Automatic analysis of the fetal heart rate variability and uterine contractions

Rotariu, Cristian; Păsărică, Alexandru; Andruseac, Gladiola; Costin, Hariton; Nemescu, Dragoş

doi:10.1109/icepe.2014.6969970

Cited by 31 publications

(14 citation statements)

References 10 publications

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“…Conventional CTG visual interpretation is limited, and many previous studies have documented high intra-observer and inter-observer variations ( Chen et al, 2014 ). The main problem in interpreting the correct record is the high complexity of the signal pattern, which results in a high level of intra and inter observer variability ( Czabański et al, 2013 ), subjective interpretation and tedious technique ( Rotariu et al, 2014 ). EFM has a poor positive predictive value, while a high false positive rate is used to detect fetal hypoxia in the intrapartum period ( Cömert & Kocamaz, 2017b ).…”

Section: Discussionmentioning

confidence: 99%

A systematic review of automated pre-processing, feature extraction and classification of cardiotocography

Al-Yousif

Jaenul²,

Al-Dayyeni

et al. 2021

PeerJ Computer Science

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Context The interpretations of cardiotocography (CTG) tracings are indeed vital to monitor fetal well-being both during pregnancy and childbirth. Currently, many studies are focusing on feature extraction and CTG classification using computer vision approach in determining the most accurate diagnosis as well as monitoring the fetal well-being during pregnancy. Additionally, a fetal monitoring system would be able to perform detection and precise quantification of fetal heart rate patterns. Objective This study aimed to perform a systematic review to describe the achievements made by the researchers, summarizing findings that have been found by previous researchers in feature extraction and CTG classification, to determine criteria and evaluation methods to the taxonomies of the proposed literature in the CTG field and to distinguish aspects from relevant research in the field of CTG. Methods Article search was done systematically using three databases: IEEE Xplore digital library, Science Direct, and Web of Science over a period of 5 years. The literature in the medical sciences and engineering was included in the search selection to provide a broader understanding for researchers. Results After screening 372 articles, and based on our protocol of exclusion and inclusion criteria, for the final set of articles, 50 articles were obtained. The research literature taxonomy was divided into four stages. The first stage discussed the proposed method which presented steps and algorithms in the pre-processing stage, feature extraction and classification as well as their use in CTG (20/50 papers). The second stage included the development of a system specifically on automatic feature extraction and CTG classification (7/50 papers). The third stage consisted of reviews and survey articles on automatic feature extraction and CTG classification (3/50 papers). The last stage discussed evaluation and comparative studies to determine the best method for extracting and classifying features with comparisons based on a set of criteria (20/50 articles). Discussion This study focused more on literature compared to techniques or methods. Also, this study conducts research and identification of various types of datasets used in surveys from publicly available, private, and commercial datasets. To analyze the results, researchers evaluated independent datasets using different techniques. Conclusions This systematic review contributes to understand and have insight into the relevant research in the field of CTG by surveying and classifying pertinent research efforts. This review will help to address the current research opportunities, problems and challenges, motivations, recommendations related to feature extraction and CTG classification, as well as the measurement of various performance and various data sets used by other researchers.

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Section: Discussionmentioning

confidence: 99%

A systematic review of automated pre-processing, feature extraction and classification of cardiotocography

Al-Yousif

Jaenul²,

Al-Dayyeni

et al. 2021

PeerJ Computer Science

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“…However, accuracy is a problem and such smart bracelets cannot be used in hospital settings. Other studies show a connection between the fetal heart rate and the uterine pressure [24]. The i-bracelet project solution which is illustrated in Fig.…”

Section: Methodsmentioning

confidence: 99%

Smart Solution for the Detection of Preeclampsia

Marin

Goga

Vasilățeanu

et al. 2019

2019 E-Health and Bioengineering Conference (EHB)

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This paper is written in the context of the international Eurostars project, i-bracelet. The main objective of the i-bracelet project-"Intelligent bracelet for blood pressure monitoring and detection of preeclampsia" is the creation of a portable medical device for uninterrupted monitoring of blood pressure and to detect the blood pressure problems (such as hypertension) and, in particular, preeclampsia. In the current paper is described the software component of this system used for monitoring, viewing and analyzing the blood pressure values coming from a smart bracelet developed in the context of the project. The software solution is available for Android and iOS phone users, as well as it is accessible from a browser. As a conclusion, the blood pressure of the future mothers should be monitored for living a safer and healthier life.

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“…The dynamic relationship between FHR variability and UC has been compared and confirmed with previous documented work. The fetal FHR variations like accelerations, decelerations (early, late, and prolonged) are correlated with the uterine contractions [140].…”

Section: Ultrasoundmentioning

confidence: 99%

N on - Invasive Feto - Maternal Well - Being Monitoring: A Review of Methods

Queyam¹,

Pahuja²,

Singh³

2017

JESTR

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Monitoring of fetal and maternal well-being is extremely critical during pregnancy and during labor to reduce the occurrence of fetal and maternal distress in high risk pregnancies. There are many approaches to identify and quantify the real-time feto-maternal well-being by measuring physiological parameters viz. fetal movement, fetal temperature, fetal respiration rate, fetal kick count, fetal heart rate, maternal ECG acquired from both chest and abdomen region, uterine contraction, blood SpO2 concentration, amniotic fluid pH etc. In this paper, different techniques to acquire and measure these physiological parameters non-invasively are evaluated and compared for the purpose of monitoring fetomaternal well-being.

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Automatic analysis of the fetal heart rate variability and uterine contractions

Cited by 31 publications

References 10 publications

A systematic review of automated pre-processing, feature extraction and classification of cardiotocography

A systematic review of automated pre-processing, feature extraction and classification of cardiotocography

Smart Solution for the Detection of Preeclampsia

N on - Invasive Feto - Maternal Well - Being Monitoring: A Review of Methods

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