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Review Article

J Biomech Eng. 2018;140(3):030801-030801-11. doi:10.1115/1.4038741.

Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4 mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i.e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra- and inter-observer variability; and (vi) validation against ground-truth bone kinematics (with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).

Commentary by Dr. Valentin Fuster

Research Papers

J Biomech Eng. 2018;140(3):031001-031001-9. doi:10.1115/1.4038743.

Predicting aortic aneurysm ruptures is a complex problem that has been investigated by many research teams over several decades. Work on this issue is notably complex and involves both the mechanical behavior of the artery and the blood flow. Magnetic resonance imaging (MRI) can provide measurements concerning the shape of an organ and the blood that flows through it. Measuring local distortion of the artery wall is the first essential factor to evaluate in a ruptured artery. This paper aims to demonstrate the feasibility of this measure using MRI on a phantom of an abdominal aortic aneurysm (AAA) with realistic shape. The aortic geometry is obtained from a series of cine-MR images and reconstructed using Mimics software. From 4D flow and MRI measurements, the field of velocity is determined and introduced into a computational fluid dynamic (CFD) model to determine the mechanical boundaries applied on the wall artery (pressure and ultimately wall shear stress (WSS)). These factors are then converted into a solid model that enables wall deformations to be calculated. This approach was applied to a silicone phantom model of an AAA reconstructed from a patient's computed tomography-scan examination. The calculated deformations were then compared to those obtained in identical conditions by stereovision. The results of both methods were found to be close. Deformations of the studied AAA phantom with complex shape were obtained within a gap of 12% by modeling from MR data.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031002-031002-13. doi:10.1115/1.4038357.

Linking head kinematics to injury risk has been the focus of numerous brain injury criteria. Although many early forms were developed using mechanics principles, recent criteria have been developed using empirical methods based on subsets of head impact data. In this study, a single-degree-of-freedom (sDOF) mechanical analog was developed to parametrically investigate the link between rotational head kinematics and brain deformation. Model efficacy was assessed by comparing the maximum magnitude of displacement to strain-based brain injury predictors from finite element (FE) human head models. A series of idealized rotational pulses covering a broad range of acceleration and velocity magnitudes (0.1–15 krad/s2 and 1–100 rad/s) with durations between 1 and 3000 ms were applied to the mechanical models about each axis of the head. Results show that brain deformation magnitude is governed by three categories of rotational head motion each distinguished by the duration of the pulse relative to the brain's natural period: for short-duration pulses, maximum brain deformation depended primarily on angular velocity magnitude; for long-duration pulses, brain deformation depended primarily on angular acceleration magnitude; and for pulses relatively close to the natural period, brain deformation depended on both velocity and acceleration magnitudes. These results suggest that brain deformation mechanics can be adequately explained by simple mechanical systems, since FE model responses and experimental brain injury tolerances exhibited similar patterns to the sDOF model. Finally, the sDOF model was the best correlate to strain-based responses and highlighted fundamental limitations with existing rotational-based brain injury metrics.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031003-031003-5. doi:10.1115/1.4038288.

Stress fractures are a common overuse injury among runners associated with the mechanical fatigue of bone. Several in vivo biomechanical studies have investigated specific characteristics of the vertical ground reaction force (vGRF) in heel-toe running and have observed an association between increased loading rate during impact and individuals with a history of stress fracture. The purpose of this study was to examine the fatigue behavior of cortical bone using vGRF-like loading profiles, including those that had been decomposed into their respective impact and active phase components. Thirty-eight cylindrical cortical bone samples were extracted from bovine tibiae and femora. Hydrated samples were fatigue tested at room temperature in zero compression under load control using either a raw (n = 10), active (n = 10), low impact (n = 10), or high impact (n = 8) vGRF profile. The number of cycles to failure was quantified and the test was terminated if the sample survived 105 cycles. Fatigue life was significantly greater for both impact groups compared to the active (p < 0.001) and raw (p < 0.001) groups, with all low impact samples and 6 of 8 high impact samples surviving 105 cycles. The mean (± SD) number of cycles to failure for the active and raw groups was 12,133±11,704 and 16,552±29,612, respectively. The results suggest that loading rates associated with the impact phase of a typical vGRF in running have little influence on the mechanical fatigue behavior of bone relative to loading magnitude, warranting further investigation of the mechanism by which increased loading rates are associated with stress fracture.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031004-031004-9. doi:10.1115/1.4037563.

Coronally uneven terrain, a common yet challenging feature encountered in daily ambulation, exposes individuals to an increased risk of falling. The foot-ankle complex may adapt to improve balance on uneven terrains, a recovery strategy which may be more challenging in patients with foot-ankle pathologies. A multisegment foot model (MSFM) was used to study the biomechanical adaptations of the foot and ankle joints during a step on a visually obscured, coronally uneven surface. Kinematic, kinetic and in-shoe pressure data were collected as ten participants walked on an instrumented walkway with a surface randomly positioned ±15 deg or 0 deg in the coronal plane. Coronally uneven surfaces altered hindfoot–tibia loading, with more conformation to the surface in early than late stance. Distinct loading changes occurred for the forefoot–hindfoot joint in early and late stance, despite smaller surface conformations. Hindfoot–tibia power at opposite heel contact (@OHC) was generated and increased on both uneven surfaces, whereas forefoot–hindfoot power was absorbed and remained consistent across surfaces. Push-off work increased for the hindfoot–tibia joint on the everted surface and for the forefoot–hindfoot joint on the inverted surface. Net work across joints was generated for both uneven surfaces, while absorbed on flat terrain. The partial decoupling and joint-specific biomechanical adaptations on uneven surfaces suggest that multi-articulating interventions such as prosthetic devices and arthroplasty may improve ambulation for mobility-impaired individuals on coronally uneven terrain.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031005-031005-11. doi:10.1115/1.4038251.

Shoe–floor interactions play a crucial role in determining the possibility of potential slip and fall during human walking. Biomechanical and tribological parameters influence the friction characteristics between the shoe sole and the floor and the existing work mainly focus on experimental studies. In this paper, we present modeling, analysis, and experiments to understand slip and force distributions between the shoe sole and floor surface during human walking. We present results for both soft and hard sole material. The computational approaches for slip and friction force distributions are presented using a spring-beam networks model. The model predictions match the experimentally observed sole deformations with large soft sole deformation at the beginning and the end stages of the stance, which indicates the increased risk for slip. The experiments confirm that both the previously reported required coefficient of friction (RCOF) and the deformation measurements in this study can be used to predict slip occurrence. Moreover, the deformation and force distribution results reported in this study provide further understanding and knowledge of slip initiation and termination under various biomechanical conditions.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031006-031006-14. doi:10.1115/1.4038430.

Hypertension is a well-documented predictive factor for cardiovascular events. Clinical studies have extensively demonstrated the differential hemodynamic consequences of various antihypertensive drugs, but failed to clearly elucidate the underlying mechanisms due to the difficulty in performing a quantitative deterministic analysis based on clinical data that carry confounding information stemming from interpatient differences and the nonlinearity of cardiovascular hemodynamics. In the present study, a multiscale model of the cardiovascular system was developed to quantitatively investigate the relationships between hemodynamic variables and cardiovascular properties under hypertensive conditions, aiming to establish a theoretical basis for assisting in the interpretation of clinical observations or optimization of therapy. Results demonstrated that heart period, central arterial stiffness, and arteriolar radius were the major determinant factors for blood pressures and flow pulsatility indices both in large arteries and in the microcirculation. These factors differed in the degree and the way in which they affect hemodynamic variables due to their differential effects on wave reflections in the vascular system. In particular, it was found that the hemodynamic effects of varying arteriolar radius were considerably influenced by the state of central arterial stiffness, and vice versa, which implied the potential of optimizing antihypertensive treatment by selecting proper drugs based on patient-specific cardiovascular conditions. When analyzed in relation to clinical observations, the simulated results provided mechanistic explanations for the beneficial pressure-lowering effects of vasodilators as compared to β-blockers, and highlighted the significance of monitoring and normalizing arterial stiffness in the treatment of hypertension.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031007-031007-11. doi:10.1115/1.4037950.

Understanding the impact of thermally and mechanically loading biological tissue to supraphysiological levels is becoming of increasing importance as complex multiphysical tissue–device interactions increase. The ability to conduct accurate, patient specific computer simulations would provide surgeons with valuable insight into the physical processes occurring within the tissue as it is heated or cooled. Several studies have modeled tissue as porous media, yet fully coupled thermoporomechanics (TPM) models are limited. Therefore, this study introduces a small deformation theory of modeling the TPM occurring within biological tissue. Next, the model is used to simulate the mass, momentum, and energy balance occurring within an artery wall when heated by a tissue fusion device and compared to experimental values. Though limited by its small strain assumption, the model predicted final tissue temperature and water content within one standard deviation of experimental data for seven of seven simulations. Additionally, the model showed the ability to predict the final displacement of the tissue to within 15% of experimental results. These results promote potential design of novel medical devices and more accurate simulations allowing for scientists and surgeons to quickly, yet accurately, assess the effects of surgical procedures as well as provide a first step toward a fully coupled large deformation TPM finite element (FE) model.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031008-031008-9. doi:10.1115/1.4038739.

In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031009-031009-7. doi:10.1115/1.4038742.

Venous ulcers are deep wounds that are located predominantly on the lower leg. They are prone to infection and once healed have a high probability of recurrence. Currently, there are no effective measures to predict and prevent venous ulcers from formation. Hence, the goal of this work was to develop a Windkessel-based model that can be used to identify hemodynamic parameters that change between healthy individuals and those with wounds. Once identified, these parameters have the potential to be used as indicators of when internal conditions change, putting the patient at higher risk for wound formation. In order to achieve this goal, blood flow responses in lower legs were measured experimentally by a laser Doppler perfusion monitor (LDPM) and simulated with a modeling approach. A circuit model was developed on the basis of the Windkessel theory. The hemodynamic parameters were extracted for three groups: legs with ulcers (“wounded”), legs without ulcers but from ulcer patients (“nonwounded”), and legs without vascular disease (“healthy”). The model was executed by two independent operators, and both operators reported significant differences between wounded and healthy legs in localized vascular resistance and compliance. The model successfully replicated the experimental blood flow profile. The global and local vascular resistances and compliance parameters rendered quantifiable differences between a population with venous ulcers and healthy individuals. This work supports that the Windkessel modeling approach has the potential to determine patient specific parameters that can be used to identify when conditions change making venous ulcer formation more likely.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031010-031010-7. doi:10.1115/1.4038329.

Bicuspid aortic valve (BAV) is the most common type of congenital heart disease, occurring in 0.5–2% of the population, where the valve has only two rather than the three normal cusps. Valvular pathologies, such as aortic regurgitation and aortic stenosis, are associated with BAVs, thereby increasing the need for a better understanding of BAV kinematics and geometrical characteristics. The aim of this study is to investigate the influence of the nonfused cusp (NFC) angle in BAV type-1 configuration on the valve's structural and hemodynamic performance. Toward that goal, a parametric fluid–structure interaction (FSI) modeling approach of BAVs is presented. Four FSI models were generated with varying NFC angles between 120 deg and 180 deg. The FSI simulations were based on fully coupled structural and fluid dynamic solvers and corresponded to physiologic values, including the anisotropic hyper-elastic behavior of the tissue. The simulated angles led to different mechanical behavior, such as eccentric jet flow direction with a wider opening shape that was found for the smaller NFC angles, while a narrower opening orifice followed by increased jet flow velocity was observed for the larger NFC angles. Smaller NFC angles led to higher concentrated flow shear stress (FSS) on the NFC during peak systole, while higher maximal principal stresses were found in the raphe region during diastole. The proposed biomechanical models could explain the early failure of BAVs with decreased NFC angles, and suggests that a larger NFC angle is preferable in suture annuloplasty BAV repair surgery.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):031011-031011-8. doi:10.1115/1.4038289.

Arteriovenous fistulae (AVF) are the preferred choice of vascular access in hemodialysis patients; however, complications such as stenosis can lead to access failure or recirculation, which reduces dialysis efficiency. This study utilized computational fluid dynamics on a patient-specific radiocephalic fistula under hemodialysis treatment to determine the dynamics of access recirculation and identify the presence of disturbed flow. Metrics of transverse wall shear stress (transWSS) and oscillatory shear index (OSI) were used to characterize the disturbed flow acting on the blood vessel wall, while a power spectral density (PSD) analysis was used to calculate the any turbulence within the access. Results showed that turbulence is generated at the anastomosis and continues through the swing segment. The arterial needle dampens the flow as blood is extracted to the dialyzer, while the venous needle reintroduces turbulence due to the presence of jet flows. Adverse shear stresses are present throughout the vascular access and coincide with these complex flow fields. The position of the needles had no effect in minimizing these forces. However, improved blood extraction may occur when the arterial needle is placed further from the anastomosis, minimizing the effects of residual turbulent structures generated at the anastomosis. Furthermore, the arterial and venous needle may be placed in close proximity to each other without increasing the risk of access recirculation, in a healthy mature fistula, due to the relatively stable blood flow in this region. This may negate the need for a long cannulation segment and aid clinicians in optimizing needle placement for hemodialysis.

Commentary by Dr. Valentin Fuster

Technical Brief

J Biomech Eng. 2018;140(3):034501-034501-4. doi:10.1115/1.4038429.

Rotary blood pumps (RBPs) used for mechanical circulatory support of heart failure patients cannot passively change pump flow sufficiently in response to frequent variations in preload induced by active postural changes. A physiological control system that mimics the response of the healthy heart is needed to adjust pump flow according to patient demand. Thus, baseline data are required on how the healthy heart and circulatory system (i.e., heart rate (HR) and cardiac output (CO)) respond. This study investigated the response times of the healthy heart during active postural changes (supine-standing-supine) in 50 healthy subjects (27 male/23 female). Early response times (te) and settling times (ts) were calculated for HR and CO from data continuously collected with impedance cardiography. The initial circulatory response of HR and CO resulted in te of 9.0–11.7 s when standing up and te of 4.7–5.7 s when lying back down. Heart rate and CO settled in ts of 50.0–53.6 s and 46.3–58.2 s when standing up and lying down, respectively. In conclusion, when compared to active stand up, HR and CO responded significant faster initially when subjects were lying down (p < 0.05); there were no significant differences in response times between male and female subjects. These data will be used during evaluation of physiological control systems for RBPs, which may improve patient outcomes for end-stage heart failure patients.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;140(3):034502-034502-7. doi:10.1115/1.4038740.

Vertical jump height is widely used for assessing motor development, functional ability, and motor capacity. Traditional methods for estimating vertical jump height rely on force plates or optical marker-based motion capture systems limiting assessment to people with access to specialized laboratories. Current wearable designs need to be attached to the skin or strapped to an appendage which can potentially be uncomfortable and inconvenient to use. This paper presents a novel algorithm for estimating vertical jump height based on foot-worn inertial sensors. Twenty healthy subjects performed countermovement jumping trials and maximum jump height was determined via inertial sensors located above the toe and under the heel and was compared with the gold standard maximum jump height estimation via optical marker-based motion capture. Average vertical jump height estimation errors from inertial sensing at the toe and heel were −2.2±2.1 cm and −0.4±3.8 cm, respectively. Vertical jump height estimation with the presented algorithm via inertial sensing showed excellent reliability at the toe (ICC(2,1)=0.98) and heel (ICC(2,1)=0.97). There was no significant bias in the inertial sensing at the toe, but proportional bias (b=1.22) and fixed bias (a=10.23cm) were detected in inertial sensing at the heel. These results indicate that the presented algorithm could be applied to foot-worn inertial sensors to estimate maximum jump height enabling assessment outside of traditional laboratory settings, and to avoid bias errors, the toe may be a more suitable location for inertial sensor placement than the heel.

Topics: Algorithms , Sensors
Commentary by Dr. Valentin Fuster

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