Non Invasive Foetal Monitoring with a Combined ECG - PCG System

Ruffo, M.; Cesarelli, Mario; Jin, Craig; McEwan, Alistair; Sullivan, Clair J.; Bifulco, Paolo; Romano, Maria; Shephard, Richard; Schaik, and André van

doi:10.5772/13554

Cited by 7 publications

(11 citation statements)

References 66 publications

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“…2) Band Pass Filter: Derau-derau pada sinyal fPCG yang bersumber dari suara organ ibu dan lingkungan eksternal memiliki karakteristik frekuensi masing-masing. Derau yang diakibatkan oleh aktivitas organ tubuh ibu biasanya berada di bawah 20 Hz [15], sedangkan akibat pengaruh eksternal di atas 70 Hz [4], [14], [16], [17]. Sebuah penelitian memberikan pendapat lain terkait derau akibat aktivitas organ ibu, yaitu berada di bawah 25 Hz [18].…”

Section: ) Normalisasiunclassified

Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Zulherman

Hendry

Adam

2020

JNTETI

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Monitoring of Fetal Heart Rate (FHR) in the pregnancy period commonly uses the Doppler-based instruments despite having several disadvantages, such as high-cost and complexity of the monitoring system. Implementation of the passive and non-invasive method based on fetal phonocardiogram (fPCG), the acoustic recording of fetus cardiac signal, can be used as a potentially economical long-term monitoring device for diagnosis. Because the interference signal from the maternal women exists, the matured denoising technique was needed to implement the fPCG method to diagnose the fetus' well-being condition. The denoising system based on Dual-tree Complex Wavelet Transforms (DTCWT) was proposed in this paper. The proposed method was evaluated using Signal to Noise Ratio (SNR). Based on the experiment result from 37 fPCG signals from physio.net, the DTCWT system performance was compared with the Discrete Wavelet Transform (DWT). There were 24 CWT’s denoised fPCG signals that have successfully outperformed DWT’s SNR. DTCWT has also reduced the noises in the range of 30 Hz–80 Hz. Also, it emphasized the existence of dominant frequencies in the range of 60 Hz–65 Hz.

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Section: ) Normalisasiunclassified

Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Zulherman

Hendry

Adam

2020

JNTETI

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“…Recently, ultrasonic Doppler technology has been extensively utilized for the assessment of fetal heart sounds and fetal heart rate (FHR) for pregnancy-related complications [15]. M. Ruffo et al proposed a combined ECG-PCG system for fetal heart rate detection and related anomalies [16]. Various other research also focuses on early detection fetal heart rate by developing a web-based fetal monitoring system [17] [15], PC-based fetal PCG measurement [18] [19], and simulation of maternal abdominal conditions for PCG based prenatal monitoring [20].…”

Section: Related Workmentioning

confidence: 99%

Doppler Ultrasound Based Non-Invasive Heart Rate Telemonitoring System for Wellbeing Assessment

Queyam¹,

Pahuja²,

Singh³

2018

IJISA

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Telemonitoring in the field of healthcare has vastly improved the quality of clinical diagnosis and disease prevention by providing timely medical consultation to people living in rural and remote areas. To monitor the health state of a patient certain vital physiological parameter like electrocardiogram (ECG), respiration rate, blood pressure, oxygen saturation, etc. are acquired and analyzed. Listening to the heart sounds (auscultation) is also a quick method to monitor the health state of the patient's heart. In this paper, we propose the use of a portable Doppler ultrasound sensor for measuring the heart sounds reliably and to transmit the data for further clinical telemonitoring. We have developed an ultrasound-based hardware prototype which is non-invasive in nature and easy to operate. Its portability, high accuracy, low cost, and wireless nature make this device suitable for home-based self-diagnostic applications. The developed prototype was successfully able to capture both fundamental heart sounds S 1 and S 2 reliably and transfer the signal wirelessly to the LabVIEW-based monitoring and data logging unit. This unit extracts clinically useful health information like heart rate (HR), R-R interval and heart rate variability (HRV) using signal processing algorithms. Health information is then transmitted via the Internet to a distant hospital for further improved clinical diagnosis and consultancy. The prototype was validated on 40 healthy males in the age group of 25-35 years, and the results show an overall accuracy of 96.74% in HR detection when compared with an ECG sensor, a photoplethysmograph (PPG) sensor, a pulse oximeter device and manual auscultation.

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“…In order to use BCI2000, a specialized bridge software is required to interface the digital converter of choice to the core of the software. Several commercial and popular hardware solutions (including the Open-EEG hardware ), are already included in BCI2000; in order to use our BIOADC we needed to write our own bridge software using the supplied code template [ 14 , 51 , 52 ]. The BIOADC is an open source, 32-channel analogue to digital converter (ADC) that supports programmable gain control for all the channels.…”

Section: Introductionmentioning

confidence: 99%

“…In our original implementation, the system was intended to be stand-alone; hence, it was paired with a supporting ARM processor to record the data on an SD card. However, the device can be also connected (with galvanically isolated connection) to a standard USB port and hence to a standard computer [ 51 ]. To allow full reproduction of the hardware, all the production files and bill of materials for both boards, BIOADC, and the analogue electrodes’ front-end are included together with the firmware and the necessary BCI2000 device driver as both source code and compiled code.…”

Section: Introductionmentioning

confidence: 99%

Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented

Bifulco

Cesarelli

McEwan

et al. 2019

Sensors

Self Cite

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The Open-electroencephalography (EEG) framework is a popular platform to enable EEG measurements and general purposes Brain Computer Interface experimentations. However, the current platform is limited by the number of available channels and electrode compatibility. In this paper we present a fully configurable platform with up to 32 EEG channels and compatibility with virtually any kind of passive electrodes including textile, rubber and contactless electrodes. Together with the full hardware details, results and performance on a single volunteer participant (limited to alpha wave elicitation), we present the brain computer interface (BCI)2000 EEG source driver together with source code as well as the compiled (.exe). In addition, all the necessary device firmware, gerbers and bill of materials for the full reproducibility of the presented hardware is included. Furthermore, the end user can vary the dry-electrode reference circuitry, circuit bandwidth as well as sample rate to adapt the device to other generalized biopotential measurements. Although, not implemented in the tested prototype, the Biomedical Analogue to Digital Converter BIOADC naturally supports SPI communication for an additional 32 channels including the gain controller. In the appendix we describe the necessary modification to the presented hardware to enable this function.

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Non Invasive Foetal Monitoring with a Combined ECG - PCG System

Cited by 7 publications

References 66 publications

Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Perbandingan Real-Valued dan Complex Wavelet Transform pada Denoising Sinyal Fetal-Phonocardiograms (Comparison of Fetal-Phonocardiogram Signal Denoising based on Real- Valued and Complex Wavelet Transform)

Doppler Ultrasound Based Non-Invasive Heart Rate Telemonitoring System for Wellbeing Assessment

Fully Open-Access Passive Dry Electrodes BIOADC: Open-Electroencephalography (EEG) Re-Invented

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