Detail
Článek
FT
Medvik - BMČ
  • Je něco špatně v tomto záznamu ?

Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

R. Jaros, R. Martinek, R. Kahankova,

. 2018 ; 18 (11) : . [pub] 20181027

Jazyk angličtina Země Švýcarsko

Typ dokumentu časopisecké články, přehledy

Perzistentní odkaz   https://www.medvik.cz/link/bmc19000273

Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

000      
00000naa a2200000 a 4500
001      
bmc19000273
003      
CZ-PrNML
005      
20190107104104.0
007      
ta
008      
190107s2018 sz f 000 0|eng||
024    7_
$a 10.3390/s18113648 $2 doi
035    __
$a (PubMed)30373259
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a sz
100    1_
$a Jaros, Rene $u Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic. rene.jaros@vsb.cz.
245    10
$a Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal / $c R. Jaros, R. Martinek, R. Kahankova,
520    9_
$a Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.
650    _2
$a algoritmy $7 D000465
650    _2
$a elektrokardiografie $x metody $7 D004562
650    _2
$a elektrody $7 D004566
650    _2
$a plod $x fyziologie $7 D005333
650    _2
$a lidé $7 D006801
650    _2
$a analýza hlavních komponent $7 D025341
650    12
$a počítačové zpracování signálu $7 D012815
650    _2
$a vlnková analýza $7 D058067
655    _2
$a časopisecké články $7 D016428
655    _2
$a přehledy $7 D016454
700    1_
$a Martinek, Radek $u Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic. radek.martinek@vsb.cz.
700    1_
$a Kahankova, Radana $u Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic. radana.kahankova@vsb.cz.
773    0_
$w MED00008309 $t Sensors (Basel) $x 1424-8220 $g Roč. 18, č. 11 (2018), s.
856    41
$u https://pubmed.ncbi.nlm.nih.gov/30373259 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y a
990    __
$a 20190107 $b ABA008
999    __
$a ok $b bmc $g 1364388 $s 1038396
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2018 $b 18 $c 11 $e 20181027 $i 1424-8220 $m Sensors $n Sensors Basel $x MED00008309
LZP    __
$a Pubmed-20190107

Najít záznam

Citační ukazatele

Nahrávání dat...

Možnosti archivace

Nahrávání dat...