PSD modifications of FHRV due to interpolation and CTG storage rate

Cesarelli, Mario; Romano, Maria; Ruffo, M.; Bifulco, Paolo; Pasquariello, G.; Fratini, Antonio

doi:10.1016/j.bspc.2010.10.002

Cited by 20 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Preliminary results here shown ( Figure 3 ) confirmed the usefulness of this methodology. About PSD computation, in previous works [ 34 , 37 ], we used the Lomb method which can be applied directly on uneven series; however, it has too long computational time by losing an advantage of the frequency analysis that can be used, if desired, also for real-time analysis; therefore, for successive as well as for this work we employed STFT. Furthermore, comparing different papers and taking into account experimental results obtained on our database, we decided to define for FHR signals the following bands limits: 0–0.05 Hz for VLF; 0.05–0.2 Hz for LF; and 0.2–1 Hz for HF.…”

Section: Discussionmentioning

confidence: 99%

“…This window is shifted sample by sample and a new PSD is computed each time [ 35 ]. To be able to use the STFT, the FHR signal was previously interpolated (4 Hz sampling rate) by means of cubic interpolation, which has been demonstrated to reduce the error introduced [ 37 ]. Then, by means of a simple integral rule, we have computed the power values, absolute (called P LF , P HF ), and percentage, with respect to the total power (called LF%, HF%), in the bands defined above.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

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

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

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

View full text Add to dashboard Cite

show abstract

“…We did not compute across a gap [35] when the length of the missing data was 20 seconds or more -the value obtained based on our experiments. For the purpose of this paper cubic Hermite spline interpolation was used for equidistant 4 Hz data re-sampling since it is convenient for signal analysis and also it is the least prone to errors when frequency spectrum is estimated [36]. The spline interpolation also introduces nonlinearity, however, the amount of nonlinearity should be approximately the same for normal and pathological FHR.…”

Section: Signal Preprocessingmentioning

confidence: 99%

Using nonlinear features for fetal heart rate classification

Spilka

Chudáček

Koucký

et al. 2012

Biomedical Signal Processing and Control

117

View full text Add to dashboard Cite

Fetal heart rate (FHR) is used to evaluate fetal well-being and enables clinicians to detect ongoing hypoxia during delivery. Routine clinical evaluation of intrapartum FHR is based on macroscopic morphological features visible to the naked eye. In this paper we evaluated conventional features and compared them to the nonlinear ones in the task of intrapartum FHR classification. The experiments were performed using a database of 217 FHR records with objective annotations, i.e. pH measurement. We have proven that the addition of nonlinear features improves accuracy of classification. The best classification results were achieved using a combination of conventional and nonlinear features with sensitivity of 73.4%, specificity of 76.3%, and F-measure of 71.9%. The best selected nonlinear features were: Lempel Ziv complexity, Sample entropy, and fractal dimension estimated by Higuchi method. Since the results of automatic signal evaluation are easily reproducible, the process of FHR evaluation can become more objective and may enable clinicians to focus on additional non-cardiotocography parameters influencing the fetus during delivery.

show abstract

“…Relative motion between patient and electrodes (but also if an individual is subjected to vibration for example in a vehicle [24]) can generate large artifacts in bioelectric recordings that should be appropriately processed [25,26]. Lastly, appropriate processing of the heart rate [27,28] can contribute to identify possible arrhythmias that can hinder identification.…”

Section: Discussionmentioning

confidence: 99%

Individual identification using electrocardiogram morphology

Fratini

Sansone

Bifulco

et al. 2013

2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

Self Cite

View full text Add to dashboard Cite

The use of electrocardiogram as biometric has raised attention in the last decade and a wide variety of ECG features were explored to verify the feasibility of such a signal. In this work the authors aim to describe a simple template based approach to the electrocardiographic biometric identification using the morphology of individual's heartbeat. The developed algorithm was tested on different recordings made available in the Physionet public database Fantasia: two different sets of heartbeats were extracted from individual recordings one was used for the template building while the second for the tests. The performances of the algorithm are encouraging with a true acceptance rate of 99.4%, however, the procedure needs to be tested on different recordings of the same individual, or during the course of a whole day or physical activity

show abstract

PSD modifications of FHRV due to interpolation and CTG storage rate

Cited by 20 publications

References 22 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

Using nonlinear features for fetal heart rate classification

Individual identification using electrocardiogram morphology

Contact Info

Product

Resources

About