Combining electrohysterography and heart rate data to detect labour

Altini, Marco; Rossetti, Elisa; Rooijakkers, Michiel; Penders, Julien; Lanssens, Dorien; Grieten, Lars; Gyselaers, Wilfried

doi:10.1109/bhi.2017.7897227

Cited by 11 publications

(7 citation statements)

References 22 publications

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“…Several devices exist for tracking fetal heart rate and movement, although none had been FDA approved at the time of this review. The Bloomlife Smart Pregnancy Tracker (CA, USA), a wearable device for tracking contractions in the third trimester of pregnancy, was shown to have an 87% success rate in predicting delivery within 24-h using electrohysterography and HR [18,120]. Their labor risk score was developed based on in-hospital data from 55 pregnant women and was evaluated on recordings from 142 pregnant women in free-living conditions.…”

Section: Maternal Pre-and Neo-natal Carementioning

confidence: 99%

Wearables and the Medical Revolution

2018

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Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events. This paper reviews current and prospective wearable technologies and their progress toward clinical application. We describe technologies underlying common, commercially available wearable sensors and early-stage devices and outline research, when available, to support the use of these devices in healthcare. We cover applications in the following health areas: metabolic, cardiovascular and gastrointestinal monitoring; sleep, neurology, movement disorders and mental health; maternal, pre- and neo-natal care; and pulmonary health and environmental exposures. Finally, we discuss challenges associated with the adoption of wearable sensors in the current healthcare ecosystem and discuss areas for future research and development.

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Section: Maternal Pre-and Neo-natal Carementioning

confidence: 99%

Wearables and the Medical Revolution

2018

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“…Other features-namely, root mean square value, autocorrelation first zero-crossing, contraction, intensity, mean crossing, and normalized range of the signal-are also used. [9][10][11] Frequency domain features include mean frequency, dominant frequency, standard deviation of frequency, median frequency, spectral moments, variance of central frequency, and mean power. 11,12 Recently, timefrequency approaches are used to characterize the EHG signals.…”

Section: Introductionmentioning

confidence: 99%

“…Several works have been done on preterm prediction by using EHG signals. It includes the analysis of the time, 9–11 frequency, 11,12 time–frequency, 13–15 and nonlinear 16–19 domains. The results obtained using these methods have high variance and hence are not used in current clinical practices.…”

Section: Introductionmentioning

confidence: 99%

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Multifractal analysis of uterine electromyography signals to differentiate term and preterm conditions

Punitha

Swaminathan

2019

Proc Inst Mech Eng H

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In this study, an attempt has been made to identify the origin of multifractality in uterine electromyography signals and to differentiate term (gestational age. 37 weeks) and preterm (gestational age 4 37 weeks) conditions by multifractal detrended moving average technique. The signals obtained from a publicly available database, recorded from the abdominal surface during the second trimester, are used in this study. The signals are preprocessed and converted to shuffle and surrogate series to examine the source of multifractality. Multifractal detrended moving average algorithm is applied on all the signals. The presence of multifractality is verified using scaling exponents, and multifractal spectral features are extracted from the spectrum. The variation of multifractal features in term and preterm conditions is analyzed statistically using Student's t-test. The results of scaling exponents show that the uterine electromyography or electrohysterography signals reveal multifractal characteristics in term and preterm conditions. Further investigation indicates the existence of long-range correlation as the primary source of multifractality. Among all extracted features, strength of multifractality, exponent index, and maximum and peak singularity exponents are statistically significant (p \ 0.05) in differentiating term and preterm conditions. The coefficient of variation is found to be lower for strength of multifractality and peak singularity exponent, which reveal that these features exhibit less inter-subject variance. Hence, it appears that multifractal analysis can aid in the diagnosis of preterm or term delivery of pregnant women.

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“…The creation of seamless interfaces between biological systems and multifunctional devices is a vital step towards the fabrication of next-generation wearable devices for applications in teleoperation, [1,2] medical treatments, [3,4] health monitoring, [5–7] and even personal entertainment [8–10] . Commercial wearable devices are either rigid (e.g., smart fitness watches), or soft but with determinant shapes (e.g., haptic gloves for virtual reality applications).…”

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confidence: 99%

3D Printed Functional and Biological Materials on Moving Freeform Surfaces

et al. 2018

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Conventional 3D printing technologies typically rely on open-loop, calibrate-then-print operation procedures. An alternative approach is adaptive 3D printing, which is a closed-loop method that combines real-time feedback control and direct ink writing of functional materials in order to fabricate devices on moving freeform surfaces. Here, it is demonstrated that the changes of states in the 3D printing workspace in terms of the geometries and motions of target surfaces can be perceived by an integrated robotic system aided by computer vision. A hybrid fabrication procedure combining 3D printing of electrical connects with automatic pick-and-placing of surface-mounted electronic components yields functional electronic devices on a free-moving human hand. Using this same approach, cell-laden hydrogels are also printed on live mice, creating a model for future studies of wound-healing diseases. This adaptive 3D printing method may lead to new forms of smart manufacturing technologies for directly printed wearable devices on the body and for advanced medical treatments.

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Combining electrohysterography and heart rate data to detect labour

Cited by 11 publications

References 22 publications

Wearables and the Medical Revolution

Wearables and the Medical Revolution

Multifractal analysis of uterine electromyography signals to differentiate term and preterm conditions

3D Printed Functional and Biological Materials on Moving Freeform Surfaces

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