Despite the advancement of cardiac imaging technologies, these have traditionally been limited to global geometrical measurements. Computational fluid dynamics (CFD) has emerged as a reliable tool that provides flow field information and other variables essential for the assessment of the cardiac function. Extensive studies have shown that vortex formation and propagation during the filling phase acts as a promising indicator for the diagnosis of the cardiac health condition. Proper setting of the boundary conditions is crucial in a CFD study as they are important determinants, that affect the simulation results. In this article, the effect of different transmitral velocity profiles (parabolic and uniform profile) on the vortex formation patterns during diastole was studied in a ventricle with dilated cardiomyopathy (DCM). The resulting vortex evolution pattern using the uniform inlet velocity profile agreed with that reported in the literature, which revealed an increase in thrombus risk in a ventricle with DCM. However the application of a parabolic velocity profile at the inlet yields a deviated vortical flow pattern and overestimates the propagation velocity of the vortex ring towards the apex of the ventricle. This study highlighted that uniform inlet velocity profile should be applied in the study of the filling dynamics in a left ventricle because it produces results closer to that observed experimentally.
Efforts to model the human upper respiratory system have undergone many phases. Geometrical proximity to the realistic shape has been the subject of many research projects. In this study, three different geometries of the trachea and main bronchus were modelled, which were reconstructed from computed tomography (CT) scan images. The geometrical variations were named realistic, simplified and oversimplified. Realistic refers to the lifelike image taken from digital imaging and communications in medicine format CT scan images, simplified refers to the reconstructed image based on natural images without realistic details pertaining to the rough surfaces, and oversimplified describes the straight wall geometry of the airway. The characteristics of steady state flows with different flow rates were investigated, simulating three varied physical activities and passing through each model. The results agree with previous studies where simplified models are sufficient for providing comparable results for airflow in human airways. This work further suggests that, under most exercise conditions, the idealised oversimplified model is not favourable for simulating either airflow regimes or airflow with particle depositions. However, in terms of immediate analysis for the prediction of abnormalities of various dimensions of human airways, the oversimplified techniques may be used.
In electromagnetic dosimetry, anatomical human models are commonly obtained by segmentation of magnetic resonance imaging or computed tomography scans. In this paper, a human head model extracted from thermal infrared images is examined in terms of its applicability to specific absorption rate (SAR) calculations. Since thermal scans are two-dimensional (2D) representation of surface temperature, this allows researchers to overcome the extensive computational demand associated with 3D simulation. The numerical calculations are performed using the finite-difference time-domain method with mesh sizes of 2 mm at 900 MHz plane wave irradiation. The power density of the incident plane wave is assumed to be 10 W/m(2). Computations were compared with a realistic anatomical head model. The results show that although there were marked differences in the local SAR distribution in the various tissues in the two models, the 1 g peak SAR values are approximately similar in the two models.
Retinal blood vessel detection and analysis play vital roles in early diagnosis and prevention of several diseases, such as hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. This paper presents an automated algorithm for retinal blood vessel segmentation. The proposed algorithm takes advantage of powerful image processing techniques such as contrast enhancement, filtration and thresholding for more efficient segmentation. To evaluate the performance of the proposed algorithm, experiments were conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm yields an accuracy rate of 96.5%, which is higher than the results achieved by other known algorithms.
In this paper, a gait event detection algorithm is presented that uses computer intelligence (fuzzy logic) to identify seven gait phases in walking gait. Two inertial measurement units and four force-sensitive resistors were used to obtain knee angle and foot pressure patterns, respectively. Fuzzy logic is used to address the complexity in distinguishing gait phases based on discrete events. A novel application of the seven-dimensional vector analysis method to estimate the amount of abnormalities detected was also investigated based on the two gait parameters. Experiments were carried out to validate the application of the two proposed algorithms to provide accurate feedback in rehabilitation. The algorithm responses were tested for two cases, normal and abnormal gait. The large amount of data required for reliable gait-phase detection necessitate the utilisation of computer methods to store and manage the data. Therefore, a database management system and an interactive graphical user interface were developed for the utilisation of the overall system in a clinical environment.
Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.
The stress shielding effect is an event in which the replacement implant limits the load transferred to bone and the ineffective stress in the vertebrae causes bony growth to cease. In the present study, a 3D finite element L4-L5 model was developed and subjected to a 1200 N compression preload. Five groups of muscle forces were applied on L4 under flexion-extension, lateral bending and axial rotation. Topology optimisation was employed for reducing the stress shielding effect by removing the ineffective material from the design domain. The optimised design was designed with polyaryletheretherketone (PEEK) titanium and cortical materials to encounter the shielding response. The stress responses show that the new design increased the stress magnitude by at least 17.10, 18.11 and 18.43% in 4 Nm of flexion-extension, lateral bending and axial rotation, respectively. In conclusion, the material factor did not significantly alter the stress magnitude, but volume was the key factor in reducing the stress shielding effect.
This study aims to investigate the influence of artery wall curvature on the anatomical assessment of stenosis severity and to identify a region of misinterpretation in the assessment of per cent area stenosis (AS) for functionally significant stenosis using fractional flow reserve (FFR) as standard. Five artery models of different per cent AS severity (70, 75, 80, 85 and 90%) were considered. For each per cent AS severity, the angle of curvature of the arterial wall varied from straight to an increasingly curved model (0°, 30°, 60°, 90° and 120°). Computational fluid dynamics was performed under transient physiologic hyperemic flow conditions to investigate the influence of artery wall curvature on the pressure drop and the FFR. The findings in this study may be useful in in vitro anatomical assessment of functionally significant stenosis. The FFR decreased with increasing stenosis severity for a given curvature of the artery wall. Moreover, a significant decrease in FFR was found between straight and curved models discussed for a given severity condition. These findings indicate that the curvature effect was included in the FFR assessment in contrast to minimum lumen area (MLA) or per cent AS assessment. The MLA or per cent AS assessment may lead to underestimation of stenosis severity. From this numerical study, an uncertainty region could be evaluated using the clinical FFR cutoff value of 0.8. This value was observed at 81.98 and 79.10% AS for arteries with curvature angles of 0° and 120° respectively. In conclusion, the curvature of the artery should not be neglected in in vitro anatomical assessment.
In the biomechanics field, material parameters calibration is significant for finite element (FE) model to ensure a legit estimation of biomechanical response. Determining an appropriate combination of calibration factors is challenging as each constitutive component responds differently. This study proposes a statistical factorial analysis approach using L16(4(5)) orthogonal array to evaluate material nonlinearity and applicable calibration factor of the intervertebral disc FE model in pure moment. The calibrated model exhibits improved agreement to the experimental findings for all directions. Appropriate combination of calibration parameter reduces the estimation gap to the experimental findings, ensuring agreeable biomechanical responses.
Glenoid perforation is not the intended consequence of the surgery and must be avoided. The analysis on biomechanical aspect of glenoid vault perforation remains unknown. The purpose of this study is to determine the impact of glenoid perforation towards stress distribution and micromotion at the interfaces. Eight glenoid implant models had been constructed with various size, number and type of fixation. A load of 750 N was applied to centre, superior-anterior and superior-posterior area. Implant perforation had minimal impact on stress distribution and micromotion at the interfaces. However, cement survival rate for implant without perforation was the highest with a difference of up to 37% compared to other perforated models. Besides that, implant fixation and high stresses at the implant had more of an impact on implant instability than implant perforation. As a conclusion, glenoid perforation did not influence the stress distribution and micromotion, but, it reduced cement survival rate and increase the stress critical volume.
Osteoarthritis (OA) is a commonly occurring cartilage degenerative disease. The end stage treatment is Total Knee Arthroplasty (TKA), which can be costly in terms of initial surgery, but also in terms of revision knee arthroplasty, which is quite often required. A novel conceptual knee implant has been proposed to function as a reducer of stress across the joint surface, to extend the period of time before TKA becomes necessary. The objective of this paper is to develop a computational model which can be used to assess the wear arising at the implant articulating surfaces. Experimental wear coefficients were determined from physical testing, the results of which were verified using a semi-analytical model. Experimental results were incorporated into an anatomically correct computational model of the knee and implant. The wear-rate predicted for the implant was 27.74 mm3 per million cycles (MC) and the wear depth predicted was 1.085 mm/MC. Whereas the wear-rate is comparable to that seen in conventional knee implants, the wear depth is significantly higher than for conventional knee prostheses, and indicates that, in order to be viable, wear-rates should be reduced in some way, perhaps by using low-wear polymers.
The Machine Learning Model (MLM) has garnered popularity in rehabilitation, ranging from developing algorithms in outcome prediction, prognostication, and training artificial intelligence. High-quality data plays a critical role in algorithm development. Limited studies have explored factors that may influence the MLM algorithm performance in predicting spasticity severity level. The objectives of this study were to train and validate a MLM algorithm for spasticity assessment and determine the algorithm's prediction performance in predicting ambiguous spasticity datasets. Forty-seven persons with central nervous system pathology that fulfilled the inclusion and exclusion criteria were recruited. Four biomechanical properties of spasticity were obtained using off-the-shelf wearable sensors. The data were analyzed individually, and ambiguous datasets were separated. The acceptable inertial data were used to train and validate MLM in predicting spasticity. The trained and validated MLM algorithm was later deployed to predict the ambiguous spasticity datasets. A series of MLM were applied, including Support Vector Machine, Decision Tree, and Random Forest. The MLM's performance accuracy of the validation data was 96%, 52%, and 72%, respectively. The validated MLM accuracy performance level predicting ambiguous datasets reduces to 20%, 23%, and 23%, respectively. This study elucidates data biases and variances of disease background, pathophysiological and anatomical factors that have to be considered in MLM training.
Whether higher variability in older adults' walking is an indication of increased instability has been challenged recently. We performed a computer simulation to investigate the effect of sensorimotor noise on the kinematic variability and stability in a biped walking model. Stochastic differential equations of the system with additive Gaussian white noise was constructed and solved. Sensorimotor noise mainly resulted in higher kinematic variability but its influence on gait stability is minimal. This implies that kinematic variability evident in walking gaits of older adults could be the result of internal sensorimotor noise and not an indication of instability.
The current study investigates the hyperemic flow effects on heamodynamics parameters such as velocity, wall shear stress in 3D coronary artery models with and without stenosis. The hyperemic flow is used to evaluate the functional significance of stenosis in the current era. Patients CT scan data of having healthy and coronary artery disease was chosen for the reconstruction of 3D coronary artery models. The diseased 3D models of coronary artery shows a narrowing of >50% lumen area. Computational fluid dynamics was performed to simulate the hyperemic flow condition. The results showed that the recirculation zone was observed immediate to the stenosis and highest wall shear stress was observed across the stenosis. The decrease in pressure was found downstream to the stenosis as compared to the coronary artery without stenosis. Our analysis provides an insight into the distribution of wall shear stress and pressure drop, thus improving our understanding of hyperemic flow effect under both conditions.