Displaying all 7 publications

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  1. Krupa N, Ali M, Zahedi E, Ahmed S, Hassan FM
    Biomed Eng Online, 2011;10:6.
    PMID: 21244712 DOI: 10.1186/1475-925X-10-6
    Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'.
    Matched MeSH terms: Cardiotocography/methods*
  2. Krupa BN, Mohd Ali MA, Zahedi E
    Physiol Meas, 2009 Aug;30(8):729-43.
    PMID: 19550027 DOI: 10.1088/0967-3334/30/8/001
    Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is identified by a statistical method. The obtained signal enhancement from the proposed method is validated by comparing the resulting traces with the output obtained by applying classical signal processing methods such as Butterworth low-pass filtering, linear interpolation and a moving average filter on 12 CTG signals. Three obstetricians evaluated all 12 sets of traces and rated the proposed method, on average, 3.8 out of 5 on a scale of 1(lowest) to 5 (highest).
    Matched MeSH terms: Cardiotocography/methods*
  3. Ravindran S, Jambek AB, Muthusamy H, Neoh SC
    Comput Math Methods Med, 2015;2015:283532.
    PMID: 25793009 DOI: 10.1155/2015/283532
    A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.
    Matched MeSH terms: Cardiotocography/methods
  4. Shamala N., Faizal, A.H.
    Medicine & Health, 2018;13(2):202-207.
    MyJurnal
    Trauma is thought to complicate 1 in 12 pregnancies. The management of trauma during pregnancy requires special consideration because pregnancy alters maternal physiology and the foetus is a potential collateral victim. The approach of these cases in the setting of the Emergency Department should not only be diagnostic for any foetal injuries but also prognostic for any future undue outcome. Antenatal traumatic brain injury is a rare but real complication of maternal blunt force trauma. Our case involves a 22-year-old primigravida who suffered a motor vehicle accident and on initial assessment revealed normal foetal assessment but subsequently after premature labour revealed a new born with traumatic brain injury. Early ultrasonographic evaluation and observational period with continuous electronic foetal monitoring may improve the detection and emergent treatment in these cases.
    Matched MeSH terms: Cardiotocography
  5. Al-Yousif S, Jaenul A, Al-Dayyeni W, Alamoodi A, Jabori I, Md Tahir N, et al.
    PeerJ Comput Sci, 2021;7:e452.
    PMID: 33987454 DOI: 10.7717/peerj-cs.452
    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.

    Matched MeSH terms: Cardiotocography
  6. Neoh HS, Kumarasamy S, Raman S
    Med J Malaysia, 1990 Mar;45(1):37-41.
    PMID: 2152067
    This report deals with the use of a relatively new investigative technique (Doppler ultrasound) in the management of a case of early onset pre-eclampsia and discusses the benefit of this new technique over conventional methods of fetal monitoring.
    Matched MeSH terms: Cardiotocography
  7. Faridah Hanim Zam Zam, Nazimah Idris, Tham, Seng Woh
    MyJurnal
    Background: Fetal surveillance in labour is performed mostly to identify fetuses at risk of hypoxia in order to reduce neonatal morbidity and mortality by initiating timely intervention. While normal and abnormal fetal heart rate (FHR) patterns have been well recognised and characterized for the first stage of labour, FHR patterns during the second stage of labour commonly showed some forms of abnormalities leading to problems in interpretation, particularly in predicting fetal hypoxia and acidosis. This study aims to identify patterns of FHR tracing during the second stage of labour associated with neonatal acidosis. Methods: A prospective cross sectional study was conducted in the Labour Ward of a state referral hospital. The study population were patients with low-risk
    singleton pregnancies between 37 to 42 weeks gestation who had normal cardiotocograph (CTG) tracing in the first stage of labour. CTG was recorded during the second stage of labour and neonatal umbilical cord blood was obtained for acid-base analysis immediately after birth prior to the delivery of placenta. FHR patterns were grouped according to modified Melchior and Barnard’s
    classification and matched with neonatal acid-base status. Patients with normal FHR pattern in the second stage acted as control. Results: A total of 111 matched pairs were analysed. Ninety nine (89.2%) second stage FHR tracings showed abnormal features when compared to control. There were significantly more neonatal acidosis and hypercapnia in type 1b, type 2a, type 2b and type 3 CTG patterns compared to control, in increasing order of severity. In addition, types 2b and 3 showed significant difference in the base excess. Conclusion: Certain second stage fetal heart rate
    patterns were found to be associated with neonatal acidosis.
    Matched MeSH terms: Cardiotocography
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