Show simple item record

dc.contributor.authorMartinek, Radek
dc.contributor.authorŽídek, Jan
dc.date.accessioned2013-03-15T14:39:25Z
dc.date.available2013-03-15T14:39:25Z
dc.date.issued2012
dc.identifier.citationPrzegląd elektrotechniczny. 2012, r. 88, nr. 12b, s. 155-160.cs
dc.identifier.issn0033-2097
dc.identifier.urihttp://hdl.handle.net/10084/96226
dc.description.abstractThis article deals with utilization of the combination of the fuzzy system and artificial intelligence techniques, called the Adaptive Neuro Fuzzy Inference System ANFIS, with the aim to refine the diagnostic quality of the abdominal fetal electrocardiogram FECG. Within the scope of the experiments carried out and based on the ANFIS structure the authors created a complex system for removing the undesirable mother’s MECG degrading the abdominal FECG. Current research shows that the application of the conventional systems for enhancing the diagnostic quality of the abdominal FECG faces a series of problems (e.g. non-linear character of the task to solve, computational complexity of RLS algorithms, etc.). The need for a higher diagnostic quality of the abdominal FECG is reflected in the authors’ intention to utilize the designed system for the latest intrapartum monitoring method, called ST analysis. In terms of this advanced method, the aspect subjected to a diagnostic analysis is the ST segment of the FECG curve. The results indicate that the system utilizing ANFIS shows better experimental results than the conventional systems based on the LMS or RLS adaptive algorithms. The proposed adaptive system aims to clear any doubts in evaluation of the results of ST analysis while using a non-invasive method of external monitoring.cs
dc.format.extent754283 bytescs
dc.format.mimetypeapplication/pdfcs
dc.language.isoencs
dc.publisherSigma Notcs
dc.relation.ispartofseriesPrzegląd elektrotechnicznycs
dc.relation.urihttp://red.pe.org.pl/articles/2012/12b/46.pdfcs
dc.subjectANFIScs
dc.subjectFECGcs
dc.subjectMECGcs
dc.subjectST analysiscs
dc.subjectelektrokardiogramcs
dc.titleRefining the diagnostic quality of the abdominal fetal electrocardiogram using the techniques of artificial intelligencecs
dc.title.alternativePoprawa jakości sygnału elektrokardiogramu płodu przy wykorzystaniu narzędzi sztucznej inteligencjics
dc.typearticlecs
dc.identifier.locationNení ve fondu ÚKcs
dc.description.abstract-enW artykule przedstawiono wykorzystanie fuzji metod: zbiorów rozmytych i sztucznej inteligencji ANFIS do poprawy jakości diagnostyki elektrokardiografii płodu. Głównym problemem jest usunięcie sygnału pochodzącego od matki który znacznie przewyższa sygnał płodu.cs
dc.rights.accessopenAccess
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume88cs
dc.description.issue12bcs
dc.description.lastpage160cs
dc.description.firstpage155cs
dc.identifier.wos000314689600046


Files in this item

This item appears in the following Collection(s)

Show simple item record