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Bioengineering
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Multiscale Modeling in Computational Biomechanics
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Multiscale Modeling in Computational Biomechanics

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomechanics and Sports Medicine".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 11642

Special Issue Editor

Prof. Dr. Tien Tuan Dao

E-Mail Website
Guest Editor
Univ. Lille, CNRS, Centrale Lille, UMR 9013-LaMcube-Laboratoire de Mécanique, Multiphysique, Multiéchelle, F-59000 Lille, France
Interests: biomechanics; machine learning; artificial intelligence; muscle mechanics

Special Issue Information

Dear Colleagues,

Computational biomechanics has been intensively investigated in the last several decades for the study of human body systems (musculoskeletal, cardiovascular, digestive, etc.) at multiple scales. Computational biomechanics is usually coupled with experimental biomechanics to enhance our understanding of the human body shape–function properties and their causal relationships. Thus, novel biomarkers and quantitative indicators have been extracted for clinical decision support and medical device optimization.

We are pleased to invite you to contribute to this challenging and exciting field. This Special Issue aims to bring together different scientific communities to present methodological approaches as well as practical applications related to the multiscale modeling of the human body.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Cell and tissue biomechanics;
  • Organ biomechanics;
  • Musculoskeletal biomechanics;
  • Human locomotion and multi-body dynamics;
  • Artificial intelligence, deep learning and biomechanics;
  • Mixed reality and biomechanics;
  • Clinical decision support;
  • Multiscale characterization and multi-physical modeling;
  • Multimodal medical imaging.

I look forward to receiving your contributions.

Prof. Dr. Tien Tuan Dao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multiscale modeling
  • computational biomechanics
  • in silico medicine
  • human body systems
  • shape–function properties
  • novel bio-markers
  • experimentation
  • artificial intelligence

Published Papers (6 papers)

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Research

17 pages, 5425 KiB  
Article
Stress Effect in the Knee Joint Based on the Fibular Osteotomy Level and Varus Deformity: A Finite Element Analysis Study
by Yeokyung Kang, Jungsung Kim, Jae Ang Sim, Myeong Moon, Jong-Chul Park, Sung Ha Cho and Byung Hoon Lee
Bioengineering 2023, 10(9), 1003; https://doi.org/10.3390/bioengineering10091003 - 24 Aug 2023
Viewed by 1084
Abstract
Proximal fibular osteotomy (PFO) was found to relieve pain and improve knee function in patients with medial compartment knee osteoarthritis (OA). Therapy redistributes the load applied from the inside to the outside and alleviates the load applied on the inside through fibula osteotomy. [...] Read more.
Proximal fibular osteotomy (PFO) was found to relieve pain and improve knee function in patients with medial compartment knee osteoarthritis (OA). Therapy redistributes the load applied from the inside to the outside and alleviates the load applied on the inside through fibula osteotomy. Therefore, the clinical effect of fibular osteotomy using the finite element (FE) method was evaluated to calculate the exact change in stress inside a knee joint with varus deformity. Using CT and MRI images of a patient’s lower extremities, 3D models of the bone, cartilage, meniscus, and ligaments were constructed. The varus angle, representing the inward angulation of the knee, was increased by applying a force ratio in the medial and lateral directions. The results showed that performing proximal fibular osteotomy led to a significant reduction in stress in the medial direction of the meniscus and cartilage. The stress reduction in the lateral direction was relatively minor. In conclusion, the study demonstrated that proximal fibular osteotomy effectively relieves stress and redistributes the load in the knee joints of patients with medial compartment knee osteoarthritis. The findings emphasize the importance of considering force distribution and the position of fibular osteotomy to achieve optimal clinical outcomes. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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14 pages, 4318 KiB  
Article
Finite Deformation of Scleral Tissue under Electrical Stimulation: An Arbitrary Lagrangian-Eulerian Finite Element Method
by Jafar Arash Mehr and Hamed Hatami-Marbini
Bioengineering 2023, 10(8), 920; https://doi.org/10.3390/bioengineering10080920 - 03 Aug 2023
Viewed by 1003
Abstract
The sclera is considered as the principal load-bearing tissue within the eye. The sclera is negatively charged; thus, it exhibits mechanical response to electrical stimulation. We recently demonstrated the electroactive behavior of sclera by performing experimental measurements that captured the deformation of the [...] Read more.
The sclera is considered as the principal load-bearing tissue within the eye. The sclera is negatively charged; thus, it exhibits mechanical response to electrical stimulation. We recently demonstrated the electroactive behavior of sclera by performing experimental measurements that captured the deformation of the tip of scleral strips subjected to electric voltage. We also numerically analyzed the electromechanical response of the tissue using a chemo-electro-mechanical model. In the pre-sent study, we extended our previous work by experimentally characterizing the deformation profile of scleral strips along their length under electrical stimulation. In addition, we improved our previous mathematical model such that it could numerically capture the large deformation of samples. For this purpose, we considered the transient variability of the fixed charge density and the coupling between mechanical and chemo-electrical phenomena. These improvements in-creased the accuracy of the computational model, resulting in a better numerical representation of experimentally measured bending angles. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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22 pages, 10751 KiB  
Article
Novel Baseline Facial Muscle Database Using Statistical Shape Modeling and In Silico Trials toward Decision Support for Facial Rehabilitation
by Vi-Do Tran, Tan-Nhu Nguyen, Abbass Ballit and Tien-Tuan Dao
Bioengineering 2023, 10(6), 737; https://doi.org/10.3390/bioengineering10060737 - 19 Jun 2023
Viewed by 1652
Abstract
Backgrounds and Objective: 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 [...] Read more.
Backgrounds and Objective: 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. However, there is a lack of facial muscle baseline data to evaluate the patient states and guide as well as optimize the rehabilitation strategy. In this present study, we aimed to develop a novel baseline facial muscle database (static and dynamic behaviors) using the coupling between statistical shape modeling and in-silico trial approaches. Methods: 10,000 virtual subjects (5000 males and 5000 females) were generated from a statistical shape modeling (SSM) head model. Skull and muscle networks were defined so that they statistically fit with the head shapes. Two standard mimics: smiling and kissing were generated. The muscle strains of the lengths in neutral and mimic positions were computed and recorded thanks to the muscle insertion and attachment points on the animated head and skull meshes. For validation, five head and skull meshes were reconstructed from the five computed tomography (CT) image sets. Skull and muscle networks were then predicted from the reconstructed head meshes. The predicted skull meshes were compared with the reconstructed skull meshes based on the mesh-to-mesh distance metrics. The predicted muscle lengths were also compared with those manually defined on the reconstructed head and skull meshes. Moreover, the computed muscle lengths and strains were compared with those in our previous studies and the literature. Results: The skull prediction’s median deviations from the CT-based models were 2.2236 mm, 2.1371 mm, and 2.1277 mm for the skull shape, skull mesh, and muscle attachment point regions, respectively. The median deviation of the muscle lengths was 4.8940 mm. The computed muscle strains were compatible with the reported values in our previous Kinect-based method and the literature. Conclusions: The development of our novel facial muscle database opens new avenues to accurately evaluate the facial muscle states of facial palsy patients. Based on the evaluated results, specific types of facial mimic rehabilitation exercises can also be selected optimally to train the target muscles. In perspective, the database of the computed muscle lengths and strains will be integrated into our available clinical decision support system for automatically detecting malfunctioning muscles and proposing patient-specific rehabilitation serious games. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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21 pages, 6092 KiB  
Article
Optimization Design and Performance Analysis of a Bionic Knee Joint Based on the Geared Five-Bar Mechanism
by Zhuo Wang, Wenjie Ge, Yonghong Zhang, Bo Liu, Bin Liu, Shikai Jin and Yuzhu Li
Bioengineering 2023, 10(5), 582; https://doi.org/10.3390/bioengineering10050582 - 11 May 2023
Viewed by 1352
Abstract
Animal joint motion is a combination of rotation and translational motion, which brings high stability, high energy utilization, and other advantages. At present, the hinge joint is widely used in the legged robot. The simple motion characteristic of the hinge joint rotating around [...] Read more.
Animal joint motion is a combination of rotation and translational motion, which brings high stability, high energy utilization, and other advantages. At present, the hinge joint is widely used in the legged robot. The simple motion characteristic of the hinge joint rotating around the fixed axis limits the improvement of the robot’s motion performance. In this paper, by imitating the knee joint of a kangaroo, we propose a new bionic geared five-bar knee joint mechanism to improve the energy utilization rate of the legged robot and reduce the required driving power. Firstly, based on image processing technology, the trajectory curve of the instantaneous center of rotation (ICR) of the kangaroo knee joint was quickly obtained. Then, the bionic knee joint was designed by the single-degree-of-freedom geared five-bar mechanism and the parameters for each part of the mechanism were optimized. Finally, based on the inverted pendulum model and the Newton–Euler recursive method, the dynamics model of the single leg of the robot in the landing stage was established, and the influence of the designed bionic knee joint and hinge joint on the robot’s motion performance was compared and analyzed. The proposed bionic geared five-bar knee joint mechanism can more closely track the given trajectory of the total center of mass motion, has abundant motion characteristics, and can effectively reduce the power demand and energy consumption of the robot knee actuators under the high-speed running and jumping gait. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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21 pages, 6151 KiB  
Article
Fast 3D Face Reconstruction from a Single Image Using Different Deep Learning Approaches for Facial Palsy Patients
by Duc-Phong Nguyen, Tan-Nhu Nguyen, Stéphanie Dakpé, Marie-Christine Ho Ba Tho and Tien-Tuan Dao
Bioengineering 2022, 9(11), 619; https://doi.org/10.3390/bioengineering9110619 - 27 Oct 2022
Viewed by 3853
Abstract
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 [...] Read more.
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. However, the 3D face shape reconstruction of facial palsy patients is still a challenge, and this has not been investigated. The contribution of the present study is to apply these state-of-the-art methods to reconstruct the 3D face shape models of facial palsy patients in natural and mimic postures from one single image. Three different methods (3D Basel Morphable model and two 3D Deep Pre-trained models) were applied to the dataset of two healthy subjects and two facial palsy patients. The reconstructed outcomes were compared to the 3D shapes reconstructed using Kinect-driven and MRI-based information. As a result, the best mean error of the reconstructed face according to the Kinect-driven reconstructed shape is 1.5±1.1 mm. The best error range is 1.9±1.4 mm when compared to the MRI-based shapes. Before using the procedure to reconstruct the 3D faces of patients with facial palsy or other facial disorders, several ideas for increasing the accuracy of the reconstruction can be discussed based on the results. This present study opens new avenues for the fast reconstruction of the 3D face shapes of facial palsy patients from a single image. As perspectives, the best DL method will be implemented into our computer-aided decision support system for facial disorders. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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10 pages, 1752 KiB  
Article
Development and Validation of a Subject-Specific Coupled Model for Foot and Sports Shoe Complex: A Pilot Computational Study
by Yang Song, Xuanzhen Cen, Yan Zhang, István Bíró, Yulei Ji and Yaodong Gu
Bioengineering 2022, 9(10), 553; https://doi.org/10.3390/bioengineering9100553 - 14 Oct 2022
Cited by 11 | Viewed by 1870
Abstract
Nowadays, footwear serves an essential role in improving athletic performance and decreasing the risk of unexpected injuries in sports games. Finite element (FE) modeling is a powerful tool to reveal the biomechanical interactions between foot and footwear, and establishing a coupled foot-shoe model [...] Read more.
Nowadays, footwear serves an essential role in improving athletic performance and decreasing the risk of unexpected injuries in sports games. Finite element (FE) modeling is a powerful tool to reveal the biomechanical interactions between foot and footwear, and establishing a coupled foot-shoe model is the prerequisite. The purpose of this pilot study was to develop and validate a 3D FE coupled model of the foot and sports shoe complex during balanced standing. All major foot and shoe structures were constructed based on the participant’s medical CT images, and 3D gait analysis was conducted to define the loading and boundary conditions. Sensitivity analysis was applied to determine the optimum material property for shoe sole. Both the plantar and shoe sole areas were further divided into four regions for model validation, and the Bland–Altman method was used for consistency analysis between methods. The simulated peak plantar and sole pressure distribution showed good consistency with experimental pressure data, and the prediction errors were all less than 10% during balanced standing with only two exceptions (medial and lateral forefoot regions). Meanwhile, the Bland–Altman analysis demonstrated a good agreement between the two approaches. The sensitivity analysis suggested that shoe sole with Young’s modulus of 2.739 MPa presented the greatest consistency with the measured data in our scenario. The established model could be used for investing the complex biomechanical interactions between the foot and sports shoe and optimizing footwear design, after it has been fully validated in the subsequent works under different conditions. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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