanků, Petr
dc.contributor.authorBilík, Petr
dc.contributor.authorŽídek, Jan
dc.contributor.authorNedoma, Jan
dc.contributor.authorFajkus, Marcel
dc.date.accessioned2017-07-24T07:08:42Z
dc.date.available2017-07-24T07:08:42Z
dc.date.issued2017
dc.identifier.citationSensors. 2017, vol. 17, issue 5, art. no. 1154.cs
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10084/117188
dc.description.abstractThis paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size mu and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.cs
dc.format.extent3550538 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesSensorscs
dc.relation.urihttps://doi.org/10.3390/s17051154cs
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectfetal ECGcs
dc.subjectadaptive filteringcs
dc.subjectLeast Mean Squares (LMS) algorithmcs
dc.subjectRecursive Least Squares (RLS) algorithmcs
dc.titleNon-invasive fetal monitoring: a maternal surface ECG electrode placement-based novel approach for optimization of adaptive filter control parameters using the LMS and RLS algorithmscs
dc.typearticlecs
dc.identifier.doi10.3390/s17051154
dc.rights.accessopenAccess
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume17cs
dc.description.issue5cs
dc.description.firstpageart. no. 1154cs
dc.identifier.wos000404553300215


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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.