scholarly journals Effects of Classical Music, Natural and Murottal Music on Fetal Well-Being

2020 ◽  
Vol 4 (7) ◽  
pp. 222-225
Author(s):  
Rahayu ` Sumaningsih ◽  
Teta Puji Rahayu ◽  
Budi Joko Santosa
Keyword(s):  
Heart Rate ◽  
Fetal Heart Rate ◽  
Classical Music ◽  
Fetal Heart ◽  
Well Being ◽  
Mean Values ◽  
Sense Of Security ◽  
Before And After ◽  
Independent Variable ◽  
Fetal Wellbeing

Music affects to human psychology, provides a sense of security, comfort and fun. Classical, natural and murottal music has a tone, rhythm, speed, gentle meter capable of stimulating alpha waves, calmness, and relaxation, beneficial to the well-being of the fetus. The purpose of this study is to describe classical, natural and murotal music on fetal well-being. This Quasi-Experiment Research with pretest-posttest design. A sample of 40 individuals was divided into 4 groups of mothers. The independent variable is classical music, natural, murotal and without music. The dependent variable is fetal well-being. The mean values before and after the intervention naturally were calculated. The results of fetal well-being based on the fetal heart rate of the classical music group before treatment there were 10% of fetuses experiencing mild aspysia after treatment of the fetus experiencing 0% aspysia. Natural and Murottal Music Group before and after treatment 100% normal fetal heart rate, group without music, before and after treatment 50% of fetuses experience Mild Aspysia. Fetal wellbeing results are based on Apgar Score, the Classical Music group after listening to classical music 10% experienced mild Aspysia. Natural Music Group and Murottal after listening to natural music and murottal 100% of babies under normal circumstances. The group without music after birth 50% of babies experience mild Aspysia. Conclusion, classical music overcomes mild asphyxia based on fetal heart rate, natural and murrotal music effectively maintains fetal well-being until birth. Keywords: classical music; natural music; murottal; fetal well-being

scholarly journals Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals

2021 ◽  
Vol 9 (1) ◽  
pp. 8
Author(s):  
Alfonso Maria Ponsiglione ◽  
Francesco Amato ◽  
Maria Romano
Keyword(s):  
Nonlinear Dynamics ◽  
Heart Rate ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Heart Rhythm ◽  
Decision Support Tool ◽  
Support Tool ◽  
Mean Values ◽  
Linear And Nonlinear ◽  
Fetal Wellbeing

In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), there are still shadows hindering a comprehensive understanding of how linear and nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose a straightforward processing and modeling route for a deeper understanding of the relationships between the characteristics of the FHR signal. A multiparametric modeling and investigation of the factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural networks. The obtained results show that linear features are more influential compared to nonlinear ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable and reliable information to clinicians and researchers.

Validation of a new algorithm for the short-term variation of the fetal heart rate: an antepartum prospective study

2018 ◽  
Vol 46 (6) ◽  
pp. 599-604 ◽  
Author(s):  
Christina Kouskouti ◽  
Hella Jonas ◽  
Kerstin Regner ◽  
Pia Ruisinger ◽  
Julia Knabl ◽  
...  
Keyword(s):  
Heart Rate ◽  
Reference Values ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Normal Values ◽  
Short Term ◽  
Mean Values ◽  
Relevant Reference ◽  
Term Variation ◽  
The Mean

Abstract Aims: Currently one of the most widespread systems for the computerized analysis of the fetal heart rate (FHR) is the Dawes-Redman system, where the short-term variation (STV) of the FHR is measured by dividing each minute into 16 segments (STV16). Technical progress has allowed for the development of a new algorithm, which measures the STV by dividing each minute into 240 segments (STV240), thus approximating the beat-to-beat variation. The STV240 still lacks reference values. Our aim was to develop clinically relevant reference values for the STV240 and compare them to the ones for the STV16. Methods: In a single centre, observational study, a total of 228 cardiotocograms were registered and subsequently analyzed with both algorithms (STV240 and STV16). Results: The 95% confidence interval (CI) was calculated for both algorithms. The values of the STV240 were significantly lower in comparison to the ones of the STV16. Not only the mean values but also the 95th percentile of the STV240 lay beneath the existent cut-off value for the STV16. Conclusions: Every clinician using the new algorithm must be aware that the normal values for the STV240 lie beneath the, up until now, established cut-off values for the STV16.

Studies in fetal well-being: Variations in fetal heart rate

1958 ◽  
Vol 76 (5) ◽  
pp. 998-1012 ◽  
Author(s):  
Louis M. Hellman ◽  
Morton A. Schiffer ◽  
Schuyler G. Kohl ◽  
Walter E. Tolles
Keyword(s):  
Heart Rate ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Well Being

FETAL HEART RATE VARIABILITY ANALYSIS FROM PHONOCARDIOGRAPHIC RECORDINGS

2011 ◽  
Vol 11 (05) ◽  
pp. 1315-1331 ◽  
Author(s):  
VIJAY S. CHOURASIA ◽  
ANIL KUMAR TIWARI
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Fetal Heart Rate ◽  
Heart Sound ◽  
Fetal Heart ◽  
Heart Rate Variability Analysis ◽  
Nonlinear Features ◽  
Fetal Heart Rate Variability ◽  
Fetal Wellbeing

This paper presents an algorithm for classification of fetal health status using fetal heart rate variability (fHRV) analysis through phonocardiography. First, the fetal heart sound signals are acquired from the maternal abdominal surface using a specially developed Bluetooth-based wireless data recording system. Then, fetal heart rate (FHR) traces are derived from these signals. Ten numbers of linear and nonlinear features are extracted from each FHR trace. Finally, the multilayer perceptron (MLP) neural network is used to classify the health status of the fetus. Results show very promising performance toward the prediction of fetal wellbeing on the set of collected fetal heart sound signals. Finally, this work is likely to lead to an automatic screening device with additional potential of predicting fetal wellbeing.

scholarly journals Automated Detection of Fetal Movements Based on Baseline Calculation and Fetal Heart Rate Accelerations

2018 ◽  
Vol 12 (9) ◽  
pp. 173
Author(s):  
Mei-Jia Huang ◽  
Hui-Jin Wang
Keyword(s):  
Heart Rate ◽  
Error Detection ◽  
Fetal Heart Rate ◽  
Electronic Monitoring ◽  
Fetal Heart ◽  
Threshold Value ◽  
Fetal Movement ◽  
Important Indicator ◽  
Fetal Movements ◽  
Fetal Wellbeing

Fetal electronic monitoring is extensive and important in obstetrics. Although fetal movement is ususally used as an important indicator for quantifying fetal wellbeing, non-invasive and long-term monitoring of fetal movement remains challenging. The object of this study is to develop an algorithm for automatic detection of the fetal movements based on the analysis of Doppler ultrasound signals. In order to detect fetal movements automatically, a two-step process was proposed to track fetal movement. In Step 1, to suppress the problem of error detection, we calculated the baseline of the fetal movement signals from actography to extract new signals. In step2, we recalculated the threshold value of fetal movement detection by utilizing the information of fetal heart rate (FHR) acceleration to produced adaptive threshold values. The results showed that the union of results detected by the proposed method from actography and tocography achieved an encouraging performance with highest sensitivity and acceptable positive predictive value (PPV).

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