System zur Erzeugung Physiologischer Zeitreihen über Tiefenlernmodellerkennung oder -Vorhersage

Details

Veröffentlichungs-Nr.

EP4740867

Anmeldetag

15. Oktober 2025

Veröffentlichung

13. Mai 2026

Rechtsraum

EP

Abstract

Methods and systems are provided for detecting and predicting uterine activity (UA) from an ultrasound receive signal and/or electrohysterogram (EHG) data, using a neural network model (420) trained using ultrasound time-series data (402) and/or EHG data as input data (404) and time-series tocodynamometer (toco) data as ground truth data (405). After training, the trained UA detection model (430) may be used to detect a timing, duration, and intensity of uterine contractions in new patients with more accuracy than the toco. An output of the trained UA detection model (430) may also be used to train a UA prediction model (470) to predict a next uterine contraction (1210) based on a series of preceding uterine contractions. As a result, the uterine contractions may be detected and/or predicted during electronic fetal monitoring (EFM) without the use of an additional toco device, reducing a cost of the EFM and a number of sensing devices relied on for the EFM.

Anmelder

Firma

GE Precision Healthcare LLC

Land

🇺🇸 USA