Fetal heart rate monitoring system with mobile internet

Yang, Wendi; Yang, Kai; Jiang, Hanjun; Wang, Zhihua; Lin, Qingliang; Wen, Jia

doi:10.1109/iscas.2014.6865165

Cited by 26 publications

(6 citation statements)

References 4 publications

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“…Some representative results of these on-body tests are reported in Figs. 8, where the received power is plotted versus the SILO locking frequency ("maximum hold" mode of the spectrum analyzer has been used), confirming that, during respiration, the SILO input signal is frequencymodulated by the chest displacements. In practice, human breath acts as a frequency modulator and generates a frequency-shift-keying (FSK) signal whose deviation is proportional to the displacement of the chest with respect to the sensor's antenna.…”

Section: B On-body Breath Testsmentioning

confidence: 64%

“…Focusing on smart health (or e-health) applications [1], the adoption of a consistent network of sensors able to continuously monitor and transmit vital data to healthcare controllers [2], has resulted in the creation of the so-called wireless body area networks (WBAN). In particular, the correct detection of human vital signs, e.g., heart rate [3]- [6], fetal cardiac activity [7], [8], and especially breath rate giacomo.paolini4@unibo.it, mazen.shanawani@unibo.it, diego.masotti@unibo.it, alessandra.costanzo@unibo.it).…”

Section: Introductionmentioning

confidence: 99%

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Respiratory Activity Monitoring by a Wearable 5.8 GHz SILO With Energy Harvesting Capabilities

Paolini

Shanawani

Masotti

et al. 2022

IEEE J. Electromagn. RF Microw. Med. Biol.

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Envisioned scenario for the wearable sensor aiming at normal and deep breath rate detection, working at 5.8 GHz, and able to harvest energy for feeding a commercial microcontroller unit. Take-Home Messages• This work describes the design and the realization of a wearable sensor working at 5.8 GHz exploiting the self-injection locking radar technique for human breath detection. • The sensor allows detecting inhalations and exhalations of monitored subjects living their normal life, as well as deep and fast breath that could reveal dangerous situations. The device is of reduced dimensions, fully wearable, and is located at a certain distance from the user's body at the chest position. • The sensor architecture is conceived in such a way that it does not need a dedicated receiving station to be placed in the surrounding environment (such as a spectrum analyzer), since an FM-to-AM demodulator is embedded into the sensor itself, with the possibility to work without the need of any anchor nodes nor remotely synchronized receivers. • As a distinctive peculiarity with respect to the already existing solutions, the demodulator can further be exploited as an RF-to-DC rectifier for energy harvesting purposes. The harvested energy can be used, for instance, to supply an ultra-low-power microcontroller equipped with a transceiver in order to send wirelessly breath rate data to a laptop or a smartphone. • Data processing of the rectifier/demodulator output is thus enabled on board with the goal of raising an alarm wirelessly only whenever a dangerous situation is detected (i.e., in presence of hyperventilation). In this way, the power-hungry transmitter operations are minimized with respect to continuous transmission of the breath rate data.

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Section: B On-body Breath Testsmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Respiratory Activity Monitoring by a Wearable 5.8 GHz SILO With Energy Harvesting Capabilities

Paolini

Shanawani

Masotti

et al. 2022

IEEE J. Electromagn. RF Microw. Med. Biol.

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“…This system also needs to be improved in some aspects, such as the design of the handheld terminal [9], the network design of remote monitoring and off-line monitoring, etc. In recent years, with the rapid development of the virtual instrument technology, it has a very broad prospects for development in the field of medical instruments by its powerful features, a combination of both will go far.…”

Section: Discussionmentioning

confidence: 99%

Design of Remote Fetal Heart Rate Monitoring System based on Virtual Instruments

Huang¹,

Deng²,

Fei³

2015

IJCA

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In view of the development of modern medical technology, we use LabVIEW software as a platform to design a kind of remote heart monitoring system. This monitoring system has realized the fetal heart rate data collection, transmission and storage. Using the network technology to connect the hospital center server, the system can check detection records, analyze and print the diagnosis in real-time, reach the aim of remote monitoring. Most functions of the system will be realized by software instead of traditional detection hardware, which will not only greatly reduce the cost of development but also improve the development efficiency.

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“…Some issues, such as premature birth, hypoxia, or intrauterine retardation, are dangerous both for the fetus and for the mother. Fetal monitoring includes methods such as fetal electrocardiography (fECG) [ 1 , 2 , 3 , 6 , 7 , 8 , 9 , 10 , 11 ], fetal phonocardiography (fPCG) [ 4 , 5 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ], fetal echocardiography (fECHO) [ 22 , 23 , 24 , 25 ], fetal magnetocardiography (fMCG) [ 26 , 27 , 28 , 29 , 30 ], and cardiotocography (CTG) [ 9 , 31 , 32 , 33 ], which is based on Doppler ultrasound. Each fetal monitoring method has its advantages as well as disadvantages, and it should be emphasized that, regarding long-term measurements, a 20-min measurement is relatively short in order to obtain real information about the condition of the fetus.…”

Section: Introductionmentioning

confidence: 99%

Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

Jaroš

Martínek

Kahánková

2018

Sensors

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Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

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Fetal heart rate monitoring system with mobile internet

Cited by 26 publications

References 4 publications

Respiratory Activity Monitoring by a Wearable 5.8 GHz SILO With Energy Harvesting Capabilities

Respiratory Activity Monitoring by a Wearable 5.8 GHz SILO With Energy Harvesting Capabilities

Design of Remote Fetal Heart Rate Monitoring System based on Virtual Instruments

Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

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