Journal of Mechanics in Medicine and Biology

It is well known from fundamental fluid mechanics that separation regions occur at bends and bifurcations of blood vessels. In addition to this, a secondary flow is also created. This means that the flow is moving forward like a vortical plait. Vortices are created that move counterclockwise to each other perpendicular to the mainstream direction. Three-dimensional flow exists, which is totally different to the well-known parabolic flow in straight pipes under laminar flow conditions. Therefore, a short fundamental introduction to biofluid mechanics is presented in this paper. A coronary artery model with different bypasses is shown as an example. The coronary artery is a prominent cardiac vessel often affected by the atherosclerosis process, which can lead to its full blockage. Blood flow is restored by the construction of a bypass performed by implanting part of the saphenous vein. This bypass is subjected to varying flow conditions during the various phases of pulsatile blood flow. For precise location of the regions associated with flow abnormalities, flow visualization through the complete bypass, covering the arterial and bypass sections, is required. This forms the objective of the present work: to visualize flow changes in bypass models of the right coronary artery prior to its bifurcation under pulsatile flow conditions.

Virtual proprioception represents a novel means of developing cortical reorganization of alternative strategies for hemiparetic gait. Fundamentals of the device are motor control plasticity, aftereffect, and visual-based biofeedback. Two wireless three-dimensional (3D) microelectromechanical systems (MEMS) accelerometers are placed on the femur (upper leg) of both the affected and unaffected limbs above the lateral epicondyle next to the knee joint. The acceleration data from the two wireless 3D MEMS accelerometers are fed back to the user in real time by visual output from a portable laptop PC. Given the virtual proprioception feedback, the user can then adjust the original gait while walking to an improved alternative gait strategy. First, hemiparetic gait is comprehensively discussed. The inherent roles of proprioception with locomotion and issues with traumatic brain injury are considered. Then, the technology advance of accelerometers and gait analysis is detailed. Virtual proprioception is tested and evaluated, while demonstrating the capacity to improve disparities in hemiparetic gait during real time.

The dermal equivalent (DE), a dermis substitute consisting of human skin fibroblasts growing into a three-dimensional collagen matrix, is extensively used in many applications: wound-healing response, pharmacological studies, skin grafting, fibroblast proliferation and migration, extracellular matrix remodeling, and efficacy of cosmetic products. The widespread growth of numerical modeling in biomechanical research has placed a heightened emphasis on accurate material property data for soft biological tissues, in particular for equivalent dermis which has not been so thoroughly investigated. Under unconfined compression loading, the effects of the strain rate, time culture, and cytoskeleton-disrupting agents are experimentally investigated. In order to model the observed mechanical behavior of the DE under the above conditions, the internal state variable approach is adopted for finite deformation viscoelasticity and the optimized material parameters are identified with respect to the stated thermodynamic restriction (i.e. positive viscous dissipation).

Measurements of cross-sectional areas (CSAs) of soft tissues such as tendons and ligaments allow for the evaluation of the biomechanical properties of the tissue. Underlying in vitro techniques are data reduction approaches for determining the average thickness of the tissue and the assumption of the geometry of the cross-section, i.e. circular or elliptical. However, tissue distortions, sagging, and concavities could affect the reliability of these techniques, since these features may not be accounted for adequately. To address some of the concerns faced by these techniques, a non-contact (non-destructive) laser scan technique has been developed. In this technique, a laser scans along the axis of the tissue, a coordinate measuring machine simultaneously locates the corresponding point on the tissue based on the detection of reflected (attenuated) intensity, and, finally, computerized image analysis reconstructs the morphology of the tissue. This technique was applied to patellar tendons (PTs) from New Zealand rabbits. The scanning time for each PT was less than 2 minutes. Reconstructed three-dimensional surface plots revealed microconcavities consistent with images seen under optical microscopy. CSAs of these PTs were determined for repeatability and precision; results from a conventional approach which estimated the corresponding CSAs based on the average thickness and the assumption of ellipsoidal cross-sectional geometry were also determined for the purpose of comparison. Based on the standard cuboid model, the error between the laser technique and the conventional approach was within 0.4%; the reproducibility of the laser technique was within 2%.

Diabetes mellitus is a medical disorder characterized by varying or persistent hyperglycemia (elevated blood sugar levels), especially after eating. People with diabetes have problems converting food to energy. The most common form of diabetes is type 2 diabetes. Foot disease is a common complication of diabetes that can have tragic consequences. Abnormal plantar pressures are considered to play a major role in the pathologies of neuropathic ulcers in the diabetic foot. The purpose of this study was to classify the plantar pressure distribution in normal and type 2 diabetes subjects with and without neuropathy. Foot scans were obtained using the F-Scan (Tekscan, USA) in-shoe pressure measurement system. Various pedobarographic parameters such as the total plantar force, total contact area, peak pressures, and percentage medial impulse (PMI) were evaluated. These parameters were subjected to analysis of variance (ANOVA) test with a >95% confidence interval, giving excellent p-values in all of the categories. When these extracted parameters were presented to the artificial neural network (ANN) for classification, the neural network classifier was seen to be correct in more than 90% of the test cases.

Articular cartilage dissipates contact loads according to three dissipative mechanisms: frictional drag, intrinsic viscoelasticity, and surface friction. Estimation of dissipation due to these three mechanisms during gait is required to understand the dissipative properties of articular cartilage. Fourteen healthy subjects performed a gait analysis on treadmill. Tibiofemoral contact forces were estimated from inverse dynamic analysis and from a reductionist knee contact model. These contact forces and the results obtained from a preloading creep simulation were introduced into a biphasic poroviscoelastic articular cartilage model, and a one-dimensional confined compression was performed. Articular dissipation from each dissipative mechanism was estimated. Sensitivity analysis was performed to determine the effects of material parameters and length of the preloading simulation on the patterns of the dissipative mechanisms. Dissipative force patterns for all dissipative mechanisms were found to be similar to those of tibiofemoral contact forces. Frictional drag was found to be the dominant dissipative mechanism. The initial permeability and the viscoelastic spectrum parameters were found to have an important impact on the magnitude of the peaks of dissipative patterns. If appropriate material parameters are introduced, this model could be used to compare the difference between healthy and osteoarthritic human articular cartilage.

A two-dimensional (2D) nonlinear mathematical model to study the response of the pulsatile flow of blood through a couple of irregular stenoses influenced by externally imposed periodic body acceleration is developed. The model is 2D and axisymmetric with an outline of the stenosis obtained from the three-dimensional (3D) casting of a mildly stenosed artery. The combined influence of an asymmetric shape and surface irregularities of the constrictions is explored in a computational study of blood flow through arterial stenoses with 48% areal occlusion. The arterial wall is treated as an elastic (moving wall) cylindrical tube having a couple of stenoses in its lumen, while the streaming blood is considered to be Newtonian. Solutions of the time-dependent nonlinear Navier–Stokes equations in the cylindrical coordinate system are obtained using a finite difference method based on the nonuniform and nonstaggered grids. The finite difference approximation helps to estimate the effects of body acceleration on the doubly constricted flow phenomena through several graphical representations quantitatively in order to validate the applicability of the present, improved mathematical model.

In many medical applications, feature selection is obvious; but in medical domains, selecting features and creating a feature vector may require more effort. The wavelet transform (WT) technique is used to identify the characteristic points of an electrocardiogram (ECG) signal with fairly good accuracy, even in the presence of severe high-frequency and low-frequency noise. Principal component analysis (PCA) is a suitable technique for ECG data analysis, feature extraction, and image processing — an important technique that is not based upon a probability model. The aim of the paper is to derive better diagnostic parameters for reducing the size of ECG data while preserving morphology, which can be done by PCA. In this analysis, PCA is used for decorrelation of ECG signals, noise, and artifacts from various raw ECG data sets. The aim of this paper is twofold: first, to describe an elegant algorithm that uses WT alone to identify the characteristic points of an ECG signal; and second, to use a composite WT-based PCA method for redundant data reduction and better feature extraction. PCA scatter plots can be observed as a good basis for feature selection to account for cardiac abnormalities. The study is analyzed with higher-order statistics, in contrast to the conventional methods that use only geometric characteristics of feature waves and lower-order statistics. A new algorithm — viz. PCA variance estimator — is developed for this analysis, and the results are also obtained for different combinations of leads to find correlations for feature classification and useful diagnostic information. PCA scatter plots of various chest and augmented ECG leads are obtained to examine the varying orientations of the ECG data in different quadrants, indicating the cardiac events and abnormalities. The efficacy of the PCA algorithm is tested on different leads of 12-channel ECG data; file no. 01 of the Common Standards for Electrocardiography (CSE) database is used for this study. Better feature extraction is obtained for some specific combinations of leads, and significant improvement in signal quality is achieved by identifying the noise and artifact components. The quadrant analysis discussed in this paper highlights the filtering requirements for further ECG processing after performing PCA, as a primary step for decorrelation and dimensionality reduction. The values of the parameters obtained from the results of PCA are also compared with those of wavelet methods.