Effects of eight different ligament property datasets on biomechanics of a lumbar L4-L5 finite element model

Ligaments assist trunk muscles in balancing external moments and providing spinal stability. In absence of the personalized material properties for ligaments, finite element (FE) models use dispersed data from the literature. This study aims to investigate the relative effects of eight different ligament property datasets on FE model responses. Eight L4-L5 models distinct only in ligament properties were constructed and loaded under moment (15 N m) alone or combined with a compressive follower load (FL). Range of motions (RoM) of the disc-alone model matched well in vitro data. Ligament properties significantly affected only sagittal RoMs (∼3.0–7.1° in flexion and ∼3.8–5.8° in extension at 10 N m). Sequential removal of ligaments shifted sagittal RoMs in and out of the corresponding in vitro ranges. When moment was combined with FL, center of rotation matched in vivo data for all models (3.8 ± 0.9 mm and 4.3 ± 1.8 mm posterior to the disc center in flexion and extension, respectively). Under 15 N m sagittal moments, ligament strains were often smaller or within the in vitro range in flexion whereas some posterior ligament forces approached their failure forces in some models. Ligament forces varied substantially within the models and affected the moment-sharing and internal forces on the disc and facet joints. Intradiscal pressure (IDP) had the greatest variation between models in extension. None of the datasets yielded results in agreement with all reported measurements. Results emphasized the important role of ligaments especially under larger moments and the need for their accurate representation in search for valid spinal models.     

Development of a surrogate model based on patient weight,bone mass and geometry to predict femoral neck strains and fracture loads

Osteoporosis and related bone fractures are an increasing global burden in our ageing society. Areal bone mineral density assessed through dual energy X-ray absorptiometry (DEXA), the clinically accepted and most used method, is not sufficient to assess fracture risk individually. Finite element (FE) modelling has shown improvements in prediction of fracture risk, better than aBMD from DEXA, but is not practical for widespread clinical use. The aim of this study was to develop an adaptive neural network (ANN)-based surrogate model to predict femoral neck strains and fracture loads obtained from a previously developed population-based FE model. The surrogate model performance was assessed in simulating two loading conditions: the stance phase of gait and a fall.The surrogate model successfully predicted strains estimated by FE (r² = 0.90–0.98 for level gait load case, r² = 0.92–0.96 for the fall load case). Moreover, an ANN model based on three measurements obtainable in clinics (femoral neck length (level gait) or maximum femoral neck diameter (fall), femoral neck bone mass, body weight) was able to give reasonable predictions (r² = 0.84–0.94) for all of the strain metrics and the estimated femoral neck fracture load. Overall, the surrogate model has potential for clinical applications as they are based on simple measures of geometry and bone mass which can be derived from DEXA images, accurately predicting FE model outcomes, with advantages over FE models as they are quicker and easier to perform.     

Forest biomass and volume estimation using airborne LiDAR in a cool-temperate forest of northern Hokkaido,Japan

Trees are recognized as a carbon reservoir, and precise and convenient methods for forest biomass estimation are required for adequate carbon management. Airborne light detection and ranging (LiDAR) is considered to be one of the solutions for large-scale forest biomass evaluation. To clarify the relationship between mean canopy height determined by airborne LiDAR and forest timber volume and biomass of cool-temperate forests in northern Hokkaido, Japan, we conducted LiDAR observations covering the total area of the Teshio Experimental Forest (225 km²) of Hokkaido University and compared the results with ground surveys and previous studies. Timber volume and aboveground tree carbon content of the studied forest stands ranged from 101.43 to 480.40 m³ ha^–1 and from 30.78 to 180.54 MgC ha^–1, respectively. The LiDAR mean canopy height explained the variation among stands well (volume: r² = 0.80, RMSE = 55.04 m³ ha^–1; aboveground tree carbon content: r² = 0.78, RMSE = 19.10 MgC ha^–1) when one simple linear regression equation was used for all types (hardwood, coniferous, and mixed) of forest stands. The determination of a regression equation for each forest type did not improve the prediction power for hardwood (volume: r² = 0.84, RMSE = 62.66 m³ ha^–1; aboveground tree carbon content: r² = 0.76, RMSE = 27.05 MgC ha^–1) or coniferous forests (volume: r² = 0.75, RMSE = 51.07 m³ ha^–1; aboveground tree carbon content: r² = 0.58, RMSE = 19.00 MgC ha^–1). Thus, the combined regression equation that includes three forest types appears to be adequate for practical application to large-scale forest biomass estimation.     

Analysis of pelvic strain in different gait configurations in a validated cohort of computed tomography based finite element models

The pelvis functions to transmit upper body loads to the lower limbs and is critical in human locomotion. Semi-automated, landmark-based finite element (FE) morphing and mapping techniques eliminate the need for segmentation and have shown to accelerate the generation of multiple specimen-specific pelvic FE models to enable the study of pelvic mechanical behaviour. The purpose of this research was to produce an experimentally validated cohort of specimen-specific FE models of the human pelvis and to use this cohort to analyze pelvic strain patterns during gait. Using an initially segmented specimen-specific pelvic FE model as a source model, four more specimen-specific pelvic FE models were generated from target clinical CT scans using landmark-based morphing and mapping techniques. FE strains from the five models were compared to the experimental strains obtained from cadaveric testing via linear regression analysis, (R² values ranging from 0.70 to 0.93). Inter-specimen variability in FE strain distributions was seen among the five specimen-specific pelvic FE models. The validated cohort of specimen-specific pelvic FE models was utilized to examine pelvic strains at different phases of the gait cycle. Each validated specimen-specific FE model was reconfigured into gait cycle phases representing heel-strike/heel-off and midstance/midswing. No significant difference was found in the double-leg stance and heel-strike/heel-off models (p = 0.40). A trend was observed between double-leg stance and midstance/midswing models (p = 0.07), and a significant difference was found between heel-strike/heel-off models and midstance/midswing models (p = 0.02). Significant differences were also found in comparing right vs. left models (heel-strike/heel-off p = 0.14, midstance/midswing p = 0.04).     

Noninvasive prediction of vertebral body compressive strength using nonlinear finite element method and an image based technique

Noninvasive prediction of vertebral body strength under compressive loading condition is a valuable tool for the assessment of clinical fractures. This paper presents an effective specimen-specific approach for noninvasive prediction of human vertebral strength using a nonlinear finite element (FE) model and an image based parameter based on the quantitative computed tomography (QCT). Nine thoracolumbar vertebrae excised from three cadavers with an average age of 42 years old were used as the samples. The samples were scanned using the QCT. Then, a segmentation technique was performed on each QCT sectional image. The segmented images were then converted into three-dimensional FE models for linear and nonlinear analyses. A new material model was implemented in our nonlinear model being more compatible with real mechanical behavior of trabecular bone. A new image based MOS (Mechanic of Solids) parameter named minimum sectional strength ((σ_uA)_min) was used for the ultimate compressive strength prediction. Subsequently, the samples were destructively tested under uniaxial compression and their experimental ultimate compressive strengths were obtained. Results indicated that our new implemented FE model can predict ultimate compressive strength of human vertebra with a correlation coefficient (R² = 0.94) better than usual linear and nonlinear FE models (R² = 0.83 and 0.85 respectively). The image based parameter introduced in this study ((σ_uA)_min) was also correlated well with the experimental results (R² = 0.86). Although nonlinear FE method with new implemented material model predicts compressive strength better than the (σ_uA)_min, this parameter is clinically more feasible due to its simplicity and lower computational costs. This can make future applications of the (σ_uA)_min more justified for human vertebral body compressive strength prediction.     

Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo

The mechanical properties of human soft tissue are crucial for impact biomechanics, rehabilitation engineering, and surgical simulation. Validation of these constitutive models using human data remains challenging and often requires the use of non-invasive imaging and inverse finite element (FE) analysis. Post-processing data from imaging methods such as tagged magnetic resonance imaging (MRI) can be challenging. Digital image correlation (DIC), however, is a relatively straightforward imaging method. DIC has been used in the past to study the planar and superficial properties of soft tissue and excised soft tissue layers. However, DIC has not been used to non-invasive study of the bulk properties of human soft tissue in vivo. Thus, the goal of this study was to assess the use of DIC in combination with FE modelling to determine the bulk material properties of human soft tissue. Indentation experiments were performed on a silicone gel soft tissue phantom. A two camera DIC setup was then used to record the 3D surface deformation. The experiment was then simulated using a FE model. The gel was modelled as Neo-Hookean hyperelastic, and the material parameters were determined by minimising the error between the experimental and FE data. The iterative FE analysis determined material parameters (μ=1.80 kPa, K=2999 kPa) that were in close agreement with parameters derived independently from regression to uniaxial compression tests (μ=1.71 kPa, K=2857 kPa). Furthermore the FE model was capable of reproducing the experimental indentor force as well as the surface deformation found (R²=0.81). It was therefore concluded that a two camera DIC configuration combined with FE modelling can be used to determine the bulk mechanical properties of materials that can be represented using hyperelastic Neo-Hookean constitutive laws.     

Management scenario evaluation for a large treatment wetland using a spatio-temporal phosphorus transport and cycling model

This paper describes the development of a two-dimensional, spatially distributed model to simulate coupled hydrologic and phosphorus (P) biogeochemical processes in a 147-ha cell of a 1544-ha stormwater treatment wetland designed to help protect the greater Everglades, FL, USA. The model was used to assess the effects of a suite of feasible management alternatives on the long-term ability of the wetland to sustain total P (TP) removal. The spatial and temporal dynamics of TP retention were simulated under historical (1995–2000) conditions, and under assumptions of removal of short-circuiting channels and ditches, changes in external hydraulic and TP loading, and long-term (>20 years) impacts on soil and water column TP dynamics under current and reduced load conditions. Internal hydrology and transport processes were calibrated against measured tracer concentrations, and subsequently validated against outflow discharge and spatial chloride concentration data. Cycling of P was simulated as first-order uptake and release, with different uptake coefficients for open water/sparse submerged aquatic vegetation (SAV) areas (0.2 day^?1) and dense SAV areas (0.4 day^?1), and a much lower, uniform release coefficient (1.97 × 10^?4 day^?1). The calibration and validation of the P model showed good agreement with field measurements of water column TP concentrations measured at the wetland outlet (calibration RMSE = 10.5 μg L^?1; validation RMSE = 15.6 μg L^?1). Under simulated conditions of preferential channels eliminated, average annual TP treatment effectiveness increased by 25%. When inflow TP loads were assumed to be eliminated after 6 years of loading, the release of accumulated soil P sustained predicted annual average outlet concentrations above 6.7 μg L^?1 for 18 years, decreasing at a rate of 0.16 μg L^?1 yr^?1. Sensitivity analyses indicate that the most critical model input factors include flow resistance parameters, initial soil TP content, and P cycling parameters compared to initial water level, initial TP concentration in water column, ET and transport parameters.     

Estimation of wetland vegetation height and leaf area index using airborne laser scanning data

Wetland vegetation is a core component of wetland ecosystems. Wetland vegetation structural parameters, such as height and leaf area index (LAI) are important variables required by earth-system and ecosystem models. Therefore, rapid, accurate, objective and quantitative estimations of wetland vegetation structural parameters are essential. The airborne laser scanning (also called LiDAR) is an active remote sensing technology and can provide accurate vertical vegetation structural parameters, but its accuracy is limited by short, dense vegetation canopies that are typical of wetland environments. The objective of this research is to explore the potential of estimating height and LAI for short wetland vegetation using airborne discrete-return LiDAR data.The accuracies of raw laser points and LiDAR-derived digital elevation models (DEM) data were assessed using field GPS measured ground elevations. The results demonstrated very high accuracy of 0.09 m in raw laser points and the root mean squared error (RMSE) of the LiDAR-derived DEM was 0.15 m.Vegetation canopy height was estimated from LiDAR data using a canopy height model (CHM) and regression analysis between field-measured vegetation heights and the standard deviation (σ) of detrended LiDAR heights. The results showed that the actual height of short wetland vegetation could not be accurately estimated using the raster CHM vegetation height. However, a strong relationship was observed between the σ and the field-measured height of short wetland vegetation and the highest correlation occurred (R² = 0.85, RMSE = 0.14 m) when sample radius was 1.50 m. The accuracy assessment of the best-constructed vegetation height prediction model was conducted using 25 samples that were not used in the regression analysis and the results indicated that the model was reliable and accurate (R² = 0.84, RMSE = 0.14 m).Wetland vegetation LAI was estimated using laser penetration index (LPI) and LiDAR-predicted vegetation height. The results showed that the vegetation height-based predictive model (R² = 0.79) was more accurate than the LPI-based model (the highest R² was 0.70). Moreover, the LAI predictive model based on vegetation height was validated using the leave-one-out cross-validation method and the results showed that the LAI predictive model had a good generalization capability. Overall, the results from this study indicate that LiDAR has a great potential to estimate plant height and LAI for short wetland vegetation.     

Applying a follower load delivers realistic results for simulating standing

The exact loads acting on the lumbar spine during standing remain hitherto unknown. It is for this reason that different loads are applied in experimental and numerical studies. The aim of this study was to compare intersegmental rotations, intradiscal pressures and facet joint forces for different loading modes simulating standing in order to ascertain, the results for which loading modes are closest to data measured in vivo.A validated osseoligamentous finite element model of the lumbar spine ranging from L1 to the disc L5–S1, was used. Six load application modes were investigated as to how they could simulate standing. This posture was simulated by applying a vertical force of 500 N at the centre of the L1 vertebral endplate with different boundary conditions, by applying a follower load, and by applying upper body weight and muscle forces. The calculated intersegmental rotations and intradiscal pressures were compared to in vivo values.Intersegmental rotations at one level vary by up to 8° for the different loading modes simulating standing. The overall rotation in the lumbar spine varies between 2.2° and 19.5°. With a follower load, the difference to the value measured in vivo is 3.3°. For all other loading cases studied, the difference is greater than 6.6°. Intradiscal pressures vary slightly with the loading mode. Calculated forces in the facet joints vary between 0 and nearly 80 N.Applying a follower load of 500 N is the only loading mode simulating standing for which the calculated values for intervertebral rotations and intradiscal pressures agreed well with in vivo data from literature.     

Improved retrieval of Secchi depth for optically-complex waters using remote sensing data

Water transparency is one of the ecological indicators for describing water quality and the underwater light field which determines its productivity. In the European Water Framework Directive (WFD) as well as in the European Marine Strategy Framework Directive (MSFD) water transparency is used for ecological status classification of inland, coastal and open sea waters and it is regarded as an indicator for eutrophication in Baltic Sea management (HELCOM, 2007). We developed and compared different empirical and semi-analytical algorithms for lakes and coastal Nordic waters to retrieve Secchi depth (Z_SD) from remote sensing data (MERIS, 300 m resolution). The algorithms were developed in water bodies with high coloured dissolved organic matter absorption (a_CDOM(442) ranging 1.7–4.0 m⁻¹), Chl a concentration (0.5–73 mg m⁻³) and total suspended matter (0.7–37.5 g m⁻³) and validated against an independent data set over inland and coastal waters (0.6 m < Z_SD < 14.8 m). The results indicate that for empirical algorithms, using longer wavelengths in the visible spectrum as a reference band decreases the RMSE and increases the coefficient of determination (R²). The accuracy increased (R² = 0.75, RMSE = 1.33 m, n = 134) when Z_SD was retrieved via an empirical relationship between Z_SD and K_d(490). The best agreement with in situ data was attained when Z_SD was calculated via both the diffuse and the beam attenuation coefficient (R² = 0.89, RMSE = 0.77 m, n = 89). The results demonstrate that transparency can be retrieved with high accuracy over various optical water types by the means of ocean color remote sensing, improving both the spatial and temporal coverage. The satellite derived Z_SD product could be therefore used as an additional source of information for WFD and MSFD reporting purposes.     

Estimation of gross primary production of irrigated maize using Landsat-8 imagery and Eddy Covariance data

A study was conducted to understand the potential of Landsat-8 in the estimation of gross primary production (GPP) and to quantify the productivity of maize crop cultivated under hyper-arid conditions of Saudi Arabia. The GPP of maize crop was estimated by using the Vegetation Photosynthesis Model (VPM) utilizing remote sensing data from Landsat-8 reflectance (GPP_VPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPP_EC), for the period from August to November 2015. Results revealed that the cumulative GPP_EC for the entire growth period of maize crop was 1871 g C m⁻². However, the cumulative GPP determined as a function of the enhanced vegetation index – EVI (GPP_EVI) was 1979 g C m⁻², and that determined as a function of the normalized difference vegetation index – NDVI (GPP_NDVI) was 1754 g C m⁻². These results indicated that the GPP_EVI was significantly higher than the GPP_EC (R² = 0.96, P = 0.0241 and RMSE = 12.6%). While, the GPP_NDVI was significantly lower than the GPP_EC (R² = 0.93, P = 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPP_EC and both the GPP_EVI and the GPP_NDVI was −6.22% and 5.76%, respectively. These results demonstrated the potential of the landsat-8 driven VPM model for the estimation of GPP, which is relevant to the productivity and carbon fluxes.     

The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures

Retrieving leaf chlorophyll content at a range of spatio-temporal scales is central to monitoring vegetation productivity, identifying physiological stress and managing biological resources. However, estimating leaf chlorophyll over broad spatial extents using ground-based traditional methods is time and resource heavy. Satellite-derived spectral vegetation indices (VIs) are commonly used to estimate leaf chlorophyll content, however they are often developed and tested on broadleaf species. Relatively little research has assessed VIs for different leaf structures, particularly needle leaves which represent a large component of boreal forest and significant global ecosystems. This study tested the performance of 47 published VIs for estimating foliar chlorophyll content from different leaf and canopy structures (broadleaf and needle). Coniferous and deciduous sites were selected in Ontario, Canada, representing different dominant vegetation species (Picea mariana and Acer saccharum) and a variety of canopy structures. Leaf reflectance data was collected using an ASD Fieldspec Pro spectroradiometer (400–2500 nm) for over 300 leaf samples. Canopy reflectance data was acquired from the medium resolution imaging spectrometer (MERIS). At the canopy level, with both leaf types combined, the DD-index showed the strongest relationship with leaf chlorophyll (R² = 0.78; RMSE = 3.56 μg/cm²), despite differences in leaf structure. For needleleaf trees alone the relationship with the top VI was weaker (D_[red], R² = 0.71; RMSE = 2.32 μg/cm²). A sensitivity study using simulated VIs from physically-modelled leaf (PROSPECT) and canopy (4-Scale) reflectance was performed in order to further investigate these results and assess the impacts of different background types and leaf area index on the VIs’ performance. At the leaf level, the MNDVI8 index showed a strong linearity to changing chlorophyll and negligible difference to leaf structure/type. At canopy level, the best performing VIs were relatively consistent where LAI ≥ 4, but responded strongly to differences in background at low canopy coverage (LAI = 2). This research provides comprehensive assessments for the use of spectral indices in retrieval of spatially-continuous leaf chlorophyll content at the leaf (MTCI: R² = 0.72; p < 0.001) and canopy (DD: R² = 0.78; p < 0.001) level for resource management over different spatial and temporal scales.     

Obesity and spinal loads; a combined MR imaging and subject-specific modeling investigation

Epidemiological studies have identified obesity as a possible risk factor for low back disorders. Biomechanical models can help test such hypothesis and shed light on the mechanism involved. A novel subject-specific musculoskeletal-modelling approach is introduced to estimate spinal loads during static activities in five healthy obese (BMI > 30 kg/m²) and five normal-weight (20 < BMI < 25 kg/m²) individuals. Subjects underwent T1 through S1 MR imaging thereby measuring cross-sectional-area (CSA) and moment arms of trunk muscles together with mass and center of mass (CoM) of T1-L5 segments. MR-based subject-specific models estimated spinal loads using a kinematics/optimization-driven approach. Average CSAs of muscles, moment arms of abdominal muscles, mass and sagittal moment arm of CoM of T1-L5 segments were larger in obese individuals (p < 0.05 except for the moment arm of CoMs) but moment arms of their back muscles were similar to those of normal-weight individuals (p > 0.05). Heavier subjects did not necessarily have larger muscle moment arms (e.g., they were larger in 64 kg (BMI = 20.7 kg/m²) subject than 78 kg (BMI = 24.6 kg/m²) subject) or greater T1-L5 trunk weight (e.g., the 97 kg (BMI = 31 kg/m²) subject had similar trunk weight as 109 kg (BMI = 33.3 kg/m²) subject). Obese individuals had in average greater spinal loads than normal-weight ones but heavier subjects did not necessarily have greater spinal loads (117 kg (BMI = 40.0 kg/m²) subject had rather similar L5-S1 compression as 105 kg (BMI = 34.7 kg/m²) subject). Predicted L4-L5 intradiscal pressures for the normal-weight subjects ranged close to the measured values (R² = 0.85–0.92). Obese individuals did not necessarily have greater IDPs than normal-weight ones.     

Performance evaluation of various bioreactors for the removal of Cr(VI) and organic matter from industrial effluent

Performances of various bioreactors under different operating conditions were evaluated with respect to hexavalent chromium (Cr(VI)) reduction and COD removal. Continuous reactor studies were carried out with (i) aerobic suspended growth system, (ii) aerobic attached growth system, and (iii) anoxic attached growth system, using both synthetic and actual industrial wastewater. Arthrobacter rhombi-RE (MTCC7048), a Cr(VI) reducing strain enriched and isolated from chromium contaminated soil, was used in all the bioreactors for Cr(VI) biotransformation and COD removal. Aerobic and anoxic batch experiments were conducted to evaluate the bio-kinetic parameters. The bio-kinetic parameters for aerobic system were: μ_max = 2.34/d, K_s = 190 mg/L (as COD), K_i = 3.8 mg/L of Cr(VI), and Y_T = 0.377. These parameters for anoxic conditions were: μ_max = 0.57/d, K_s = 710 mg/L (as COD), K_i = 8.77 mg/L of Cr(VI), and Y_T = 0.13. Aerobic attached growth system, operated at a hydraulic retention time (HRT) of 24 h and an organic loading rate (OLR) of 3 kg/m³/d, performed better than aerobic suspended and the anoxic attached growth systems operated under identical conditions, while treating synthetic wastewater as well as industrial effluent.     

Electromyographic and mechanomyographic responses across repeated maximal isometric and concentric muscle actions of the leg extensors

The purpose of the present study was to examine the patterns of responses for torque, electromyographic (EMG) amplitude, EMG mean power frequency (MPF), mechanomyographic (MMG) amplitude, and MMG MPF across 30 repeated maximal isometric (ISO) and concentric (CON) muscle actions of the leg extensors. Twelve female subjects (21.1 ± 1.4 yrs; 63.3 ± 7.4 kg) performed ISO and CON fatigue protocols with EMG and MMG signals recorded from the vastus lateralis. The relationships for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF versus repetition number were examined using polynomial regression. The results indicated there were decreases (p < 0.05) across the ISO muscle actions for torque (r² = 0.95), EMG amplitude (R² = 0.44), EMG MPF (r² = 0.62), and MMG MPF (r² = 0.48), but no change in MMG amplitude (r² = 0.07). In addition, there were decreases across the CON muscle actions for torque (R² = 0.97), EMG amplitude (R² = 0.46), EMG MPF (R² = 0.86), MMG amplitude (R² = 0.44), and MMG MPF (R² = 0.80). Thus, the current findings suggested that the mechanisms of fatigue and motor control strategies used to modulate torque production were similar between maximal ISO and CON muscle actions.     

Tissue viscoelasticity is related to tissue composition but may not fully predict the apparent-level viscoelasticity in human trabecular bone – An experimental and finite element study

Trabecular bone is viscoelastic under dynamic loading. However, it is unclear how tissue viscoelasticity controls viscoelasticity at the apparent-level. In this study, viscoelasticity of cylindrical human trabecular bone samples (n = 11, male, age 18–78 years) from 11 proximal femurs were characterized using dynamic and stress-relaxation testing at the apparent-level and with creep nanoindentation at the tissue-level. In addition, bone tissue elasticity was determined using scanning acoustic microscope (SAM). Tissue composition and collagen crosslinks were assessed using Raman micro-spectroscopy and high performance liquid chromatography (HPLC), respectively. Values of material parameters were obtained from finite element (FE) models by optimizing tissue-level creep and apparent-level stress-relaxation to experimental nanoindentation and unconfined compression testing values, respectively, utilizing the second order Prony series to depict viscoelasticity. FE simulations showed that tissue-level equilibrium elastic modulus (E_eq) increased with increasing crystallinity (r = 0.730, p = .011) while at the apparent-level it increased with increasing hydroxylysyl pyridinoline content (r = 0.718, p = .019). In addition, the normalized shear modulus g₁ (r = −0.780, p = .005) decreased with increasing collagen ratio (amide III/CH₂) at the tissue-level, but increased (r = 0.696, p = .025) with increasing collagen ratio at the apparent-level. No significant relations were found between the measured or simulated viscoelastic parameters at the tissue- and apparent-levels nor were the parameters related to tissue elasticity determined with SAM. However, only E_eq, g₂ and relaxation time τ₁ from simulated viscoelastic values were statistically different between tissue- and apparent-levels (p < .01). These findings indicate that bone tissue viscoelasticity is affected by tissue composition but may not fully predict the macroscale viscoelasticity in human trabecular bone.     

Muscle activation patterns of knee flexors and extensors during passive and active movement of the spastic lower limb in chronic stroke patients

The aim of this study was to describe the characteristics of spasticity, quantified as muscle activity during stretch, during passive and active movement. For this cross sectional study 19 stroke patients with spasticity in the lower limb were recruited. Reflex activity was studied with surface electromyography of knee flexor and extensor muscles during passive and active movement of the lower leg.On both the affected and unaffected side, root mean square values of the knee extensor muscles, while stretched, were higher during active than during passive movement (p < 0.05). For the vastus lateralis (VL) the correlation was moderate (ρ = 0.54, p = 0.022), for the rectus femoris (RF) high (ρ = 0.83, p < 0.001). For the semitendinosus (ST) the correlation was low (ρ = 0.27) and not significant.During active movement the correlation between VL activity and activity of the antagonist ST, as an indicator for co-contraction of the affected muscles, was marked (ρ = 0.73, p = 0.001). A moderate negative correlation was found between reflex activity of RF during passive stretch and the active range of motion (ρ = ?0.51, p = 0.027).The results show that a passive stretch test alone is insufficient either as assessment method for spasticity during active motor tasks or as a measure for motor control.     

Demonstration of extended field-of-view ultrasound’s potential to increase the pool of muscles for which in vivo fascicle length is measurable

Static, B-mode ultrasound is the most common method of measuring fascicle length in vivo. However, most forearm muscles have fascicles that are longer than the field-of-view of traditional ultrasound (T-US). As such, little work has been done to quantify in vivo forearm muscle architecture. The extended field-of-view ultrasound (EFOV-US) method, which fits together a sequence of B-mode images taken from a continuous ultrasound scan, facilitates direct measurements of longer, curved fascicles. Here, we test the validity and reliability of the EFOV-US method for obtaining fascicle lengths in the extensor carpi ulnaris (ECU). Fascicle lengths from images of the ECU captured in vivo with EFOV-US were compared to lengths from a well-established method, T-US. Images were collected in a joint posture that shortens the ECU such that entire fascicle lengths were captured within a single T-US image. Resulting measurements were not significantly different (p = 0.18); a Bland-Altman test demonstrated their agreement. A novice sonographer implemented EFOV-US in a phantom and in vivo on the ECU. The novice sonographer’s measurements from the ultrasound phantom indicate that the combined imaging and analysis method is valid (average error = 2.2 ± 1.3 mm) and the in vivo fascicle length measurements demonstrate excellent reliability (ICC = 0.97). To our knowledge, this is the first study to quantify in vivo fascicle lengths of the ECU using any method. The ability to define a muscle’s architecture in vivo using EFOV-US could lead to improvements in diagnosis, model development, surgery guidance, and rehabilitation techniques.     

Muscle architecture variations along the human semitendinosus and biceps femoris (long head) length

The purpose of this study was to examine whether muscle architecture of the long head of biceps femoris (BF) and semitendinosus (ST) muscles varies along their length. The ST and BF muscles were dissected and removed from their origins in eight cadaveric specimens (age range 67.8–73.4 years). One-way analysis of variance designs were used to compare fascicle length (FL), pennation angle (PA) and muscle thickness (MT) between proximal, mid-belly and distal positions. Tendon and muscle length properties were also quantified. For the BF muscle, one-way analysis of variance tests showed a higher PA (23.96 ± 3.82°) and FL (7.12 ± 0.48 cm) proximally than distal positions (PA = 17.78 ± 1.95° and FL = 6.35 ± 0.89 cm, respectively). For the ST, there was a significantly (p < 0.05) lower PA (8.81 ± 1.22°) and FL (13.10 ± 1.54 cm) proximally than distally (PA = 14.69 ± 1.09° and FL = 15.49 ± 2.30 cm, respectively). Muscle thickness significantly increased from distal to more proximal positions (p < 0.05). These data suggest that the ST and BF architecture is not uniform and that measurement of these parameters largely depends on the measurement site. Modeling these muscles by assuming a uniform architecture along muscle length may yield less accurate representation of human hamstring muscle function.     

The in vivo assessment of mechanical loadings on pectoral pacemaker implants

Reduced sizes of implantable cardiac pacemakers and clinical advances have led to a higher feasibility of using such devices in younger patients including children. Increased structural demands deriving from reduced device size and more active recipients require detailed knowledge of in vivo mechanical conditions to ensure device reliability. Objective of this study was the proof of feasibility of a system for the measurement of in vivo mechanical loadings on pacemaker implants. The system comprised the following: implantable instrumented pacemaker (IPM) with six force sensors, accelerometer and radio-frequency (RF) transceiver; RF data logging system and video capture system. Three Chacma baboons (20.6±1.15 kg) received one pectoral sub-muscular IPM implant. After wound healing, forces were measured during physical activities. Forces during range of motion of the arm were assessed on the anaesthetized animals prior to device explantation. Mass, volume and dimensions of the excised Pectoralis major muscles were determined after device explantation. Remote IPM activation and data acquisition were reliable in the indoor cage environment with transceiver distances of up to 3 m. Sampling rates of up to 1000 Hz proved sufficient to capture dynamic in vivo loadings. Compressive forces on the IPM in conscious animals reached a maximum of 77.2±54.6 N during physical activity and were 22.2±7.3 N at rest, compared with 34.6±15.7 N maximum during range of motion and 13.4±3.3 N at rest in anaesthetized animals. The study demonstrated the feasibility of the developed system for the assessment of in vivo mechanical loading conditions of implantable pacemakers with potential for use for other implantable therapeutic devices.