MyMedR

Displaying all 5 publications

Abstract:

Sort:

Fetal heart rate monitoring based on independent component analysis

Najafabadi FS, Zahedi E, Mohd Ali MA

Comput Biol Med, 2006 Mar;36(3):241-52.
PMID: 16446158

In this paper, an algorithm based on independent component analysis (ICA) for extracting the fetal heart rate (FHR) from maternal abdominal electrodes is presented. Three abdominal ECG channels are used to extract the FHR in three steps: first preprocessing procedures such as DC cancellation and low-pass filtering are applied to remove noise. Then the algorithm for multiple unknown source extraction (AMUSE) algorithm is fed to extract the sources from the observation signals include fetal ECG (FECG). Finally, FHR is extracted from FECG. The method is shown to be capable of completely revealing FECG R-peaks from observation leads even with a SNR=-200dB using semi-synthetic data.

Matched MeSH terms: Fetal Monitoring/methods*
Fetal heart rate monitoring device using condenser microphone sensor: Validation and comparison to standard devices

Ahmad HAB, El-Badawy IM, Singh OP, Hisham RB, Malarvili MB

Technol Health Care, 2018;26(4):573-579.
PMID: 29758955 DOI: 10.3233/THC-171067

BACKGROUND: Fetal heart rate (FHR) monitoring device is highly demanded to assess the fetus health condition in home environments. Conventional standard devices such as ultrasonography and cardiotocography are expensive, bulky and uncomfortable and consequently not suitable for long-term monitoring. Herein, we report a device that can be used to measure fetal heart rate in clinical and home environments.
METHODS: The proposed device measures and displays the FHR on a screen liquid crystal display (LCD). The device consists of hardware that comprises condenser microphone sensor, signal conditioning, microcontroller and LCD, and software that involves the algorithm used for processing the conditioned fetal heart signal prior to FHR display. The device's performance is validated based on analysis of variance (ANOVA) test.
RESULTS: FHR data was recorded from 22 pregnant women during the 17th to 37th week of gestation using the developed device and two standard devices; AngelSounds and Electronic Stethoscope. The results show that F-value (1.5) is less than F𝑐𝑟𝑖𝑡, (3.1) and p-value (p> 0.05). Accordingly, there is no significant difference between the mean readings of the developed and existing devices. Hence, the developed device can be used for monitoring FHR in clinical and home environments.

Matched MeSH terms: Fetal Monitoring/methods*
Transabdominal fetal heart rate detection using NIR photopleythysmography: instrumentation and clinical results

Gan KB, Zahedi E, Mohd Ali MA

IEEE Trans Biomed Eng, 2009 Aug;56(8):2075-82.
PMID: 19403354 DOI: 10.1109/TBME.2009.2021578

In obstetrics, fetal heart rate (FHR) detection remains the standard for intrapartum assessment of fetal well-being. In this paper, a low-power (< 55 mW) optical technique is proposed for transabdominal FHR detection using near-infrared photoplesthysmography (PPG). A beam of IR-LED (890 nm) propagates through to the maternal abdomen and fetal tissues, resulting in a mixed signal detected by a low-noise detector situated at a distance of 4 cm. Low-noise amplification and 24-bit analog-to-digital converter resolution ensure minimum effect of quantization noise. After synchronous detection, the mixed signal is processed by an adaptive filter to extract the fetal signal, whereas the PPG from the mother's index finger is the reference input. A total of 24 datasets were acquired from six subjects at 37 +/- 2 gestational weeks. Results show a correlation coefficient of 0.96 (p-value < 0.001) between the proposed optical and ultrasound FHR, with a maximum error of 4%. Assessment of the effect of probe position on detection accuracy indicates that the probe should be close to fetal tissues, but not necessarily restricted to head or buttocks.

Matched MeSH terms: Fetal Monitoring/methods
Fulltext A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being

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: Fetal Monitoring/methods*
Real-time signal processing for fetal heart rate monitoring

Ibrahimy MI, Ahmed F, Mohd Ali MA, Zahedi E

IEEE Trans Biomed Eng, 2003 Feb;50(2):258-62.
PMID: 12665042

An algorithm based on digital filtering, adaptive thresholding, statistical properties in the time domain, and differencing of local maxima and minima has been developed for the simultaneous measurement of the fetal and maternal heart rates from the maternal abdominal electrocardiogram during pregnancy and labor for ambulatory monitoring. A microcontroller-based system has been used to implement the algorithm in real-time. A Doppler ultrasound fetal monitor was used for statistical comparison on five volunteers with low risk pregnancies, between 35 and 40 weeks of gestation. Results showed an average percent root mean square difference of 5.32% and linear correlation coefficient from 0.84 to 0.93. The fetal heart rate curves remained inside a +/- 5-beats-per-minute limit relative to the reference ultrasound method for 84.1% of the time.

Matched MeSH terms: Fetal Monitoring/methods*