| Title | An intrauterine pressure generator for educational simulation of labour and delivery |
| Publication Type | Journal Article |
| 2010 |
| Authors | Bastos, LF, Lobo, MF, van Meurs, WL, Ayres-de-Campos, D |
| Journal | Medical Engineering and PhysicsMed. Eng. Phys. |
| Volume | 32 |
| Issue | 7 |
| Pagination | 740 - 745 |
| Date Published | 2010/// |
| 13504533 (ISSN) |
| article, Clinical situations, Computer simulation, delivery, Delivery, Obstetric, Developed countries, Educational simulations, Essential component, Female, Fetal monitoring, Gaussian curves, generator, Health care providers, Heart Rate, Fetal, Heart rates, High-fidelity simulators, Humans, Immersive, intrauterine pressure, labor, Labor, Obstetric, Labour and delivery, medical education, Medical educational simulation, muscle tone, Natural variability, normal distribution, Obstetrics, Physiological data, Pregnancy, Prenatal Diagnosis, Pressure, Pressure generators, priority journal, Random processes, Risk free, Signal generator, Signal generators, Signal models, Signal parameters, Signal Processing, Computer-Assisted, simulation, Stationary stochastic process, statistical model, statistical parameters, statistics, Stochastic Processes, Time Factors, Training program, Uterine activities, Uterine activity, Uterine Contraction, Uterine Monitoring, uterus contraction |
| 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 44. h 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. © 2010 IPEM. |
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