Special Issue "Computer Methods in Bio-mechanics and Biomedical Engineering"

Submission Deadline: 30 October 2019 (closed)
Guest Editors
Professor Lulu Wang, Shenzhen Technology University, China
Professor Xiaoning Jiang, North Carolina State University
Professor Lindong Yu, Hefei University of Technology
Professor Linxia Gu, University of Nebraska-Lincoln


This special issue focuses on the implementation of various engineering principles in the conception, design, development, analysis and operation of biomedical and biotechnological systems and applications. The special issue aims to promote solutions of excellence for biomedical data and establishes links among engineers, researchers, and clinicians. 

This special issue offers a comprehensive forum for discussion of the current state-of-the-art in the scientific fields related to bio-mechanics and biomedical technologies, including, but not limited to:
1. Computational Modeling in Biomedical Applications
2. Computer Aided Diagnosis, Surgery, Therapy and Treatment
3. Data Processing and Analysis
4. Injury and Damage Bio-mechanics
5. Vibration and Acoustics in Biomedical Applications
6. Biomedical Imaging, Therapy and Tissue Characterization
7. Biomaterials and Tissue: Modelling, Synthesis, Fabrication and Characterization
8. Biomedical Devices
9. Dynamics and Control of Biomechanical Systems
10. Clinical Applications of Bioengineering
11. Musculoskeletal and Sports Bio-mechanics
12. Sensors and Actuators
13. Robotics, Rehabilitation
14. Data Processing and Analysis
15. Virtual Reality
16. Visual Data Mining and Knowledge Discovery
17. Software Development for Bio-mechanics and Biomedical Engineering

Biomedical imaging; Biomedical Devices; CAD; Biosensors;

Published Papers
  • Prediction of Intrinsically Disordered Proteins Based on Deep Neural Network-ResNet18
  • Abstract Accurately, reliably and rapidly identifying intrinsically disordered (IDPs) proteins is essential as they often play important roles in various human diseases; moreover, they are related to numerous important biological activities. However, current computational methods have yet to develop a network that is sufficiently deep to make predictions about IDPs and demonstrate an improvement in performance. During this study, we constructed a deep neural network that consisted of five identical variant models, ResNet18, combined with an MLP network, for classification. Resnet18 was applied for the first time as a deep model for predicting IDPs, which allowed the extraction of information from… More
  •   Views:406       Downloads:323        Download PDF

  • Fast and Accurate Thoracic SPECT Image Reconstruction
  • Abstract In Single-Photon Emission Computed Tomography (SPECT), the reconstructed image has insufficient contrast, poor resolution and inaccurate volume of the tumor size due to physical degradation factors. Generally, nonstationary filtering of the projection or the slice is one of the strategies for correcting the resolution and therefore improving the quality of the reconstructed SPECT images. This paper presents a new 3D algorithm that enhances the quality of reconstructed thoracic SPECT images and reduces the noise level with the best degree of accuracy. The suggested algorithm is composed of three steps. The first one consists of denoising the acquired projections using the… More
  •   Views:372       Downloads:305        Download PDF

  • Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study
  • Abstract Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total… More
  •   Views:497       Downloads:383        Download PDF

  • Predicting Genotype Information Related to COVID-19 for Molecular Mechanism Based on Computational Methods
  • Abstract Novel coronavirus disease 2019 (COVID-19) is an ongoing health emergency. Several studies are related to COVID-19. However, its molecular mechanism remains unclear. The rapid publication of COVID-19 provides a new way to elucidate its mechanism through computational methods. This paper proposes a prediction method for mining genotype information related to COVID-19 from the perspective of molecular mechanisms based on machine learning. The method obtains seed genes based on prior knowledge. Candidate genes are mined from biomedical literature. The candidate genes are scored by machine learning based on the similarities measured between the seed and candidate genes. Furthermore, the results of… More
  •   Views:973       Downloads:787        Download PDF

  • Bioprosthetic Valve Size Selection to Optimize Aortic Valve Replacement Surgical Outcome: A Fluid-Structure Interaction Modeling Study
  • Abstract Aortic valve replacement (AVR) remains a major treatment option for patients with severe aortic valve disease. Clinical outcome of AVR is strongly dependent on implanted prosthetic valve size. Fluid-structure interaction (FSI) aortic root models were constructed to investigate the effect of valve size on hemodynamics of the implanted bioprosthetic valve and optimize the outcome of AVR surgery. FSI models with 4 sizes of bioprosthetic valves (19 (No. 19), 21 (No. 21), 23 (No. 23) and 25 mm (No. 25)) were constructed. Left ventricle outflow track flow data from one patient was collected and used as model flow conditions. Anisotropic Mooney–Rivlin… More
  •   Views:1459       Downloads:1022        Download PDF

  • Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data
  • Abstract This study aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs. In the study, 66 male and 54 female participants were scanned by MRI and a stereovision body imaging (SBI) to measure participants’ abdominal VAT and SAT volumes and the BSDs. A fuzzy c-means algorithm was used to form the inherent grouping clusters of… More
  •   Views:1207       Downloads:969        Download PDF

  • An Efficient Algorithm Based on Spectrum Migration for High Frame Rate Ultrasound Imaging
  • Abstract The high frame rate (HFR) imaging technique requires only one emission event for imaging. Therefore, it can achieve ultrafast imaging with frame rates up to the kHz regime, which satisfies the frame rate requirements for imaging moving tissues in scientific research and clinics. Lu’s Fourier migration method is based on a non-diffraction beam to obtain HFR images and can improve computational speed and efficiency. However, in order to obtain high-quality images, Fourier migration needs to make full use of the spectrum of echo signals for imaging, which requires a large number of Fast Fourier Transform (FFT) points and increases the… More
  •   Views:1359       Downloads:1213        Download PDF

  • ALCencryption: A Secure and Efficient Algorithm for Medical Image Encryption
  • Abstract With the rapid development of medical informatization and the popularization of digital imaging equipment, DICOM images contain the personal privacy of patients, and there are security risks in the process of storage and transmission, so it needs to be encrypted. In order to solve the security problem of medical images on mobile devices, a safe and efficient medical image encryption algorithm called ALCencryption is designed. The algorithm first analyzes the medical image and distinguishes the color image from the gray image. For gray images, the improved Arnold map is used to scramble them according to the optimal number of iterations,… More
  •   Views:5834       Downloads:2043       Cited by:2        Download PDF

  • Numerical Simulation of Bone Remodeling Coupling the Damage Repair Process in Human Proximal Femur
  • Abstract Microdamage is produced in bone tissue under the long-term effects of physiological loading, as well as age, disease and other factors. Bone remodeling can repair microdamage, otherwise this damage will undermine bone quality and even lead to fractures. In this paper, the damage variable was introduced into the remodeling algorithm. The new remodeling algorithm contains a quadratic term that can simulate reduction in bone density after large numbers of loading cycles. The model was applied in conjunction with the 3D finite element method (FEM) to the remodeling of the proximal femur. The results showed that the initial accumulation of fatigue… More
  •   Views:1592       Downloads:1400        Download PDF

  • Soft Tissue Deformation Model Based on Marquardt Algorithm and Enrichment Function
  • Abstract In order to solve the problem of high computing cost and low simulation accuracy caused by discontinuity of incision in traditional meshless model, this paper proposes a soft tissue deformation model based on the Marquardt algorithm and enrichment function. The model is based on the element-free Galerkin method, in which Kelvin viscoelastic model and adjustment function are integrated. Marquardt algorithm is applied to fit the relation between force and displacement caused by surface deformation, and the enrichment function is applied to deal with the discontinuity in the meshless method. To verify the validity of the model, the Sensable Phantom Omni… More
  •   Views:2263       Downloads:1818        Download PDF

  • A Geometrical Approach to Compute Upper Limb Joint Stiffness
  • Abstract Exoskeletons are designed to control the forces exerted during the physical coupling between the human and the machine. Since the human is an active system, the control of an exoskeleton requires coordinated action between the machine and the load so to obtain a reciprocal adaptation. Humans in the control loop can be modeled as active mechanical loads whose stiffness is continuously changing. The direct measurement of human stiffness is difficult to obtain in real-time, thus posing a significant limitation to the design of wearable robotics controllers. Electromyographic (EMG) recordings can provide an indirect estimation of human muscle force and stiffness,… More
  •   Views:2744       Downloads:2057        Download PDF

  • Automatic Sleep Staging Algorithm Based on Random Forest and Hidden Markov Model
  • Abstract In the field of medical informatics, sleep staging is a challenging and timeconsuming task undertaken by sleep experts. According to the new standard of the American Academy of Sleep Medicine (AASM), the stages of sleep are divided into wakefulness (W), rapid eye movement (REM) and non-rapid eye movement (NREM) which includes three sleep stages (N1, N2 and N3) that describe the depth of sleep. This study aims to establish an automatic sleep staging algorithm based on the improved weighted random forest (WRF) and Hidden Markov Model (HMM) using only the features extracted from double-channel EEG signals. The WRF classification model… More
  •   Views:2927       Downloads:2171       Cited by:1        Download PDF

  • A Joint Delay-and-Sum and Fourier Beamforming Method for High Frame Rate Ultrasound Imaging
  • Abstract Frame rate is an important metric for ultrasound imaging systems, and high frame rates (HFR) benefit moving-target imaging. One common way to obtain HFR imaging is to transmit a plane wave. Delay-and-sum (DAS) beamformer is a conventional beamforming algorithm, which is simple and has been widely implemented in clinical application. Fourier beamforming is an alternative method for HFR imaging and has high levels of imaging efficiency, imaging speed, and good temporal dynamic characteristics. Nevertheless, the resolution and contrast performance of HFR imaging based on DAS or Fourier beamforming are insufficient due to the single plane wave transmission. To address this… More
  •   Views:2810       Downloads:1962        Download PDF

  • Grading Method for Hypoxic-Ischemic Encephalopathy Based on Neonatal EEG
  • Abstract The grading of hypoxic-ischemic encephalopathy (HIE) contributes to the clinical decision making for neonates with HIE. In this paper, an automated grading method based on electroencephalogram (EEG) data is proposed to describe the severity of HIE infants, namely mild asphyxia, moderate asphyxia and severe asphyxia. The automated grading method is based on a multi-class support vector machine (SVM) classifier, and the input features of SVM classifier include long-term features which are extracted by decomposing the EEG data into different 64 s epoch data and short-term features which are extracted by segmenting the 64 s epoch data into 8 s epoch… More
  •   Views:3480       Downloads:1987       Cited by:2        Download PDF