4Figure 4.1 Bone shapes.Figure 4.2 Cortical and trabecular.Figure 4.3 Comparison of four empirical expressions.Figure 4.4 Algorithm for calculation of elasticity modulus.Figure 4.5 A list of information contained in a CT scan.Figure 4.6 Effect of threshold value on the segmentation of the femoral bone...Figure 4.7 Printing of the calculated values.Figure 4.8 Visual representation of the original image and segmented bone us...Figure 4.9 Femoral body in the transverse plane before segmentation.Figure 4.10 Femoral body in the transverse plane after segmentation.Figure 4.11 Femoral bone model.Figure 4.12 Applied boundary conditions for the numerical simulations.Figure 4.13 Obtained stress distribution – case 1.Figure 4.14 Obtained displacement distribution – case 1.Figure 4.15 Obtained stress distribution – case 2.Figure 4.16 Obtained displacement distribution – case 2.Figure 4.17 Obtained stress distribution – case 3.Figure 4.18 Obtained displacement distribution – case 3.Figure 4.19 Correlation between Young's modulus of elasticity and calculated...Figure 4.20 Correlation between Young's modulus of elasticity and calculated...
5 Chapter 5Figure 5.1 Schematic representation of the cardiovascular system [28].Figure 5.2 Anatomy of the aorta [21].Figure 5.3 The structure of the wall of the main components of healthy elast...Figure 5.4 CT scan shows the false and true lumen.Figure 5.5 Classification of aortic dissection.Figure 5.6 Coordinate definitions.Figure 5.7 Schematic representation of a deformable body under the action of...Figure 5.8 Schematic representation of the distorted axial velocity profile ...Figure 5.9 Schematic representation of the velocity profile in bifurcation....Figure 5.10 Geometric dimensions of the aorta.Figure 5.11 Geometries of parametric models: (a) healthy aorta; (b) dissecte...Figure 5.12 The time‐dependent pulsatile waveform at the ascending aorta.Figure 5.13 Example 1 – distribution of velocity (a) and pressure (b) throug...Figure 5.14 Example 1 – distribution of shear stress on fluid domain (a) and...Figure 5.15 Example 2 – distribution of velocity (a) and pressure (b) throug...Figure 5.16 Example 2 – distribution of wall shear stress on fluid domain (a...Figure 5.17 Example 3 – distribution of velocity (a) and pressure (b) throug...Figure 5.18 Example 3 – distribution of wall shear stress on fluid domain (a...Figure 5.19 Example 4 – distribution of velocity (a) and pressure (b) throug...Figure 5.20 Example 4 – distribution of wall shear stress on fluid domain (a...
6 Chapter 6Figure 6.1 A simple example of augmented reality.Figure 6.2 Schematic representation of AR monitor system.Figure 6.3 Augmented reality application on mobile phone.Figure 6.4 Schematic diagrams: SHDM device (left); VHDM device (right).Figure 6.5 Schematic representation – the fundamental principle of AR system...Figure 6.6 Dome and arrow during the suturing task to guide the trainee in t...Figure 6.7 Schematic representation of the flow of an AR‐based biomedical en...Figure 6.8 Some examples of ArUco markers.Figure 6.9 Example of ArUco marker.Figure 6.10 ArUco markers on the wall – preparation AR scene.Figure 6.11 An example of using ArUco marker – AR images on a real wall.Figure 6.12 ArUco markers – biomedical application.Figure 6.13 Matching results by using cross‐checks filter.Figure 6.14 Visualization of matches that were refined using homography matr...Figure 6.15 Visualization of matches that were refined using refinement homo...Figure 6.16 Examples of calibration images.Figure 6.17 AR result with wrong calibration parameters (left); with good ca...Figure 6.18 Accurate tracking of liver tumors for augmented reality in robot...
7 Chapter 7Figure 7.1 Balance physiotherapy mock‐up motion capture and display devices....Figure 7.2 Balance physiotherapy hologram using Meta 2 and Kinect 2 for stan...Figure 7.3 First versions of avatars used with Meta 2. Realistic Female Virt...Figure 7.4 HoloLens Virtual Coach (VC).Figure 7.5 Virtual Coach initial standing position (a) and direction indicat...Figure 7.6 Gazing pointers. (a) White pointer when gazing out of VC and (b) ...Figure 7.7 Hand gesture. Interacting with VC. VC demonstrates exercise after...Figure 7.8 Voice gesture. Interacting with VC. VC demonstrates exercise afte...Figure 7.9 HoloBox schematic setup.Figure 7.10 Test version – demonstrates exercise.Figure 7.11 Conceptual architecture of the interfacing modules with the MCWS...Figure 7.12 Avatars.Figure 7.13 Virtual Coach Demo mode with controls.Figure 7.14 Sitting exercise – yaw.Figure 7.15 Sitting exercise – pitch.Figure 7.16 Sitting exercise – bend over.Figure 7.17 Standing exercise – maintain balance.Figure 7.18 Standing exercise – bend over.Figure 7.19 Standing exercise – reach up.Figure 7.20 Standing exercise – turn 180o.Figure 7.21 Walking exercise – looking at the horizon.Figure 7.22 Walking exercise – yaw.Figure 7.23 Walking exercise – pitch.Figure 7.24 Avatar following the index finger with the eyes.Figure 7.25 Opened eyes.Figure 7.26 Closed eyes.Figure 7.27 Speech recognition workflow.Figure 7.28 Motion tracking – marker‐less based system.Figure 7.29 Motion tracking – marker‐based system.Figure 7.30 Motion capture professional studio.Figure 7.31 HOLOBALANCE target image.Figure 7.32 Unity's Avatar structure.Figure 7.33 Animation using a muscle‐based control framework.Figure 7.34 A biomechanical upper limb model. On the left, the elbow is actu...Figure 7.35 Inverse dynamics‐based optimization. The optimization problem it...Figure 7.36 Forward dynamics‐based optimization. The optimization problem it...Figure 7.37 Tension–velocity curve corresponding to a muscle in the tetanize...Figure 7.38 Isometric tension–length curve.Figure 7.39 Hill's functional model of a muscle. CE is the contractile eleme...
8 Chapter 8Figure 8.1 Heart geometry and seven different regions of the model: (1) Sino...Figure 8.2 Six electrodes (V1–V6) positioned at the chest to model the preco...Figure 8.3 Material local coordinate system according to [14]. Biaxial loadi...Figure 8.4 Experimental curves with hysteresis for biaxial loading of myocar...Figure 8.5 Experimental curves without hysteresis for biaxial loading of myo...Figure 8.6 Interpolation of normal stresses in the local (material) coordina...Figure 8.7 Shear stresses acting on material element.Figure 8.8 Shear stresses in terms of shear deformation for three modes. (a)...Figure 8.9 Shear stress constitutive curves, no hysteresis (Figure 8.13 [14]...Figure 8.10 Whole heart activation simulation from lead II ECG signal at var...Figure 8.11 Simulated and measured ECG for six electrodes (V1–V6).Figure 8.12 Body surface potential maps in a healthy subject during progress...Figure 8.13 Model of the human heart: (a) Purkinje network; (b) uniform Purk...
9 Chapter 9Figure 9.1 Design flow of Xilinx System Generator use in implementing an alg...Figure 9.2 Xilinx System Generator library.Figure 9.3 Schematic icons for some of the widely used XSG elements. (a) Xil...Figure 9.4 Image preprocessing module.Figure 9.5 Image post‐processing module.Figure 9.6 Simulink – System Generator DSP model for creating negative image...Figure 9.7 Simulink – System Generator DSP model for image contrast stretchi...Figure 9.8 Robert method – System Generator DSP sub‐model for horizontal mas...Figure 9.9 Robert method ‐ System Generator DSP sub‐model for vertical mask ...Figure 9.10 Prewitt method – System Generator DSP sub‐model for horizontal m...Figure 9.11 Prewitt method – System Generator DSP sub‐model for vertical mas...Figure 9.12 Sobel method – System Generator DSP sub‐model for horizontal mas...Figure 9.13 Sobel method – System Generator DSP sub‐model for vertical mask ...Figure 9.14 System Generator DSP sub‐model for thresholding method.Figure 9.15 System Generator DSP model for Canny Edge detection.Figure 9.16 Canny method – System Generator DSP sub‐model for Gaussian smoot...Figure 9.17 Canny method – System Generator DSP sub‐model for edge detection...Figure 9.18 Canny method – System Generator DSP sub‐model for Non‐Maximum Su...Figure 9.19 Canny method – System Generator DSP sub‐model for Hysteresis thr...Figure 9.20 Combined software and hardware co‐simulation model for the edge ...Figure 9.21 Original and output image after application of algorithm for ima...Figure 9.22 Original and output image after application of algorithm for con...Figure 9.23 Original image (a) compared with output images after application...Figure 9.24 Canny edge detection sub‐steps: Gaussian smoothing (a), calculat...
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