Eight Weeks of Local Vibration Training Do Not Increase Tibialis Anterior Muscle Stiffness Evaluated by Supersonic Shear Imaging

Background

Local vibration (LV) training is efficient to improve muscle strength due to adaptations within the central nervous system. However, little is known about adaptations at the muscular level after this form of training. The aim of this study was to assess the effect of LV training on muscle elastic properties using supersonic shear imaging technique.

A Simple Method for Measuring the Changeable Mechanical Action of Unloader Knee Braces for Osteoarthritis

Purpose

Today's orthotics should be designed to apply the external orthosis moment to the knee joint solely during the stance phase instead of the entire gait cycle. The aim of this study was to validate the reliability of a simple device for measuring forces at the leg–orthosis interface and describe the behavior of an innovating dynamic unloader knee brace built to interrupt its mechanical action during large knee flexion (swing phase of gait).

Computerised Decision Support System for Remote Health Monitoring: A Systematic Review

Background

Remote health monitoring plays a major role in handling the critical situation of patients and avoiding death and also enhancing the quality of healthcare services. The effective real time monitoring with accurate decision has to be made in advance with the help of decision making system by continuously acquiring biosignals.

Comparison of Several Algorithms to Estimate Activity Counts with Smartphones as an Indication of Physical Activity Level

Background

Dedicated devices like GT3X+, Actical or ActivPal have been widely used to measure physical activity (PA) levels by using cut-points on activity counts. However, the calculation of activity counts relies on proprietary software. Since smartphones incorporate accelerometers they are suitable candidates to determine PA levels in a wider population.

Estimation of distal arm joint angles from EMG and shoulder orientation for transhumeral prostheses

In this paper, we quantify the extent to which shoulder orientation, upper-arm electromyography (EMG), and forearm EMG are predictors of distal arm joint angles during reaching in eight subjects without disability as well as three subjects with a unilateral transhumeral amputation and targeted reinnervation. Prior studies have shown that shoulder orientation and upper-arm EMG, taken separately, are predictors of both elbow flexion/extension and forearm pronation/supination. We show that, for eight subjects without disability, shoulder orientation and upper-arm EMG together are a significantly better predictor of both elbow flexion/extension during unilateral ($R^2=0.72$) and mirrored bilateral ($R^2=0.72$) reaches and of forearm pronation/supination during unilateral ($R^2=0.77$) and mirrored bilateral ($R^2=0.70$) reaches. We also show that adding forearm EMG further improves the prediction of forearm pronation/supination during unilateral ($R^2=0.82$) and mirrored bilateral ($R^2=0.75$) reaches. In principle, these results provide the basis for choosing inputs for control of transhumeral prostheses, both by subjects with targeted motor reinnervation (when forearm EMG is available) and by subjects without target motor reinnervation (when forearm EMG is not available). In particular, we confirm that shoulder orientation and upper-arm EMG together best predict elbow flexion/extension ($R^2=0.72$) for three subjects with unilateral transhumeral amputations and targeted motor reinnervation. However, shoulder orientation alone best predicts forearm pronation/supination ($R^2=0.88$) for these subjects, a contradictory result that merits further study.     

Analysis of User Control Attainment in SMR-based Brain Computer Interfaces

Context

Sensorimotor rhythms (SMR) have been the neuronal phenomena of choice in non-invasive EEG-based endogenous brain computer interfaces (BCIs) for more than two decades and SMR-based BCIs have achieved the highest degree of freedom control so far. Nevertheless, they are subject to long periods of training prior to attaining a satisfactory level of control requiring users to learn to modulate their rhythms. The goal of this work is to analyse this problem, discuss the causes of the slow rise in performance and provide recommendations on alternative solutions to quicken control attainment.

Modelling the mechanical response of elastin for arterial tissue

We compare two constitutive models proposed to model the elastinous constituents of an artery. Holzapfel and Weizsäcker [1998. Biomechanical behavior of the arterial wall and its numerical characterization. Comput. Biol. Med. 28, 377–392] attribute a neo-Hookean response, i.e. $\Psi =c(I_1-3))$, to the elastin whilst Zulliger et al. [2004a. A strain energy function for arteries accounting for wall composition and structure. J. Biomech. 37, 989–1000] propose $\Psi =c(I_1-3{)}^{3/2}$. We analyse these constitutive models for two specific cases: (i) uniaxial extension of an elastinous sheet; (ii) inflation of a cylindrical elastinous membrane. For case (i) we illustrate the functional relationships between: (a) the Cauchy stress (CS) and the Green–Lagrange (GL) strain; (b) the tangent modulus (gradient of the CS–GL strain curve) and linearised strain. The predicted mechanical responses are compared with recent uniaxial extension tests on elastin [Gundiah, N., Ratcliffe, M.B., Pruitt, L.A., 2007. Determination of strain energy function for arterial elastin: experiments using histology and mechanical tests. J. Biomech. 40, 586–594; Lillie, M.A., Gosline, J.M., 2007a. Limits to the durability of arterial elastic tissue. Biomaterials 28, 2021–2031; 2007b. Mechanical properties of elastin along the thoracic aorta in the pig. J. Biomech. 40, 2214–2221]. The neo-Hookean model accurately predicts the mechanical response of a single elastin fibre. However, it is unable to accurately capture the mechanical response of arterial elastin, e.g. the initial toe region of arterial elastin (if it exists) or the gradual increase in modulus of arterial elastin that occurs as it is stretched. The alternative constitutive model ($n=\frac{3}{2}$) yields a nonlinear mechanical response that departs from recent uniaxial test data mentioned above, for the same stretch range. For case (ii) we illustrate the pressure–circumferential stretch relationships and the gradients of the pressure–circumferential stretch curves: significant qualitative differences are observed. For the neo-Hookean model, the gradient decreases rapidly to zero, however, for $n=\frac{3}{2}$, the gradient decreases more gradually to a constant value. We conclude that whilst the neo-Hookean model has limitations, it appears to capture more accurately the mechanical response of elastin.     

Protein crystal’s shape and polymorphism prediction within the limits resulting from the exploration of the Miyazawa–Jernigan matrix

A computer study of the prediction of the protein crystal’s shape and polymorphism of crystal’s structures within the limits resulting from the exploration of the Miyazawa–Jernigan matrix is presented. In this study, a coarse-graining procedure was applied to prepare a two-dimensional growth unit, where instead of full atom representation of the protein a two-type (hydrophobic–hydrophilic, HP) aminoacidal representation was used. The interaction energies between hydrophobic ($E_{\text{HH}}$) aminoacids were chosen from the well-known HP-type models ($E_{\text{HH}}\in [-4\text{,}-3\text{,}-2.3\text{,}-1]$), whereas interaction energies between hydrophobic and hydrophilic aminoacids ($E_{\text{HP}}$) as well as interaction energies between hydrophilic aminoacids ($E_{\text{PP}}$) were chosen from the range: $<-1\text{,}1>$, but not all values from this range fulfiled limitations resulting from the exploration of the Miyazawa–Jernigan matrix. Exploring every positively vetted combinations of energy interactions a polymorphism of the unit cell was observed what led to the fact that different final crystal’s shapes were obtained.