Results 91 to 100 of about 697 (169)
) 30-minutes electrohysterogram and fetal heart rate (EHG-fHR) recording; b) BPRSA graph denoting presence of coupled periodicities between uterine PRSA (grey line) and fHR BPRSA (black line); c) CPSD analysis of PRSA transformed signals. The coefficient
Tamara Stampalija (338798) +7 more
core +1 more source
a) 30 minutes recording of electrohysterogram (EHG, grey line) and fetal heart rate (fHR, black line) free of signal loss; b) cross power spectral density (CPSD) analysis of original signals, CRAW0.5 at the UC frequency domain proved a significant ...
Tamara Stampalija (338798) +7 more
core +1 more source
Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review. [PDF]
Mendis L +3 more
europepmc +1 more source
Garment design for an ambulatory pregnancy monitoring system
Constant pregnancy monitoring is a promising alternative to reduce the number of stillbirths and preterm delivery due to false alarms. Tele-monitoring systems can provide regular, accurate and timely monitoring to re-duce risks, costs and the time the ...
Bravo, J. +6 more
core +1 more source
Cilj diplomske naloge je bilo razviti grafični uporabniški vmesnik za vizualizacijo, procesiranje in analizo posnetkov elektrohisterograma (EHG). Razvili smo grafični uporabniški vmesnik EHGLab, prilagojen za delo s posnetki EHG v formatu WaveForm ...
Prevc, Jure
core
Objective: To observe the effect of electroacupuncture(EA) of different acupoints on electrical activities of the uterus in rats.Methods: A total of 79 Wistar rats anesthetized with mixture solution of 1.5% chloralose(50 mg/kg) and 25% urethrane(420 mg ...
LIU Jun-ling +2 more
doaj
International audienceThe early delivery of the infants can risk their lives andcause them serious health issues in the future. Artificial intelligencemodels that are trained on the uterine muscular contraction signals(electrohysterogram) have been shown
Ammar, Hadi +5 more
core
Artificial intelligence in obstetrics. [PDF]
Ahn KH, Lee KS.
europepmc +1 more source
Artificial intelligence in preterm birth prediction: a narrative review of current approaches and clinical applicability. [PDF]
Lee Y.
europepmc +1 more source
Developing a prognostic model for predicting preterm birth using a machine learning algorithm. [PDF]
Abdi F +5 more
europepmc +1 more source

