Symbolic dynamic and frequency analysis in foetal monitoring

Romano, Maria; D’Addio, Giovanni; Clemente, Fabrizio; Ponsiglione, Alfonso Maria; Improta, Giovanni; Cesarelli, Mario

doi:10.1109/memea.2014.6860122

Cited by 38 publications

(9 citation statements)

References 20 publications

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“…Nevertheless, a standardized definition of FHRV is still lacking and subject to changes and updates. Traditional analysis lack of standardized methods for computing time or frequency domain indexes and the relationship between FHRV and foetal growth is actually not completely clear and most of the studies inspecting this issue are by now rather old [ 52 , 54 , 71 , 72 ].…”

Section: Introductionmentioning

confidence: 99%

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

Romano

Iuppariello

Ponsiglione

et al. 2016

Computational and Mathematical Methods in Medicine

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Monitoring of foetal heart rate and its variability (FHRV) covers an important role in assessing health of foetus. Many analysis methods have been used to get quantitative measures of FHRV. FHRV has been studied in time and in frequency domain and interesting clinical results have been obtained. Nevertheless, a standardized definition of FHRV and a precise methodology to be used for its evaluation are lacking. We carried out a literature overview about both frequency domain analysis (FDA) and time domain analysis (TDA). Then, by using simulated FHR signals, we defined the methodology for FDA. Further, employing more than 400 real FHR signals, we analysed some of the most common indexes, Short Term Variability for TDA and power content of the spectrum bands and sympathovagal balance for FDA, and evaluated their ranges of values, which in many cases are a novelty. Finally, we verified the relationship between these indexes and two important parameters: week of gestation, indicator of foetal growth, and foetal state, classified as active or at rest. Our results indicate that, according to literature, it is necessary to standardize the procedure for FHRV evaluation and to consider week of gestation and foetal state before FHR analysis.

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Section: Introductionmentioning

confidence: 99%

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

Romano

Iuppariello

Ponsiglione

et al. 2016

Computational and Mathematical Methods in Medicine

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“…In previous works [4,27,71,72], FHRV analysis through the SD was carried out, and this technique was compared with other traditional indices. Results showed how the SD is a more reliable measure than frequency domain parameters in assessing fetal development during the course of pregnancy, in accordance with the above-reported results.…”

Section: Symbolic Dynamics Analysismentioning

confidence: 99%

A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals

Ponsiglione

Cosentino

Cesarelli

et al. 2021

Sensors

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The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing autonomous nervous system development, many different approaches for computerized processing and analysis of FHR patterns have been proposed in the literature. The objective of this review is to describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their main achievements and discussing the value they brought to the scientific and clinical community. The review explores the following two main approaches to the processing and analysis of FHR signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of accelerations in FHR signals is also examined in a case study conducted by the authors.

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“…In this work, after computation of the RR series, the authors choose an alphabet of only five symbols leading hence to four word classes to which real CTG data have been classified according to the values of a new variability index (VI) in order to find its possible correlation with spontaneous deliveries (SD) and caesarean section (CS). In a similar work [61], the results obtained with the SDA method have been compared to those obtained by using classical parameters -like morphological features, computed with frequency domain analysis (FDA) tools in order to assess the foetal well-being and development.…”

Section: Various Approachesmentioning

confidence: 99%

Survey on Cardiotocography Feature Extraction Algorithms for Foetal Welfare Assessment

Haritopoulos

Illanes

Nandi

2016

XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016

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Abstract-Since its inception forty years ago as a way to control birth process, the cardiotocograph (CTG) has emerged over time and became the undisputed leader worldwide of noninvasive intrapartum foetal monitoring systems. The CTG signals conveying a lot of information, it is very difficult to interpret them and act accordingly even for specialists; hence, researchers have started looking for characteristics which could be correlated with a particular pathological state of the foetus. Thereby, many features appeared in the literature, ranging from the most common ones to artificially generated features, and computed using a wide variety of signal processing-based analysis tools: time scale, spectral or non-linear analysis, to name but a few. This survey paper, presents in a hierarchical order the most common processing steps of a CTG signal and focuses primarily on the feature extraction methods for foetal heart rate (FHR) analysis reported in the literature during the last decade. Also, some feature classification methods are reported before a brief discussion which concludes this work.

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Symbolic dynamic and frequency analysis in foetal monitoring

Cited by 38 publications

References 20 publications

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals

Survey on Cardiotocography Feature Extraction Algorithms for Foetal Welfare Assessment

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