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An intrauterine pressure generator for educational simulation of labour and delivery.

机译:一种宫内压发生器,用于人工模拟分娩和分娩。

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摘要

Simulation provides a risk free and controllable environment for training of healthcare providers. The limited realism of available simulators and training programs impedes immersive training in obstetric emergencies. In developed countries, intrapartum monitoring in high-risk cases involves continuous evaluation of foetal heart rate and uterine contractions signals. We present an essential component of a high-fidelity simulator for normal and critical situations in labour and delivery, namely an intrauterine pressure generator. The signal model behind the generator consists of a truncated Gaussian curve with the programmable features: amplitude, frequency, duration, and resting tone. Through analysis of 44h of physiological data, we demonstrate that the natural variability of these features and of the baseline pressure can be approximated by deterministic trends and stationary stochastic processes. Signal parameters can be controlled by simulation instructors, scripts, or other models to reflect different patients, pathologies, and evolving clinical situations. Twelve 40-min tracings reflecting three different patients in labour were presented to three clinical experts, who attributed similar realism scores to simulated and to real tracings.
机译:模拟为培训医疗保健提供者提供了无风险且可控制的环境。可用的模拟器和培训程序的有限的现实性阻碍了产科紧急情况下的身临其境的培训。在发达国家,在高危病例中进行分娩期监护涉及对胎儿心率和子宫收缩信号的持续评估。我们介绍了一种高保真模拟器的基本组件,它适用于分娩中的正常和紧急情况,即子宫内压发生器。发生器后面的信号模型由一条截断的高斯曲线组成,该曲线具有可编程特征:幅度,频率,持续时间和静息音。通过对44h生理数据的分析,我们证明了这些特征和基线压力的自然变化可以通过确定性趋势和平稳的随机过程来近似。信号参数可以由模拟讲师,脚本或其他模型控制,以反映不同的患者,病状和不断发展的临床情况。向三名临床专家介绍了反映三名不同分娩患者的十二分钟40分钟描迹,他们将相似的真实度得分归因于模拟和真实描迹。

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