Identification of constitutive law for 3d-printed bioresorbable thermosensitive polymer to design medical devices for soft tissue reconstruction.

Breast cancer concerns 1 in 8 women in the world and is followed in 40% of cases by a mastectomy. Only 14% of women receive reconstructive surgery because of unfavorable clinical issues. The need of innovative tissue engineering devices leads Lattice Medical company to bring a new 3D-printed device, allowing the regeneration of soft tissue in order to replace the withdrawn breast.

Fetus descent simulation with the active uterine contraction during the vaginal delivery: MRI-based evaluation and uncertainty quantification.

Finite element models ranging from single to multiscale models have been widely used to gain valuable insights into the physiological delivery process and associated complication scenarios. However, the fetus descent simulation with the active uterine contraction is still challenging for validation and uncertainty quantification issues. The present study performed a fetus descent simulation using the active uterine contraction.

Foetus-specific neuromusculoskeletal modelling with MRI-driven vaginal delivery kinematics during the second stage of labor.

Childbirth simulations lack realism due to an oversimplification of the foetal model, particularly as most models do not allow joint motion. Foetus-specific neuromusculoskeletal (NMS) model with a detailed articulated skeleton is still not available in the literature. The present work aims at proposing the first-ever foetus-specific NMS model and then simulating the foetal descent during a vaginal delivery by using medical resonance imaging (MRI) childbirth data.

Novel hybrid rigid-deformable fetal modeling for simulating the vaginal delivery within the second stage of labor.

Background And Objective: The fetal representation as a 3D articulated body plays an essential role to describe a realistic vaginal delivery simulation. However, the current computational solutions have been oversimplified. The objective of the present work was to develop and evaluate a novel hybrid rigid-deformable modeling approach for the fetal body and then simulate its interaction with surrounding fetal soft tissues and with other maternal pelvis soft tissues during the second stage of labor.

On the uncertainty quantification of the active uterine contraction during the second stage of labor simulation.

Uterine contractions in the myometrium occur at multiple scales, spanning both organ and cellular levels. This complex biological process plays an essential role in the fetus delivery during the second stage of labor. Several finite element models of active uterine contractions have already been developed to simulate the descent of the fetus through the birth canal.

Multiphysics and multiscale modeling of uterine contractions: integrating electrical dynamics and soft tissue deformation with fiber orientation.

The development of a comprehensive uterine model that seamlessly integrates the intricate interactions between the electrical and mechanical aspects of uterine activity could potentially facilitate the prediction and management of labor complications. Such a model has the potential to enhance our understanding of the initiation and synchronization mechanisms involved in uterine contractions, providing a more profound comprehension of the factors associated with labor complications, including preterm labor. Consequently, it has the capacity to assist in more effective preparation and intervention strategies for managing such complications.

On the estimation of hip joint centre location with incomplete bone ossification for foetus-specific neuromusculoskeletal modeling.

Childbirth is a complex physiological process in which a foetal neuromusculoskeletal model is of great importance to develop realistic delivery simulations and associated complication analyses. However, the estimation of hip joint centre (HJC) in foetuses remains a challenging issue. Thus, this paper aims to propose and evaluate a new approach to locate the HJC in foetuses.

Novel Baseline Facial Muscle Database Using Statistical Shape Modeling and In Silico Trials toward Decision Support for Facial Rehabilitation.

: Facial palsy is a complex pathophysiological condition affecting the personal and professional lives of the involved patients. Sudden muscle weakness or paralysis needs to be rehabilitated to recover a symmetric and expressive face. Computer-aided decision support systems for facial rehabilitation have been developed.

Fast 3D Face Reconstruction from a Single Image Using Different Deep Learning Approaches for Facial Palsy Patients.

The 3D reconstruction of an accurate face model is essential for delivering reliable feedback for clinical decision support. Medical imaging and specific depth sensors are accurate but not suitable for an easy-to-use and portable tool. The recent development of deep learning (DL) models opens new challenges for 3D shape reconstruction from a single image.

Reinforcement learning coupled with finite element modeling for facial motion learning.

Background And Objective: Facial palsy patients or patients with facial transplantation have abnormal facial motion due to altered facial muscle functions and nerve damage. Computer-aided system and physics-based models have been developed to provide objective and quantitative information. However, the predictive capacity of these solutions is still limited to explore the facial motion patterns with emerging properties.

Recurrent neural network to predict hyperelastic constitutive behaviors of the skeletal muscle.

Hyperelastic constitutive laws have been commonly used to model the passive behavior of the human skeletal muscle. Despite many efforts, the use of accurate finite element formulations of hyperelastic constitutive laws is still time-consuming for a real-time medical simulation system. The objective of the present study was to develop a deep learning model to predict the hyperelastic constitutive behaviors of the skeletal muscle toward a fast estimation of the muscle tissue stress.

HyperMSM: A new MSM variant for efficient simulation of dynamic soft-tissue deformations.

Background And Objective: Fast, accurate, and stable simulation of soft tissue deformation is a challenging task. Mass-Spring Model (MSM) is one of the popular methods used for this purpose for its simple implementation and potential to provide fast dynamic simulations. However, accurately simulating a non-linear material within the mass-spring framework is still challenging.

Enhanced head-skull shape learning using statistical modeling and topological features.

Skull prediction from the head is a challenging issue toward a cost-effective therapeutic solution for facial disorders. This issue was initially studied in our previous work using full head-to-skull relationship learning. However, the head-skull thickness topology is locally shaped, especially in the face region.

Enhanced facial expression recognition using 3D point sets and geometric deep learning.

Facial expression recognition plays an essential role in human conversation and human-computer interaction. Previous research studies have recognized facial expressions mainly based on 2D image processing requiring sensitive feature engineering and conventional machine learning approaches. The purpose of the present study was to recognize facial expressions by applying a new class of deep learning called geometric deep learning directly on 3D point cloud data.

An Early Stage Researcher's Primer on Systems Medicine Terminology.

Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields.

Kinect-driven Patient-specific Head, Skull, and Muscle Network Modelling for Facial Palsy Patients.

Background And Objective: Facial palsy negatively affects both professional and personal life qualities of involved patients. Classical facial rehabilitation strategies can recover facial mimics into their normal and symmetrical movements and appearances. However, there is a lack of objective, quantitative, and in-vivo facial texture and muscle activation bio-feedbacks for personalizing rehabilitation programs and diagnosing recovering progresses.

A statistical shape modeling approach for predicting subject-specific human skull from head surface.

Human skull is an important body structure for jaw movement and facial mimic simulations. Surface head can be reconstructed using 3D scanners in a straightforward way. However, internal skull is challenging to be generated when only external information is available.

A Systematic Review of Real-Time Medical Simulations with Soft-Tissue Deformation: Computational Approaches, Interaction Devices, System Architectures, and Clinical Validations.

Simulating deformations of soft tissues is a complex engineering task, and it is even more difficult when facing the constraint between computation speed and system accuracy. However, literature lacks of a holistic review of all necessary aspects (computational approaches, interaction devices, system architectures, and clinical validations) for developing an effective system of soft-tissue simulations. This paper summarizes and analyses recent achievements of resolving these issues to estimate general trends and weakness for future developments.

Real-time computer vision system for tracking simultaneously subject-specific rigid head and non-rigid facial mimic movements using a contactless sensor and system of systems approach.

Background And Objective: Head and facial mimic animations play important roles in various fields such as human-machine interactions, internet communications, multimedia applications, and facial mimic analysis. Numerous studies have been trying to simulate these animations. However, they hardly achieved all requirements of full rigid head and non-rigid facial mimic animations in a subject-specific manner with real-time framerates.

A Systematic Review of Continuum Modeling of Skeletal Muscles: Current Trends, Limitations, and Recommendations.

Finite elasticity theory has been commonly used to model skeletal muscle. A very large range of heterogeneous constitutive laws has been proposed. In this review, the most widely used continuum models of skeletal muscles were synthetized and discussed.

From deep learning to transfer learning for the prediction of skeletal muscle forces.

Skeletal muscle forces may be estimated using rigid musculoskeletal models and neural networks. Neural network (NN) approach has the advantages of real-time estimation ability and promising prediction accuracy. However, most of the developed NN models are based on conventional feedforward NNs, which do not take dynamic temporal relationships of the muscle force profiles into consideration.

Rehabilitation-Oriented Serious Game Development and Evaluation Guidelines for Musculoskeletal Disorders.

Background: The progress in information and communication technology (ICT) led to the development of a new rehabilitation technique called "serious game for functional rehabilitation." Previous works have shown that serious games can be used for general health and specific disease management. However, there is still lack of consensus on development and evaluation guidelines.