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Fast soft-tissue deformations coupled with mixed reality toward the next-generation childbirth training simulator

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Abstract

High-quality gynecologist and midwife training is particularly relevant to limit medical complications and reduce maternal and fetal morbimortalities. Physical and virtual training simulators have been developed. However, physical simulators offer a simplified model and limited visualization of the childbirth process, while virtual simulators still lack a realistic interactive system and are generally limited to imposed predefined gestures. Objective performance assessment based on the simulation numerical outcomes is still not at hand. In the present work, we developed a virtual childbirth simulator based on the Mixed-Reality (MR) technology coupled with HyperMSM (Hyperelastic Mass-Spring Model) formulation for real-time soft-tissue deformations, providing intuitive user interaction with the virtual physical model and a quantitative assessment to enhance the trainee’s gestures. Microsoft HoloLens 2 was used and the MR simulator was developed including a complete holographic obstetric model. A maternal pelvis system model of a pregnant woman (including the pelvis bone, the pelvic floor muscles, the birth canal, the uterus, and the fetus) was generated, and HyperMSM formulation was applied to simulate the soft tissue deformations. To induce realistic reactions to free gestures, the virtual replicas of the user’s detected hands were introduced into the physical simulation and were associated with a contact model between the hands and the HyperMSM models. The gesture of pulling any part of the virtual models with two hands was also implemented. Two labor scenarios were implemented within the MR childbirth simulator: physiological labor and forceps-assisted labor. A scoring system for the performance assessment was included based on real-time biofeedback. As results, our developed MR simulation application was developed in real-time with a refresh rate of 30–50 FPS on the HoloLens device. HyperMSM model was validated using FE outcomes: high correlation coefficients of [0.97–0.99] and weighted root mean square relative errors of 9.8% and 8.3% were obtained for the soft tissue displacement and energy density respectively. Experimental tests showed that the implemented free-user interaction system allows to apply the correct maneuvers (in particular the “Viennese” maneuvers) during the labor process, and is capable to induce a truthful reaction of the model. Obtained results confirm also the possibility of using our simulation’s outcomes to objectively evaluate the trainee’s performance with a reduction of 39% for the perineal strain energy density and 5.6 mm for the vertical vaginal diameter when the “Viennese” technique is applied. This present study provides, for the first time, an interactive childbirth simulator with an MR immersive experience with direct free-hand interaction, real-time soft-tissue deformation feedback, and an objective performance assessment based on numerical outcomes. This offers a new perspective for enhancing next-generation training-based obstetric teaching. The used models of the maternal pelvic system and the fetus will be enhanced, and more delivery scenarios (e.g. instrumental delivery, breech delivery, shoulder dystocia) will be designed and integrated. The third stage of labor will be also investigated to include the delivery of the placenta, and the clamping and cutting of the umbilical cord.

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Acknowledgements

The authors would like to thank the Métropole Européenne de Lille (MEL) and ISITE ULNE (R-TALENT-20-009-DAO) for funding.

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Authors and Affiliations

  1. Univ. Lille, CNRS, Centrale Lille, UMR 9013-LaMcube-Laboratoire de Mécanique, Multiphysique, Multiéchelle, Lille, F-59000, France

    Abbass Ballit, Chrystèle Rubod & Tien-Tuan Dao

  2. Université Lille Nord de France, Faculté de Médecine, F-59000, Lille, France

    Mathieu Hivert & Chrystèle Rubod

  3. CHU Lille, Service de Chirurgie Gynécologique, F-59000, Lille, France

    Mathieu Hivert & Chrystèle Rubod

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  1. Abbass Ballit
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Ballit, A., Hivert, M., Rubod, C. et al. Fast soft-tissue deformations coupled with mixed reality toward the next-generation childbirth training simulator. Med Biol Eng Comput 61, 2207–2226 (2023). https://doi.org/10.1007/s11517-023-02864-5

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