Automatic Contraction Detection Using Uterine Electromyography
نویسندگان
چکیده
منابع مشابه
A Machine Learning System for Automatic Detection of Preterm Activity Using Artificial Neural Networks and Uterine Electromyography Data
Background: Preterm births are babies that are born before 37 weeks of gestation. The premature delivery of babies is regarded as a major global public health issue with those affected at greater risk of developing short and long-term complications. The care provided for premature infants has significantly improved. However, it has had no impact on reducing the prevalence of preterm birth. Ther...
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The aim of this paper is to detect fetal heart beats temporally overlapping with the transabdominally-measured QRS-complexes of the mother, non-invasively. Modified, Weighted and uterine contraction interference signal covariance matrix incorporated spectral MUSIC technique is applied. It is based on partitioning the subspace containing the ECG signal bearing the mother and fetal, and the ortho...
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متن کاملUterine Contraction Modeling and Simulation
Building a training system for medical personnel to properly interpret fetal heart rate tracing requires developing accurate models that can relate various signal patterns to certain pathologies. In addition to modeling the fetal heart rate signal itself, the change of uterine pressure that bears strong relation to fetal heart rate and provides indications of maternal and fetal status should al...
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ژورنال
عنوان ژورنال: Applied Sciences
سال: 2020
ISSN: 2076-3417
DOI: 10.3390/app10207014