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Cardiac valves simulation is one of the most complex tasks in cardiovascular modeling. Fluid–structure interaction is not only highly computationally demanding but also requires knowledge of the mechanical properties of the tissue. Therefore, an alternative is to include valves as resistive flow obstacles, prescribing the geometry (and its possible changes) in a simple way, but, at the same time, with a geometry complex enough to reproduce both healthy and pathological configurations. In this work, we present a generalized parametric model of the aortic valve to obtain patient-specific geometries that can be included into blood flow simulations using a resistive immersed implicit surface (RIIS) approach. Numerical tests are presented for geometry generation and flow simulations in aortic stenosis patients whose parameters are extracted from ECG-gated CT images. [ABSTRACT FROM AUTHOR]

In spine research, two possibilities to generate models exist: generic (population-based) models representing the average human and subject-specific representations of individuals. Despite the increasing interest in subject specificity, individualisation of spine models remains challenging. Neuro-musculoskeletal (NMS) models enable the analysis and prediction of dynamic motions by incorporating active muscles attaching to bones that are connected using articulating joints under the assumption of rigid body dynamics. In this study, we used forward-dynamic simulations to compare a generic NMS multibody model of the thoracolumbar spine including fully articulated vertebrae, detailed musculature, passive ligaments and linear intervertebral disc (IVD) models with an individualised model to assess the contribution of individual biological structures. Individualisation was achieved by integrating skeletal geometry from computed tomography and custom-selected muscle and ligament paths. Both models underwent a gravitational settling process and a forward flexion-to-extension movement. The model-specific load distribution in an equilibrated upright position and local stiffness in the L4/5 functional spinal unit (FSU) is compared. Load sharing between occurring internal forces generated by individual biological structures and their contribution to the FSU stiffness was computed. The main finding of our simulations is an apparent shift in load sharing with individualisation from an equally distributed element contribution of IVD, ligaments and muscles in the generic spine model to a predominant muscle contribution in the individualised model depending on the analysed spine level. [ABSTRACT FROM AUTHOR]

A Brain-Computer Interface (BCI) is a communication system that decodes and transfers information directly from the brain to external devices. The electroencephalogram (EEG) technique is used to measure the electrical signals corresponding to commands occurring in the brain to control functions. The signals used for control applications in BCI are called Motor Imagery (MI) EEG signals. EEG signals are noisy, so it is important to use the right methods to recognize patterns correctly. This study examined the performances of different classification schemes to train networks using Ensemble Subspace Discriminant classifier. Also, the most efficient feature space was found using Neighborhood Component Analysis. The maximum average accuracy in classifying MI signals corresponding to right-direction and left-direction was 80.4% with a subject-specific classification scheme and 250 features. [ABSTRACT FROM AUTHOR]

Forward and reverse springboard somersaulting dives use similar approaches with a hurdle step prior to the final board contact phase during which forward rotation is produced in forward takeoffs and backward rotation in reverse takeoffs. This study compared forward and reverse takeoffs for joint strength, activation complexity, technique kinematics, and rotation potential. A planar 8-segment torque-driven computer simulation model of springboard diving takeoff was used to determine isometric joint strength by matching performances of a forward 2½ somersault dive and a reverse 1½ somersault dive. Activation complexity for the reverse takeoff was increased to achieve a similar closeness of match as for the forward takeoff. Takeoff technique was optimised to maximise rotation potential of forward and reverse somersaulting dives. Kinematics at touchdown, lowest point and takeoff were compared for the optimised forward and reverse takeoff simulations. It was found that the optimised reverse somersaulting dive exhibited greater isometric strength for ankle plantarflexion and shoulder flexion, greater joint torque activation complexity for ankle plantarflexion and for knee flexion. There was also less forward motion during board depression, more hip extension and knee flexion during the later stages of board recoil, less capacity for rotation potential, and greater vertical velocity at takeoff. [ABSTRACT FROM AUTHOR]

Enhancing the performance of motor imagery-based Brain-Computer Interfaces (BCI) has been a significant goal in the BCI field. To achieve such a goal, several typical and promising techniques have been implemented, such as developing intelligent algorithms, combining features from different domains, extracting subject-specific parameters, and so forth. Previous studies performing temporal segmentation often ended up with a large number of features and placed a burden on computational cost, which poses a disadvantage to online analysis. This study proposes a novel approach to utilizing short-window segments to find an optimal combination of time segments and feature extractors. Electroencephalogram data from four datasets (BCI Competition IV dataset 2a, 2b and two self-acquired datasets) were segmented into four types of the time window and had features extracted by Common Spatial Pattern and its variants, and lastly classified by Linear Discriminant Analysis. The result shows that the combination of the “2-s with 1-s overlapping” segment and Filter Bank Common Spatial Pattern yields overall accuracy of 2–6.5% (p-value

Purpose: Parallel RF transmission (PTx) is one of the key technologies enabling high quality imaging at ultra‐high fields (≥7T). Compliance with regulatory limits on the local specific absorption rate (SAR) typically involves over‐conservative safety margins to account for intersubject variability, which negatively affect the utilization of ultra‐high field MR. In this work, we present a method to generate a subject‐specific body model from a single T1‐weighted dataset for personalized local SAR prediction in PTx neuroimaging at 7T. Methods: Multi‐contrast data were acquired at 7T (N = 10) to establish ground truth segmentations in eight tissue types. A 2.5D convolutional neural network was trained using the T1‐weighted data as input in a leave‐one‐out cross‐validation study. The segmentation accuracy was evaluated through local SAR simulations in a quadrature birdcage as well as a PTx coil model. Results: The network‐generated segmentations reached Dice coefficients of 86.7% ± 6.7% (mean ± SD) and showed to successfully address the severe intensity bias and contrast variations typical to 7T. Errors in peak local SAR obtained were below 3.0% in the quadrature birdcage. Results obtained in the PTx configuration indicated that a safety margin of 6.3% ensures conservative local SAR estimates in 95% of the random RF shims, compared to an average overestimation of 34% in the generic "one‐size‐fits‐all" approach. Conclusion: A subject‐specific body model can be automatically generated from a single T1‐weighted dataset by means of deep learning, providing the necessary inputs for accurate and personalized local SAR predictions in PTx neuroimaging at 7T. [ABSTRACT FROM AUTHOR]

Voxel-based binder jetting is explored for 3D printing ferromagnetic passive shims for magnetic resonance imaging (MRI). The resulting shims demonstrate promising capabilities in generating specific magnetic field distributions and showcasing minimal dimensional inaccuracies, enabling shim voxels to be at least 25 times smaller than previously reported. Passive shims 3D printed this way can potentially improve the performance of MRI acquisitions. [Display omitted] • Binder-jetting 3D printing corrects B 0 in MRI with ferromagnetic ink deposition. • Printed shims generate magnetic fields corresponding to 2nd-order SHE terms. • The electrically insulating ink eliminates eddy currents and heating risk. Magnetic Resonance Imaging (MRI) often encounters image quality degradation due to magnetic field inhomogeneities. Conventional passive shimming techniques involve the manual placement of discrete magnetic materials, imposing limitations on correcting complex inhomogeneities. To overcome this, we propose a novel 3D printing method utilizing binder jetting technology to enable precise deposition of a continuous range of concentrations of ferromagnetic ink. This approach grants complete control of the magnitude of the magnetic moment within the passive shim enabling tailored corrections of B 0 field inhomogeneities. By optimizing the magnetic field distribution using linear programming and an in-house written Computer-Aided Design (CAD) generation software, we printed shims with promising results in generating low spherical harmonic corrections. Experimental evaluations demonstrate feasibility of these 3D printed passive shims to induce target magnetic fields corresponding to second-order spherical harmonic, as evidenced by acquired B 0 maps. The electrically insulating properties of the printed shims eliminate the risk of eddy currents and heating, thus ensuring safety. The dimensional fabrication accuracy of the printed shims surpasses previous methods, enabling more precise and localized correction of subject-specific inhomogeneities. The findings highlight the potential of binder-jetted 3D printed passive shims in MRI shimming as a versatile and efficient solution for fabricating passive shims, with the potential to enhance the quality of MRI imaging while also being applicable to other types of Magnetic Resonance systems. [ABSTRACT FROM AUTHOR]

Indonesia is among the countries affected by the coronavirus disease 2019 (COVID-19) pandemic, and DKI Jakarta Province recorded the highest number of deaths. This study aimed to analyze the excess mortality across five administrative cities in Jakarta stratified by gender to assess the pandemic impact on mortality. The monthly mortality data from January 2018 to December 2020 was obtained through government sources. This data helped to measure excess mortality by estimating the baseline mortality had the COVID-19 pandemic not occurred. The analysis used a linear mixed model because of its ease and flexibility in forecasting subject-specific mortality. The results showed 13,507 or 35% excess deaths in Jakarta [95% CI: 11,636 to 15,236] between June and December 2020. The excess numbers were found relatively higher among men than women. Furthermore, Jakarta has underreported the COVID-19 deaths at least seven times higher than the reported number of confirmed deaths. [ABSTRACT FROM AUTHOR]

Computational models of the brain have become the gold standard in biomechanics to understand, predict, and mitigate traumatic brain injuries. Many models have been created and evaluated with limited experimental data and without accounting for subject-specific morphometry of the specimens in the dataset. Recent advancements in the measurement of brain motion using sonomicrometry allow for a comprehensive evaluation of brain model biofidelity using a high-rate, rotational brain motion dataset. In this study, four methods were used to determine the best technique to compare nodal displacement to experimental brain motion, including a new morphing method to match subject-specific inner skull geometry. Three finite element brain models were evaluated in this study: the isotropic GHBMC and SIMon models, as well as an anisotropic model with explicitly embedded axons (UVA-EAM). Using a weighted cross-correlation score (between 0 and 1), the anisotropic model yielded the highest average scores across specimens and loading conditions ranging from 0.53 to 0.63, followed by the isotropic GHBMC with average scores ranging from 0.46 to 0.58, and then the SIMon model with average scores ranging from 0.36 to 0.51. The choice of comparison method did not significantly affect the cross-correlation score, and differences of global strain up to 0.1 were found for the morphed geometry relative to baseline models. The morphed or scaled geometry is recommended when evaluating computational brain models to capture the subject-specific skull geometry of the experimental specimens. [ABSTRACT FROM AUTHOR]

Gait retraining to reduce knee loading has been proposed as a conservative treatment option for early-stage knee osteoarthritis. Mounting evidence suggests that a subject-specific approach may be most effective for ensuring consistent knee loading reductions across all individuals within a population. However, it is currently unclear how to determine the required gait modification dosage selection type and amount to both reduce knee loading and satisfy individual preferences. To overcome this challenge, we introduce a novel, mapping-based dosage selection approach to systematically determine multi-parameter gait modifications to reduce knee loading while maintaining individual user preference. In this approach, individuals first explore different dosages of multi-parameter gait modifications, and then a resulting visual map is displayed with a subject-specific dosage selection zone for the target knee loading reduction. Subjects then self-select a preferred gait within their dosage selection zone. To evaluate the feasibility of this approach, fifteen healthy subjects and one knee OA patient performed walking trials on a treadmill involving various dosages of gait modifications to foot progression angle and step width. Subjects quickly selected the subject-specific gait modifications via mapping-based dosage selection during a single 6 min trial, which reduced the knee adduction moment by an average of 14.2%. Resulting subject-specific gait modifications varied, with 6 subjects selecting only toe-in, 5 subjects selecting both toe-in and increased step width, 2 subjects selecting only toe-out, 1 subject selecting both toe-out and increased step width and 1 subject selecting only increased step width. Average perceived exertion was “fairly light” (index was 10.5±2.2). The knee OA patient selected only toe-in and reduced the knee adduction moment by 12.8%. The presented mapping-based dosage selection approach could provide a systematic and practical means to determine subject-specific gait modifications while maintaining individual preferences.

Subject-specific mathematical models for prediction of physiological parameters such as blood volume, cardiac output, and blood pressure in response to hemorrhage have been developed. In silico studies using these models may provide an effective tool to generate pre-clinical safety evidence for medical devices and help reduce the size and scope of animal studies that are performed prior to initiation of human trials. To achieve such a goal, the credibility of the mathematical model must be established for the purpose of pre-clinical in silico testing. In this work, the credibility of a subject-specific mathematical model of blood volume kinetics intended to predict blood volume response to hemorrhage and fluid resuscitation during fluid therapy was evaluated. A workflow was used in which: (i) the foundational properties of the mathematical model such as structural identifiability were evaluated; (ii) practical identifiability was evaluated both pre- and post-calibration, with the pre-calibration results used to determine an optimal splitting of experimental data into calibration and validation datasets; (iii) uncertainty in model parameters and the experimental uncertainty were quantified for each subject; and (iv) the uncertainty was propagated through the blood volume kinetics model and its predictive capability was evaluated via validation tests. The mathematical model was found to be structurally identifiable. Pre-calibration identifiability analysis led to splitting the 180 min of time series data per subject into 50 and 130 min calibration and validation windows, respectively. The average root mean squared error of the mathematical model was 12.6% using the calibration window of (0 min, 50 min). Practical identifiability was established post-calibration after fixing one of the parameters to a nominal value. In the validation tests, 82 and 75% of the subject-specific mathematical models were able to correctly predict blood volume response when predictive capability was evaluated at 180 min and at the time when amount of infused fluid equals fluid loss. [ABSTRACT FROM AUTHOR]

Musculoskeletal models of the lumbar spine have been developed with varying levels of detail for a wide range of clinical applications. Providing consistency is ensured throughout the modelling approach, these models can be combined with other computational models and be used in predictive modelling studies to investigate bone health deterioration and the associated fracture risk. To provide precise physiological loading conditions for such predictive modelling studies, a new full-body musculoskeletal model including a detailed and consistent representation of the lower limbs and the lumbar spine was developed. The model was assessed against in vivo measurements from the literature for a range of spine movements representative of daily living activities. Comparison between model estimations and electromyography recordings was also made for a range of lifting tasks. This new musculoskeletal model will provide a comprehensive physiological mechanical environment for future predictive finite element modelling studies on bone structural adaptation. It is freely available on . [ABSTRACT FROM AUTHOR]

Background and objectives: Statistical shape modeling (SSM) based on computerized tomography (CT) datasets has enabled reasonably accurate reconstructions of subject-specific 3D bone morphology from one or two synchronous radiographs for clinical applications. Increasing the number of radiographic images may increase the reconstruction accuracy, but errors related to the temporal and spatial asynchronization of clinical alternating bi-plane fluoroscopy may also increase. The current study aimed to develop a new approach for subject-specific 3D knee shape reconstruction from multiple asynchronous fluoroscopy images from 2, 4, and 6 X-ray detector views using a CT-based SSM model; and to determine the optimum number of planar images for best accuracy via computer simulations and in vivo experiments.Methods: A CT-based SSM model of the knee was established from 60 training models in a healthy young Chinese male population. A new two-phase optimization approach for 3D subject-specific model reconstruction from multiple asynchronous clinical fluoroscopy images using the SSM was developed, and its performance was evaluated via computer simulation and in vivo experiments using one, two and three image pairs from an alternating bi-plane fluoroscope.Results: The computer simulation showed that subject-specific 3D shape reconstruction using three image pairs had the best accuracy with RMSE of 0.52 ± 0.09 and 0.63 ± 0.085 mm for the femur and tibia, respectively. The corresponding values for the in vivo study were 0.64 ± 0.084 and 0.69 ± 0.069 mm, respectively, which was significantly better than those using one image pair (0.81 ± 0.126 and 0.83 ± 0.108 mm). No significant differences existed between using two and three image pairs.Conclusion: A new two-phase optimization approach was developed for SSM-based 3D subject-specific knee model reconstructions using more than one asynchronous fluoroscopy image pair from widely available alternating bi-plane fluoroscopy systems in clinical settings. A CT-based SSM model of the knee was also developed for a healthy young Chinese male population. The new approach was found to have high mode reconstruction accuracy, and those for both two and three image pairs were much better than for a single image pair. Thus, two image pairs may be used when considering computational costs and radiation dosage. The new approach will be useful for generating patient-specific knee models for clinical applications using multiple asynchronous images from alternating bi-plane fluoroscopy widely available in clinical settings. The current SSM model will serve as a basis for further inclusion of training models with a wider range of sizes and morphological features for broader applications.

Subject-specific mathematical models for prediction of physiological parameters such as blood volume, cardiac output, and blood pressure in response to hemorrhage have been developed. In silico studies using these models may provide an effective tool to generate pre-clinical safety evidence for medical devices and help reduce the size and scope of animal studies that are performed prior to initiation of human trials. To achieve such a goal, the credibility of the mathematical model must be established for the purpose of pre-clinical in silico testing. In this work, the credibility of a subject-specific mathematical model of blood volume kinetics intended to predict blood volume response to hemorrhage and fluid resuscitation during fluid therapy was evaluated. A workflow was used in which: (i) the foundational properties of the mathematical model such as structural identifiability were evaluated; (ii) practical identifiability was evaluated both pre- and post-calibration, with the pre-calibration results used to determine an optimal splitting of experimental data into calibration and validation datasets; (iii) uncertainty in model parameters and the experimental uncertainty were quantified for each subject; and (iv) the uncertainty was propagated through the blood volume kinetics model and its predictive capability was evaluated via validation tests. The mathematical model was found to be structurally identifiable. Pre-calibration identifiability analysis led to splitting the 180 min of time series data per subject into 50 and 130 min calibration and validation windows, respectively. The average root mean squared error of the mathematical model was 12.6% using the calibration window of (0 min, 50 min). Practical identifiability was established post-calibration after fixing one of the parameters to a nominal value. In the validation tests, 82 and 75% of the subject-specific mathematical models were able to correctly predict blood volume response when predictive capability was evaluated at 180 min and at the time when amount of infused fluid equals fluid loss.

The P300-based spelling system is one of the most popular brain–computer interface applications. Its success largely depends on performance, including the information transmission rate (ITR) and detection rate (i.e., accuracy). To achieve good performance, we proposed a multiscale convolutional neural network (MS-CNN) model that consists of seven layers. First, an upfront data set was used to train the MS-CNN, aiming to obtain a subject-unspecific model (universal model) for P300 detection. Second, this universal model was adapted by a portion of data derived from a subject to update the model to obtain a subject-specific model by incorporating a transfer learning technique. We applied the proposed model in the brain–computer interface (BCI) Controlled Robot Contest at the 2019 World Robot Conference, and our performance was the best among the teams in the contest. In the contest, ten healthy young subjects were randomly assigned by the contest committee to assess the model. Our model achieved the best P300 detection performance (higher accuracy with less repetition time). The ITR for the subject-unspecific case was 13.49 bits/min, while the ITR for the subject-specific case was 12.13 bits/min when the repetitions were fewer than six. It is believed that our method may pave a promising path for taking a further step toward efficient implementation of the P300-based spelling system. [ABSTRACT FROM AUTHOR]

Individuals with diabetes are at a higher risk of developing foot ulcers. To better understand internal soft tissue loading and potential treatment options, subject-specific finite element (FE) foot models have been used. However, existing models typically lack subject-specific soft tissue material properties and only utilize subject-specific anatomy. Therefore, this study determined subject-specific hindfoot soft tissue material properties from one non-diabetic and one diabetic subject using inverse FE analysis. Each subject underwent cyclic MRI experiments to simulate physiological gait and to obtain compressive force and three-dimensional soft tissue imaging data at 16 phases along the loading–unloading cycles. The FE models consisted of rigid bones and nearly-incompressible first-order Ogden hyperelastic skin, fat, and muscle (resulting in six independent material parameters). Then, calcaneus and loading platen kinematics were computed from imaging data and prescribed to the FE model. Two analyses were performed for each subject. First, the skin, fat, and muscle layers were lumped into a single generic soft tissue material and optimized to the platen force. Second, the skin, fat, and muscle material properties were individually determined by simultaneously optimizing for platen force, muscle vertical displacement, and skin mediolateral bulging. Our results indicated that compared to the individual without diabetes, the individual with diabetes had stiffer generic soft tissue behavior at high strain and that the only substantially stiffer multi-material layer was fat tissue. Thus, we suggest that this protocol serves as a guideline for exploring differences in non-diabetic and diabetic soft tissue material properties in a larger population. [ABSTRACT FROM AUTHOR]

The objective of this paper is to quantitatively evaluate the effects of rotator cuff tear propagation on glenohumeral joint stability in a previously constructed and validated finite element shoulder model. Rotator cuff tears with a sequence of increasing sizes were created from the anterior portion of the supraspinatus osseous insertion site and propagated posteriorly through the infraspinatus tendon until a complete tear extended through the entire teres minor tendon. Finite element simulations were performed in the same physiological loading and boundary conditions as in the original model. A novel integrative stability index was proposed and used for quantitative analysis of the simulated results. By defining the healthy condition as the baseline (100%), the stability index decreased slightly with small tear sizes but declined suddenly after half tear of the infraspinatus accompanied by a complete tear of the supraspinatus tendon until the full tear condition, when the index reached 0.41%. These results confirm the clinical and cadaveric findings that glenohumeral joint stability generally decreases as the size of the rotator cuff tear increases and that the critical tear size which leads to the loss of normal shoulder biomechanics was half tear of the infraspinatus accompanied by a complete tear of the supraspinatus tendon. It is concluded that the finite element shoulder model and the proposed novel stability ratio can accurately predict shoulder biomechanics in the investigated rotator cuff condition. Both the model and ratio may have the potential to be used to improve diagnostic and therapeutic strategies for clinicians.

The body-centric wireless channel characterization mostly utilizes whole body models. However, localized channels for body parts consistently interacting with the wireless device have their own importance. This paper attempts to characterize the hand palm local channel through experimental measurements at three millimeter-wave frequency bands of 27-28 GHz, 29-30 GHz, and 31-32 GHz. Five human subjects are used in this study. Net body loss is found to be 3dB for different subjects with subject-specific and varying palm shape size is found to be the primary affecting source. The repeatability of the on-body propagation measurements is found to be within 10% of variance.

Intellectualists claim that knowing how to do something is a matter of knowing, for some w, that w is a way to do that thing. However, standard accounts fail to account for the way that knowing how sometimes seems to require ability (although at other times does not). I argue that the way to make sense of this situation is via a 'subject-specific' intellectualism according to which knowing how to do something is a matter of knowing that w is a way for some relevant person to do that thing, but who the relevant person is can change from context to context. If it is the utterer themselves, then knowing how will require ability, but otherwise it will not. [ABSTRACT FROM AUTHOR]

Biomechanical models of the knee joint allow the development of accurate procedures as well as novel devices to restore the joint natural motion. They are also used within musculoskeletal models to perform clinical gait analysis on patients. Among relevant knee models in the literature, the anatomy-based spatial parallel mechanisms represent the joint motion using rigid links for the ligaments' isometric fibres and point contacts for the articular surfaces. To customize analyses, therapies and devices, there is the need to define subject-specific models, but relevant procedures and their accuracy are still questioned. A procedure is here proposed and validated to define a customized knee model based on a spatial parallel mechanism. Computed tomography, magnetic resonance and 3D-video-fluoroscopy were performed on a healthy volunteer to define the personalized model geometry. The model was then validated by comparing the measured and the replicated joint motion. The model showed mean absolute difference and standard deviations in translations and rotations, respectively of 0.98 ± 0.40 mm and 0.68 ± 0.29 ° for the tibia–femur motion, and of 0.77 ± 0.15 mm and 2.09 ± 0.69 ° for the patella–femur motion. These results show that accurate personalized spatial models of knee kinematics can be obtained from in-vivo imaging. [ABSTRACT FROM AUTHOR]

There has been a lot of development in realistic muscle modeling based on finite elements in the last decade. However, one of the challenges in this area remains to be custom or specimen-specific meshing of the relevant muscle, mainly due to the scarcity of the DT-MRI infrastructure and expertise. The purpose of this work is to capitalize on the Bayesian regularization backpropagation based artificial neural networks, to transform digital photographic imagery into a finite element mesh, and the accompanying internal fiber orientation data. A gastrocnemius muscle was extracted from a frog and utilized to conduct the proposed work. Due to the highly nonlinear nature of the resulting finite element model, from both metric and material considerations, as well as the limited suitability of available elements for meshing in this case, a custom hexahedral-type mesh topology was selected for the meshing procedure. Results indicate a very good agreement between the geometries of the sample muscle and its mesh. Furthermore, fiber orientations were approximated as following the fusiform geometry of the muscle. The proposed framework can be used to overcome the pre-processing requirements of subject-specific muscles, including hexahedral-type meshing and extraction of internal fiber orientation data. [ABSTRACT FROM AUTHOR]

Cerebral palsy is a complex neuromuscular disorder that affects the sufferers in multiple different ways. Neuromusculoskeletal models are promising tools that can be used to plan patient-specific treatments for cerebral palsy. However, current neuromusculoskeletal models are typically scaled from generic adult templates that poorly represent paediatric populations. Furthermore, muscle activations are commonly computed via optimisation methods, which may not reproduce co-contraction observed in cerebral palsy. Alternatively, calibrated EMG-informed approaches within OpenSim can capture pathology-related muscle activation abnormalities, possibly enabling more feasible estimations of muscle and joint contact forces. Two identical twin brothers, aged 13, one with unilateral cerebral palsy and the other typically developing, were enrolled in the study. Four neuromusculoskeletal models with increasing subject-specificity were built in OpenSim and CEINMS combining literature findings, experimental motion capture, EMG and MR data for both participants. The physiological and biomechanical validity of each model was assessed by quantifying its ability to track experimental joint moments and muscle excitations. All developed models accurately tracked external joint moments; however EMG-informed models better tracked muscle excitations compared to neural solutions generated by static optimisation. Calibrating muscle-tendon unit parameters with EMG data allowed for more physiologically plausible joint contact forces estimates. Further scaling the maximal isometric force of muscles with MR-derived muscle volumes did not affect model predictions. Given their ability to identify atypical joint contact forces profiles and accurately reproduce experimental data, calibrated EMG-informed models should be preferred over generic models using optimisation methods in informing the management of cerebral palsy. • Personalisation of musculoskeletal models is important in studying cerebral palsy. • Electromyography data to inform models allow to capture atypical muscle activity. • Calibration of muscle-tendon unit parameters ensures physiological force estimates. • The use of medical images to scale muscle parameters may not improve model outcomes. [ABSTRACT FROM AUTHOR]

Due to lack of reference validation data, the common strategy in characterizing adolescent idiopathic scoliosis (AIS) by musculoskeletal modelling approach consists in adapting structure and parameters of validated body models of adult individuals with physiological alignments. Until now, only static postures have been replicated and investigated in AIS subjects. When aiming to simulate trunk motion, two critical factors need consideration: how distributing movement along the vertebral motion levels (lumbar spine rhythm), and if neglecting or accounting for the contribution of the stiffness of the motion segments (disc stiffness). The present study investigates the effect of three different lumbar spine rhythms and absence/presence of disc stiffness on trunk muscle imbalance in the lumbar region and on intervertebral lateral shear at different levels of the thoracolumbar/lumbar scoliotic curve, during simulated trunk motions in the three anatomical planes (flexion/extension, lateral bending, and axial rotation). A spine model with articulated ribcage previously developed in AnyBody software and adapted to replicate the spinal alignment in AIS subjects is employed. An existing dataset of 100 subjects with mild and moderate scoliosis is exploited. The results pointed out the significant impact of lumbar spine rhythm configuration and disc stiffness on changes in the evaluated outputs, as well as a relationship with scoliosis severity. Unfortunately, no optimal settings can be identified due to lack of reference validation data. According to that, extreme caution is recommended when aiming to adapt models of adult individuals with physiological alignments to adolescent subjects with scoliotic deformity. [ABSTRACT FROM AUTHOR]

This study used an optimization procedure to evaluate an 8-segment torque-driven subject-specific computer simulation model of the takeoff phase in running jumps for height. Kinetic and kinematic data were obtained on a running jump performed by an elite male high jumper. Torque generator activation timings were varied to minimize the difference between simulation and performance in terms of kinematic and kinetic variables subject to constraints on the joint angles at takeoff to ensure that joints remained within their anatomical ranges of motion. A percentage difference of 6.6% between simulation and recorded performance was obtained. Maximizing the height reached by the mass center during the flight phase by varying torque generator activation timings resulted in a credible height increase of 90 mm compared with the matching simulation. These two results imply that the model is sufficiently complex and has appropriate strength parameters to give realistic simulations of running jumps for height. [ABSTRACT FROM AUTHOR]

A modification to an existing mathematical model is described, which permits the determination of subject-specific inertia parameters for wobbling and rigid masses of female body segments. The model comprises segment-specific soft tissue, bone, and lung components. A total of 59 geometric solids (40 soft tissue, 17 bone, 2 lung) were used to represent the body components. Ninety-five anthropometric measurements were collected from 7 female participants and were used to develop and evaluate the model. The success of the model is evaluated using predicted mass and mass distribution. The overall absolute accuracy in predicted whole body mass was better than 3.0%, with a maximum error of 4.9%. The appropriateness of the cadaver-based density values used in the model is addressed and the accuracy of the component inertia model in relation to uniform density models is discussed. The model offers a novel approach for determining component inertia parameters, which have been used successfully in a wobbling mass model to produce realistic kinetic analyses of drop-landings. [ABSTRACT FROM AUTHOR]

Obesity has been associated to increase the risk of low back disorders. Previous musculoskeletal models simulating the effect of body weight on intervertebral joint loads have assumed identical body postures for obese and normal-weight individuals during a given physical activity. Our recent kinematic-measurement studies, however, indicate that obese individuals adapt different body postures (segmental orientations) than normal-weight ones when performing load-reaching activities. The present study, therefore, used a subject- and kinematics-specific musculoskeletal modeling approach to compare spinal loads of nine normal-weight and nine obese individuals each performing twelve static two-handed load-reaching activities at different hand heights, anterior distances, and asymmetry angles (total of 12 tasks × 18 subjects = 216 model simulations). Each model incorporated personalized muscle architectures, body mass distributions, and full-body kinematics for each subject and task. Results indicated that even when accounting for subject-specific body kinematics obese individuals experienced significantly larger (by ∼38% in average) L5-S1 compression (2305 ± 468 N versus 1674 ± 337 N) and shear (508 ± 111 N versus 705 ± 150 N) loads during all reaching activities (p < 0.05 for all hand positions). This average difference of ∼38% was similar to the results obtained from previous modeling investigations that neglected kinematics differences between the two weight groups. Moreover, there was no significant interaction effect between body weight and hand position on the spinal loads; indicating that the effect of body weight on L5-S1 loads was not dependent on the position of hands. Postural differences alone appear, hence, ineffective in compensating the greater spinal loads that obese people experience during reaching activities. [ABSTRACT FROM AUTHOR]

Cable-driven devices for hands allow compact and lightweight design that could provide various functional movements. However, for many patients post-stroke, cable-driven devices produce nonphysiologic movements, such as metacarpophalangeal joint hyperextension, due to their abnormal passive joint impedance. In this study, we developed a novel bio-inspired device mimicking the anatomy of the extensor mechanism of the human finger, which can be tuned for individuals to provide ‘subject-specific’ assistance to achieve physiological movement patterns. We first evaluated the proposed design via mathematical modeling and computer simulation. Its performance was then tested experimentally with twenty-four subjects, including six healthy and eighteen chronic stroke survivors. We determined the loading condition of the device from the experimental identification of passive joint impedance of each subject before device use. Our results showed that the proposed design could achieve improved spatiotemporal coordination of finger movements compared to conventional cable-driven design by providing ‘subject-specific’ assistance based on identified passive stiffness values of each subject. We also identified a significant (negative) correlation between the metacarpophalangeal joint stiffness and the intrinsic exotendon loading level across subjects. The proposed system can restore normal movement patterns for patients with different types of impairments, which were previously found important in improving rehabilitative outcomes. [ABSTRACT FROM AUTHOR]

Computational knee models that replicate the joint motion are important tools to discern difficult-to-measure functional joint biomechanics. Numerous knee kinematic models of different complexity, with either generic or subject-specific anatomy, have been presented and used to predict three-dimensional tibiofemoral (TFJ) and patellofemoral (PFJ) joint kinematics of cadavers or healthy adults, but not pediatric populations. The aims of this study were: (i) to develop subject-specific TFJ and PFJ kinematic models, with TFJ models having either rigid or extensible ligament constraints, for eight healthy pediatric participants and (ii) to validate the estimated joint and ligament kinematics against in vivo kinematics measured from magnetic resonance imaging (MRI) at four TFJ flexion angles. Three different TFJ models were created from MRIs and used to solve the TFJ kinematics: (i) 5-rigid-link parallel mechanism with rigid surface contact and isometric anterior cruciate (ACL), posterior cruciate (PCL) and medial collateral (MCL) ligaments (Δ L null ) , (ii) 6-link parallel mechanism with minimized ACL, PCL, MCL and lateral collateral ligament (LCL) length changes (Δ L min ) and (iii) 6-link parallel mechanism with prescribed ACL, PCL, MCL and LCL length variations (Δ L match ). Each model's geometrical parameters were optimized using a Multiple Objective Particle Swarm algorithm. When compared to MRI-measured data, Δ L null and Δ L match performed the best, with average root mean square errors below 6.93° and 4.23 mm for TFJ and PFJ angles and displacements, respectively, and below 2.01 mm for ligament lengths (<4.32% ligament strain). Therefore, within these error ranges, Δ L null and Δ L match can be used to estimate three-dimensional pediatric TFJ, PFJ and ligament kinematics and can be incorporated into lower-limb models to estimate joint kinematics and kinetics during dynamic tasks. [ABSTRACT FROM AUTHOR]

Robotic therapy enables mass practice of complex hand movements after stroke, but current devices generally enforce patients to reproduce prescribed kinematic patterns using rigid actuators, without considering individuals’ unique impairment characteristics, thereby reducing their efficacy. In this paper, we tested the feasibility of a novel, theory-based “biomimetic” approach to restoring mechanics of complex hand tasks with subject-specific assistance patterns. Twelve chronic stroke survivors performed two simulated functional tasks: hand open and simulated pinch task (distal pad press). Assistance was provided by non-restraining actuators (exotendons) that counteracted ‘subject-specific’ impairments, identified during unassisted task performance. There was no constraint of movement to predefined patterns. Assistance patterns required to complete tasks were significantly different across subjects, reflecting high variability in impairment and required assistance patterns. For hand open, range of motion and interjoint coordination were significantly improved for severely impaired patients, while movement quality was enhanced (reduction in jerk) for those less impaired. For simulated pinch, subject-specific assistance restored task mechanics before injury, as patients were able to direct fingertip force toward the direction normal to surface; angular deviation reduced from 16.8°±10.4° to 3.7°±2.6°. Notably, electromyography data confirmed that subjects maintained an effort level under assistance comparable to unassisted conditions. The proposed method could lead to a novel paradigm for hand rehabilitation that restores complex task mechanics with a subject-specific assistance reflecting individual impairment characteristics while promoting subjects’ participation. [ABSTRACT FROM AUTHOR]

We hypothesized that minimally invasive injections of a softening agent at strategic locations in stiff myocardium could de-stiffen the left ventricle (LV) globally. Physics-based finite element models of the LV were created from LV echocardiography images and pressures recorded during experiments in four swine. Results confirmed animal models of LV softening by systemic agents. Regional de-stiffening of myocardium led to global de-stiffening of LV. The mathematical set up was used to design LV global de-stiffening by regional softening of myocardium. At an end diastolic pressure of 23 mmHg, when 8 ml of the free wall was covered by intramyocardial injections, end diastolic volume (EDV) increased by 15.0%, whereas an increase up to 11 ml due to intramyocardial injections in the septum and free wall led to a 26.0% increase in EDV. Although the endocardial intramyocardial injections occupied a lower LV wall volume, they led to an EDV (44 ml) that was equal compared to intramyocardial injections in the mid-wall (44 ml) and larger compared to intramyocardial injections in the epicardium (41 ml). Using an in silico set up, sites of regional myocardium de-stiffening could be planned in order to globally soften overly stiff LV in heart failure with preserved ejection fraction. This novel treatment is built on subject-specific data. Hypothesis-testing of these simulation findings in animal models is warranted. [ABSTRACT FROM AUTHOR]

The authors numerically investigated the correlation between airway skeletons of severe asthmatic human subjects and predicted aerosol deposition to shed light on the effect of environmental factors on asthma risk. We hypothesized that there are asthmatic subjects whose airway skeletal structure can expose the subject to a risk of higher local aerosol deposition compared to subjects with a more common/normal branching pattern. From a population of severe asthmatics studied at total lung capacity via computed tomography we randomly selected 8 subjects whose Forced Expiratory Volume in 1 s, percent predicted fell below 45% predicted. To simulate aerosol motion in the human lungs, we employed in-house three-dimensional eddy-resolving computational fluid dynamics and particle tracking models utilizing 3 of the 8 severe asthmatic subjects. One of the 3 subjects was found to have a distinct, localized airway narrowing chosen for further investigation. In the simulation, we controlled flow rate and luminal area, i.e., Reynolds and Stokes numbers, in each branch of the computed tomography-derived airway skeletons. We found a distinct enhancement of aerosol deposition associated with the narrowed branches of one subject even when the luminal area was numerically adjusted from its narrowed state to that of a non-asthmatic subject. The branching angle, freed of luminal narrowing persisted in demonstrating a marginally significant increase in local particle deposition compared with the subjects without the initial constriction. These results demonstrate the possibility that inherent airway structure may influence localized constriction found in severe asthmatics. [ABSTRACT FROM AUTHOR]

• We developed a complete and coherent musculoskeletal model of the entire human spine and studied the intervertebral disc compression forces. • Intradiscal pressures estimated from predicted compressive forces were generally in close agreement with previous measurements of spinal loads both quantitatively and qualitatively. • We found that compressive forces at the trunk discs increased during trunk lateral bending and axial rotation of the trunk. • During trunk flexion, compressive forces increased in the thoracolumbar and lumbar regions and slightly decreased at the middle thoracic discs. • The model predicted increased compression forces in neck flexion, lateral bending, and axial rotation, and decreased forces in neck extension. Although in vivo spinal loads have been previously measured, existing data are limited to certain lumbar and thoracic levels. A detailed investigation of spinal loads would assist with injury prevention and implant design but is unavailable. In this study, we developed a complete and coherent musculoskeletal model of the entire human spine and studied the intervertebral disc compression forces for physiological movements on three anatomical planes. This model incorporates the individual vertebrae at the cervical, thoracic, and lumbar regions, a flexible ribcage, and complete muscle anatomy. Intradiscal pressures were estimated from predicted compressive forces, and these were generally in close agreement with previously measured data. We found that compressive forces at the trunk discs increased during trunk lateral bending and axial rotation of the trunk. During flexion, compressive forces increased in the thoracolumbar and lumbar regions and slightly decreased at the middle thoracic discs. In extension, the forces generally decreased at the thoracolumbar and lumbar discs whereas they slightly increased at the upper and middle thoracic discs. Furthermore, similar to a previous biomechanical model of the cervical spine, our model predicted increased compression forces in neck flexion, lateral bending, and axial rotation, and decreased forces in neck extension. [ABSTRACT FROM AUTHOR]

Abstract Performance in the flight phase of springboard diving is limited by the amounts of linear and angular momentum generated during the takeoff phase. A planar 8-segment torque-driven simulation model combined with a springboard model was used to investigate optimum takeoff technique for maximising rotation in forward dives from the one metre springboard. Optimisations were run by varying the torque activation parameters to maximise forward rotation potential (angular momentum × flight time) while allowing for movement constraints, anatomical constraints, and execution variability. With a constraint to ensure realistic board clearance and anatomical constraints to prevent joint hyperextension, the optimised simulation produced 24% more rotation potential than a simulation matching a 2½ somersault piked dive. When 2 ms perturbations to the torque onset timings were included for the ankle, knee and hip torques within the optimisation process, the model was only able to produce 87% of the rotation potential achieved in the matching simulation. This implies that a pre-planned technique cannot produce a sufficiently good takeoff and that adjustments must be made during takeoff. When the initial onset timings of the torque generators were unperturbed and 10 ms perturbations were introduced into the torque onset timings in the board recoil phase, the optimisation produced 8% more rotation potential than the matching simulation. The optimised simulation had more hip flexion and less shoulder extension at takeoff than the matching simulation. This study illustrates the difficulty of including movement variability within performance optimisation when the movement duration is sufficiently long to allow feedback corrections. [ABSTRACT FROM AUTHOR]

To account for proximal femoral deformities in children with cerebral palsy (CP), subject-specific musculoskeletal models are needed. Non-rigid deformation (NRD) deforms generic onto personalized bone geometry and thereby transforms the muscle points. The goal of this study was to determine to what extent the models and simulation outcomes in CP patients differ when including subject-specific detail using NRD or Magnetic Resonance Imaging (MRI)-based models. The NRD models slightly overestimated hip contact forces compared to MRI models and differences in muscle point positions and moment arm lengths (MALs) remained, although differences were smaller than for the generic model. [ABSTRACT FROM AUTHOR]

Optimizing the geometric complexity of musculoskeletal models is important for reliable yet feasible estimation of joint biomechanics. This study investigated the effects of subject-specific model geometry on hip joint reaction forces (JRFs) and muscle forces in patients with developmental dysplasia of the hip (DDH) and healthy controls. For nine DDH and nine control subjects, three models were created with increasingly subject-specific pelvis geometry, hip joint center locations and muscle attachments. Hip JRFs and muscle forces during a gait cycle were compared among the models. For DDH subjects, resultant JRFs from highly specific models including subject-specific pelvis geometry, joint locations and muscle attachments were not significantly different compared to models using generic geometry in early stance, but were significantly higher in late stance (p = 0.03). Estimates from moderately specific models using CT-informed scaling of generic pelvis geometry were not significantly different from low specificity models using generic geometry scaled with skin markers. For controls, resultant JRFs in early stance from highly specific models were significantly lower than moderate and low specificity models (p ≤ 0.02) with no significant differences in late stance. Inter-model JRF differences were larger for DDH subjects than controls. Inter-model differences for JRF components and muscle forces were similar to resultant JRFs. Incorporating subject-specific pelvis geometry significantly affects JRF and muscle force estimates in both DDH and control groups, which may be especially important for reliable estimation of pathomechanics in dysplastic hips. [ABSTRACT FROM AUTHOR]

Mixed models estimated by maximum likelihood and marginal models estimated by generalized estimating equations are the standard methods for the analysis of longitudinal data. However, their use is highly debated when attrition may be due to death. While some authors consider that mixed model estimates are interpretable only in an immortal cohort, we show that their subject-specific interpretation still holds in the population currently alive, but their population-averaged interpretation is valid only in the immortal cohort. We propose an approximation of the population-averaged mean among the population alive that highlights the difference with the population-averaged mean in the immortal cohort. The interpretation of ML estimates of mixed models and joint models for the marker and the time-to-death as well as unweighted and weighted GEE of marginal models is then illustrated in a simulation study and in an application regarding cognitive decline in the elderly. [ABSTRACT FROM AUTHOR]

Rotator cuff tendons undergo degeneration with age, which could have an impact on tear propagation. The objective of this study was to predict tear propagation for different levels of tissue degeneration using an experimentally validated finite element model of a supraspinatus tendon. It was hypothesized that greater amounts of degeneration will result in tear propagation at lower loads than tendons with less degeneration. Using a previously-validated computational model of supraspinatus tendon, 1-cm tears were introduced in the anterior, middle, and posterior thirds of the tendon. Cohesive elements were assigned subject-specific failure properties to model tear propagation, and tendon degeneration ranging from "minimal" to "severe" was modeled by modifying its mechanical properties. Tears in tendons with severe degeneration required the smallest loads to propagate (122-207 N). Posterior tears required greater loads compared to middle and anterior tears at all levels of degeneration. Stress and strain required for tear propagation decreased substantially with degeneration, ranging from 8.5 MPa and 32.6% strain for minimal degeneration and 0.6 MPa and 4.5% strain for severe degeneration. Overall, this work indicates that greater amounts of tendon degeneration lead to greater risk of tear propagation, supporting the need for early detection and treatment of rotator cuff tears. [ABSTRACT FROM AUTHOR]

An objective method to detect muscle fatigue-related kinematic changes may reduce workplace injuries. However, heterogeneous responses to muscle fatigue suggest that subject-specific analyses are necessary. The objectives of this study were to: (1) determine if wearable inertial measurement units (IMUs) could be used in conjunction with a spine motion composite index (SMCI) to quantify subject-specific changes in spine kinematics during a repetitive spine flexion-extension (FE) task; and (2) determine if the SMCI was correlated with measures of global trunk muscle fatigue. Spine kinematics were measured using wearable IMUs in 10 healthy adults during a baseline set followed by 10 sets of 50 spine FE repetitions. After each set, two fatigue measures were collected: perceived level of fatigue using a visual analogue scale (VAS), and maximal lift strength. SMCIs incorporating 10 kinematic variables from 2 IMUs (pelvis and T8 vertebrae) were calculated and used to quantify subject-specific changes in movement. A main effect of set was observed (F (1.7, 15.32) = 10.42, p = 0.002), where the SMCI became significantly greater than set 1 starting at set 4. Significant correlations were observed between the SMCI and both fatigue VAS and maximal lift strength at the individual and study level. These findings support the use of wearable IMUs to detect subject-specific changes in spine motion associated with muscle fatigue.

Biomechanical models of the knee joint allow the development of accurate procedures as well as novel devices to restore the joint natural motion. They are also used within musculoskeletal models to perform clinical gait analysis on patients. Among relevant knee models in the literature, the anatomy-based spatial parallel mechanisms represent the joint motion using rigid links for the ligaments’ isometric fibres and point contacts for the articular surfaces. To customize analyses, therapies and devices, there is the need to define subject-specific models, but relevant procedures and their accuracy are still questioned. A procedure is here proposed and validated to define a customized knee model based on a spatial parallel mechanism. Computed tomography, magnetic resonance and 3D-video-fluoroscopy were performed on a healthy volunteer to define the personalized model geometry. The model was then validated by comparing the measured and the replicated joint motion. The model showed mean absolute difference and standard deviations in translations and rotations, respectively of 0.98 ± 0.40 mm and 0.68 ± 0.29 ° for the tibia−femur motion, and of 0.77 ± 0.15 mm and 2.09 ± 0.69 ° for the patella−femur motion. These results show that accurate personalized spatial models of knee kinematics can be obtained from in-vivo imaging.

Predictive computational modeling has revolutionized classical engineering disciplines and is in the process of transforming cardiovascular research. This is particularly relevant for investigating emergent therapies for heart failure, which remains a leading cause of death globally. The creation of subject-specific biventricular computational cardiac models has been a long-term endeavor within the biomedical engineering community. Using high resolution (0.3 × 0.3 × 0.8 mm) ex vivo data, we constructed a precise fully subject-specific biventricular finite-element model of healthy and failing swine hearts. Each model includes fully subject-specific geometries, myofiber architecture and, in the case of the failing heart, fibrotic tissue distribution. Passive and active material properties are prescribed using hyperelastic strain energy functions that define a nearly incompressible, orthotropic material capable of contractile function. These materials were calibrated using a sophisticated multistep approach to match orthotropic tri-axial shear data as well as subject-specific hemodynamic ventricular targets for pressure and volume to ensure realistic cardiac function. Each mechanically beating heart is coupled with a lumped-parameter representation of the circulatory system, allowing for a closed-loop definition of cardiovascular flow. The circulatory model incorporates unidirectional fluid exchanges driven by pressure gradients of the model, which in turn are driven by the mechanically beating heart. This creates a computationally meaningful representation of the dynamic beating of the heart coupled with the circulatory system. Each model was calibrated using subject-specific experimental data and compared with independent in vivo strain data obtained from echocardiography. Our methods produced highly detailed representations of swine hearts that function mechanically in a remarkably similar manner to the in vivo subject-specific strains on a global and regional comparison. The degree of subject-specificity included in the models represents a milestone for modeling efforts that captures realism of the whole heart. This study establishes a foundation for future computational studies that can apply these validated methods to advance cardiac mechanics research.

Blast injuries are very common among soldiers deployed in politically unstable regions such as Afghanistan and Iraq, and also in a battle field anywhere in the world. Understanding the mechanics of interaction of blasts with the skin and bone at various parts of the human body is the key to designing effective personal protective equipment (PPE's) which can mitigate blast impacts. In the current work, subject-specific 3D computational models of the skin (with the three layers namely the epidermis, dermis and the hypodermis (muscles)) and bone sections from various parts of the human body (such as the elbow, finger, wrist, cheek bone, forehead, shin etc.) have been developed to study the effect of blast loading. Non-linear material properties have been adopted for the skin and stress impulses at the different skin layers and bone sections are estimated. To date, such an extensive study on the effect of blast loading on the human skin and bone has not been attempted. The results of this study would be indispensable for medical practitioners to understand the effect of blast trauma and plan effective post-traumatic surgical strategies, and also for developing better PPE designs for the military in the future.