Suchergebnis: Katalogdaten im Frühjahrssemester 2022
Biomedical Engineering Master  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Vertiefungsfächer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Biomechanics | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kernfächer der Vertiefung Während des Studiums müssen mindestens 12 KP aus Kernfächern einer Vertiefung (Track) erreicht werden. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 227-0391-00L | Medical Image Analysis Basic knowledge of computer vision would be helpful. | W | 3 KP | 2G | E. Konukoglu, M. A. Reyes Aguirre | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | It is the objective of this lecture to introduce the basic concepts used in Medical Image Analysis. In particular the lecture focuses on shape representation schemes, segmentation techniques, machine learning based predictive models and various image registration methods commonly used in Medical Image Analysis applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | This lecture aims to give an overview of the basic concepts of Medical Image Analysis and its application areas. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Prerequisites: Basic concepts of mathematical analysis and linear algebra. Preferred: Basic knowledge of computer vision and machine learning would be helpful. The course will be held in English. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1392-00L | Mechanobiology: Implications for Development, Regeneration and Tissue Engineering | W | 3 KP | 2G | G. Shivashankar | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course will emphasize the importance of mechanobiology to cell determination and behavior. Its importance to regenerative medicine and tissue engineering will also be addressed. Finally, this course will discuss how age and disease adversely alter major mechanosensitive developmental programs. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The goal of this course is to provide an introduction to the emerging field of “Mechanobiology”. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | We will focus on cells and tissues and introduce the major methods employed in uncovering the principles of mechanobiology. We will first discuss the cellular mechanotransduction mechanisms and how they regulate genomes. This will be followed by an analysis of the mechanobiological underpinnings of cellular differentiation, cell-state transitions and homeostasis. Developing on this understanding, we will then introduce the mechanobiological basis of cellular ageing and its impact on tissue regeneration, including neurodegeneration and musculoskeletal systems. We will then highlight the importance of tissue organoid models as routes to regenerative medicine. We will also discuss the impact of mechanobiology on host-pathogen interactions. Finally, we will introduce the broad area of mechanopathology and the development of cell-state biomarkers as readouts of tissue homeostasis and disease pathologies. Collectively, the course will provide a quantitate framework to understand the mechanobiological processes at cellular scale and how they intersect with tissue function and diseases. Lecture 1: Introduction to the course: forces, signalling and cell behaviour Lecture 2: Methods to engineer and sense mechanobiological processes Lecture 3: Mechanisms of cellular mechanosensing and cytoskeletal remodelling Lecture 4: Nuclear mechanotransduction pathways Lecture 5: Genome organization, regulation and genome integrity Lecture 6: Differentiation, development and reprogramming Lecture 7: Tissue microenvironment, cell behaviour and homeostasis Lecture 8: Cellular aging and tissue regeneration Lecture 9: Neurodegeneration and regeneration Lecture 10: Musculoskeletal systems and regeneration Lecture 11: Tissue organoid models and regenerative medicine Lecture 12: Microbial systems and host-pathogen interactions Lecture13: Mechanopathology and cell-state biomarkers Lecture14: Concluding lecture and case studies | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | n/a | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Topical Scientific Manuscripts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1397-00L | Orthopaedic Biomechanics  Number of participants limited to 48. | W | 3 KP | 2G | R. Müller, J. Schwiedrzik | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course is aimed at studying the mechanical and structural engineering of the musculoskeletal system alongside the analysis and design of orthopaedic solutions to musculoskeletal failure. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | To apply engineering and design principles to orthopaedic biomechanics, to quantitatively assess the musculoskeletal system and model it, and to review rigid-body dynamics in an interesting context. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Engineering principles are very important in the development and application of quantitative approaches in biology and medicine. This course includes a general introduction to structure and function of the musculoskeletal system: anatomy and physiology of musculoskeletal tissues and joints; biomechanical methods to assess and quantify tissues and large joint systems. These methods will also be applied to musculoskeletal failure, joint replacement and reconstruction; implants; biomaterials and tissue engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Stored on Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Orthopaedic Biomechanics: Mechanics and Design in Musculoskeletal Systems Authors: Donald L. Bartel, Dwight T. Davy, Tony M. Keaveny Publisher: Prentice Hall; Copyright: 2007 ISBN-10: 0130089095; ISBN-13: 9780130089090 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Lectures will be given in English. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1712-00L | Finite Element Analysis in Biomedical Engineering | W | 3 KP | 2V | S. J. Ferguson, B. Helgason | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course provides an introduction to finite element analysis, with a specific focus on problems and applications from biomedical engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Finite element analysis is a powerful simulation method for the (approximate) solution of boundary value problems. While its traditional roots are in the realm of structural engineering, the methods have found wide use in the biomedical engineering domain for the simulation of the mechanical response of the human body and medical devices. This course provides an introduction to finite element analysis, with a specific focus on problems and applications from biomedical engineering. This domain offers many unique challenges, including multi-scale problems, multi-physics simulation, complex and non-linear material behaviour, rate-dependent response, dynamic processes and fluid-solid interactions. Theories taught are reinforced through practical applications in self-programmed and commercial simulation software, using e.g. MATLAB, ANSYS, FEBIO. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | (Theory) The Finite Element and Finite Difference methods Gallerkin, weighted residuals, discretization (Theory) Mechanical analysis of structures Trusses, beams, solids and shells, DOFs, hand calculations of simple FE problems, underlying PDEs (Application) Mechanical analysis of structures Truss systems, beam systems, 2D solids, meshing, organ level analysis of bones (Theory and Application) Mechanical analysis of structures Micro- and multi-scale analysis, voxel models, solver limitations, large scale solvers (Theory) Non-linear mechanical analysis of structures Large strain, Newton-Rhapson, plasticity (Application) Non-linear mechanical analysis of structures Plasticity (bone), hyperelasticity, viscoelasticity (Theory and Application) Contact analysis Friction, bonding, rough contact, implants, bone-cement composites, pushout tests (Theory) Flow in Porous Media Potential problems, Terzhagi's consolidation (Application) Flow in Porous Media Confined and unconfined compression of cartilage (Theory) Heat Transfer and Mass Transport Diffusion, conduction and convection, equivalency of equations (Application) Heat Transfer and Mass Transport Sequentially-coupled poroelastic and transport models for solute transport (Theory) Computational Biofluid Dynamics Newtonian vs. Non-Newtonian fluid, potential flow (Application) Computational Biofluid Dynamics Flow between micro-rough parallel plates | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Handouts consisting of (i) lecturers' script, (ii) selected excerpts from relevant textbooks, (iii) selected excerpts from theory manuals of commercial simulation software, (iv) relevant scientific publications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Familiarity with basic numerical methods. Programming experience with MATLAB. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Wahlfächer der Vertiefung Diese Fächer sind für die Vertiefung in Biomechanics besonders empfohlen. Bei abweichender Fächerwahl konsultieren Sie bitte den Track Adviser. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 151-0540-00L | Experimentelle Mechanik | W | 4 KP | 2V + 1U | J. Dual, T. Brack | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | 1. Allgemeines: Messkette, Frequenzgang, Schwingungen und Wellen in kontinuierlichen Systemen, Modalanalyse, Statistik, Digitale Signalanalyse, Phasenregelkreis 2. Optische Methoden 3. Piezoelektrizität 4. Elektromagnetische Erzeugung und Messung von Schwingungen und Wellen 5. Kapazitive Messaufnehmer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Verständnis, quantitative Modellierung und praktische Anwendung von experimentellen Methoden zur Erzeugung und Messung von mechanischen Grössen (Bewegung, Deformation, Spannungen) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 1. Allgemeines: Messkette, Frequenzgang, Frequenzgangmessung, Schwingungen und Wellen in kontinuierlichen Systemen, Modalanalyse, Statistik, Digitale Signalanalyse, Phasenregelkreis 2. Optische Methoden (Akustooptische Modulation, Interferometrie, Holographie, Spannungsoptik, Schattenoptik, Moiré Methoden) 3. Piezoelektrische Materialien: Grundgleichungen, Anwendungen Beschleunigungsaufnehmer, Verschiebungsmessung) 4. Elektromagnetische Erzeugung und Messung von Schwingungen und Wellen 5. Kapazitive Messaufnehmer, Praktika und Uebungen | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | ja | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Voraussetzungen: Mechanik I bis III, Physik, Elektrotechnik | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 151-0622-00L | Measuring on the Nanometer Scale | W | 2 KP | 2G | A. Stemmer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Introduction to theory and practical application of measuring techniques suitable for the nano domain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Introduction to theory and practical application of measuring techniques suitable for the nano domain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Conventional techniques to analyze nano structures using photons and electrons: light microscopy with dark field and differential interference contrast; scanning electron microscopy, transmission electron microscopy. Interferometric and other techniques to measure distances. Optical traps. Foundations of scanning probe microscopy: tunneling, atomic force, optical near-field. Interactions between specimen and probe. Current trends, including spectroscopy of material parameters. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Slides and recordings available via Moodle (registered participants only). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 151-0630-00L | Nanorobotics | W | 4 KP | 2V + 1U | S. Pané Vidal | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Nanorobotics is an interdisciplinary field that includes topics from nanotechnology and robotics. The aim of this course is to expose students to the fundamental and essential aspects of this emerging field. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The aim of this course is to expose students to the fundamental and essential aspects of this emerging field. These topics include basic principles of nanorobotics, building parts for nanorobotic systems, powering and locomotion of nanorobots, manipulation, assembly and sensing using nanorobots, molecular motors, and nanorobotics for nanomedicine. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 151-0636-00L | Soft and Biohybrid Robotics | W | 4 KP | 3G | R. Katzschmann | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Soft and biohybrid robots are emerging fields taking inspiration from Nature to create integrated robots that are inherently safer to interact with. You will be able to create the structures, actuators, sensors, models, controllers, and machine learning architectures exploiting the deformable nature of these robots. You will apply the learned principles to challenges of your research domain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Learning Objective 1: Convert any robotics challenge into a functional soft robotic physical prototype Step 1: Formulate suitable functional requirements Step 2: Select actuator material Step 3: Design + fabricate suitable for the task Step 4: Controller for basic functionality Step 5: Learning Approach for complex robotic skills Learning Objective 2: Formulate control and learning frameworks to highly articulated robots in real life scenarios Step 1: Formulate the dynamic skills needed for the real life scenario Step 2: Pick or combine suitable control and learning frameworks given the robot at hand Step 3: Evaluate the control approach for a real life scenario Step 4: Modify and enhance the control approach and repeat the evaluation Learning Objective 3: Apply the principle of mechanical impedance and embodied intelligence to any research challenge within any domain Step 1: Identify the moving aspects of the problem Step 2: Choose and design the passive and actively-controlled degrees of freedom Step 3: Pick the actuation material based on suitability to your challenge Step 4: Design in detail multiple combinations of body and brain Step 5: Simulate, build, test, fail, and repeat this often and quickly until the soft robot works for simple settings Step 6: Upgrade and validate the robot for performances in real world conditions Learning Objective 4: Rethink approaches to robotics by moving towards designs made of living materials Step 1: Identify what problems could be easier to solve with a complex living material Step 2: Scout for available works that have potentially tackled the problem with a living material Step 3: Formulate a hypothesis for your new approach with a living material Step 4: Design a minimum viable prototype (MVP) that properly highlights your new approach | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Students will cover a range of latest research insights on materials, fabrication technologies, and modeling approaches to design, simulate, and build soft and biohybrid robots. Part 1: Functional and intelligent materials for use in soft and biohybrid robotic applications Part 2: Design and design morphologies of soft robotic actuators and sensors Part 3: Fabrication techniques including 3D printing, casting, roll-to-roll, tissue engineering Part 4: Biohybrid robotics including microrobots and macrorobots; tissue engineering Part 5: Mechanical modeling including minimal parameter models, finite-element models and ML-based models Part 6: Closed-loop controllers of soft robots that exploit the robot's impedance and dynamics for locomotion and manipulation tasks Part 7: Machine Learning approaches to soft robotics, for design synthesis, modeling, and control A mandatory semester-long project will teach the participants to implement the skills and knowledge learned during the class by building their own soft robotic prototype or simulation. There is a mandatory pass/fail assignment to be submitted within the first two weeks of class to get a spot in the project. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | All class materials including slides, recordings, class challenges infos, pre-reads, and tutorial summaries can be found on Moodle: https://moodle-app2.let.ethz.ch/course/view.php?id=14501 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | 1) Wang, Liyu, Surya G. Nurzaman, and Fumiya Iida. "Soft-material robotics." (2017). 2) Polygerinos, Panagiotis, et al. "Soft robotics: Review of fluid‐driven intrinsically soft devices; manufacturing, sensing, control, and applications in human‐robot interaction." Advanced Engineering Materials 19.12 (2017): 1700016. 3) Verl, Alexander, et al. Soft Robotics. Berlin, Germany:: Springer, 2015. 4) Cianchetti, Matteo, et al. "Biomedical applications of soft robotics." Nature Reviews Materials 3.6 (2018): 143-153. 5) Ricotti, Leonardo, et al. "Biohybrid actuators for robotics: A review of devices actuated by living cells." Science Robotics 2.12 (2017). 6) Sun, Lingyu, et al. "Biohybrid robotics with living cell actuation." Chemical Society Reviews 49.12 (2020): 4043-4069. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | dynamics, controls, intro to robotics Only for students at master or PhD level. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 151-0980-00L | Biofluiddynamics | W | 4 KP | 2V + 1U | D. Obrist, P. Jenny | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Introduction to the fluid dynamics of the human body and the modeling of physiological flow processes (biomedical fluid dynamics). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | A basic understanding of fluid dynamical processes in the human body. Knowledge of the basic concepts of fluid dynamics and the ability to apply these concepts appropriately. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This lecture is an introduction to the fluid dynamics of the human body (biomedical fluid dynamics). For selected topics of human physiology, we introduce fundamental concepts of fluid dynamics (e.g., creeping flow, incompressible flow, flow in porous media, flow with particles, fluid-structure interaction) and use them to model physiological flow processes. The list of studied topics includes the cardiovascular system and related diseases, blood rheology, microcirculation, respiratory fluid dynamics and fluid dynamics of the inner ear. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Lecture notes are provided electronically. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | A list of books on selected topics of biofluiddynamics can be found on the course web page. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-1046-00L | Computer Simulations of Sensory Systems Findet dieses Semester nicht statt. | W | 3 KP | 3G | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course deals with computer simulations of the human auditory, visual, and balance system. The lecture will cover the physiological and mechanical mechanisms of these sensory systems. And in the exercises, the simulations will be implemented with Python. The simulations will be such that their output could be used as input for actual neuro-sensory prostheses. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Our sensory systems provide us with information about what is happening in the world surrounding us. Thereby they transform incoming mechanical, electromagnetic, and chemical signals into “action potentials”, the language of the central nervous system. The main goal of this lecture is to describe how our sensors achieve these transformations, how they can be reproduced with computational tools. For example, our auditory system performs approximately a “Fourier transformation” of the incoming sound waves; our early visual system is optimized for finding edges in images that are projected onto our retina; and our balance system can be well described with a “control system” that transforms linear and rotational movements into nerve impulses. In the exercises that go with this lecture, we will use Python to reproduce the transformations achieved by our sensory systems. The goal is to write programs whose output could be used as input for actual neurosensory prostheses: such prostheses have become commonplace for the auditory system, and are under development for the visual and the balance system. For the corresponding exercises, at least some basic programing experience is required!! | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The following topics will be covered: • Introduction into the signal processing in nerve cells. • Introduction into Python. • Simplified simulation of nerve cells (Hodgkins-Huxley model). • Description of the auditory system, including the application of Fourier transforms on recorded sounds. • Description of the visual system, including the retina and the information processing in the visual cortex. The corresponding exercises will provide an introduction to digital image processing. • Description of the mechanics of our balance system, and the “Control System”-language that can be used for an efficient description of the corresponding signal processing (essentially Laplace transforms and control systems). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | For each module additional material will be provided on the e-learning platform "moodle". The main content of the lecture is also available as a wikibook, under http://en.wikibooks.org/wiki/Sensory_Systems | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Open source information is available as wikibook http://en.wikibooks.org/wiki/Sensory_Systems For good overviews of the neuroscience, I recommend: • Principles of Neural Science (5th Ed, 2012), by Eric Kandel, James Schwartz, Thomas Jessell, Steven Siegelbaum, A.J. Hudspeth ISBN 0071390111 / 9780071390118 THE standard textbook on neuroscience. NOTE: The 6th edition will be released on February 5, 2021! • L. R. Squire, D. Berg, F. E. Bloom, Lac S. du, A. Ghosh, and N. C. Spitzer. Fundamental Neuroscience, Academic Press - Elsevier, 2012 [ISBN: 9780123858702]. This book covers the biological components, from the functioning of an individual ion channels through the various senses, all the way to consciousness. And while it does not cover the computational aspects, it nevertheless provides an excellent overview of the underlying neural processes of sensory systems. • G. Mather. Foundations of Sensation and Perception, 2nd Ed Psychology Press, 2009 [ISBN: 978-1-84169-698-0 (hardcover), oder 978-1-84169-699-7 (paperback)] A coherent, up-to-date introduction to the basic facts and theories concerning human sensory perception. • The best place to get started with Python programming are the https://scipy-lectures.org/ On signal processing with Python, my upcoming book • Hands-on Signal Analysis with Python (Due: January 13, 2021 ISBN 978-3-030-57902-9, https://www.springer.com/gp/book/9783030579029) will contain an explanation to all the required programming tools and packages. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | • Since I have to gravel from Linz, Austria, to Zurich to give this lecture, I plan to hold this lecture in blocks (every 2nd week). • In addition to the lectures, this course includes external lab visits to institutes actively involved in research on the relevant sensory systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0966-00L | Quantitative Big Imaging: From Images to Statistics | W | 4 KP | 2V + 1U | P. A. Kaestner, M. Stampanoni | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The lecture focuses on the challenging task of extracting robust, quantitative metrics from imaging data and is intended to bridge the gap between pure signal processing and the experimental science of imaging. The course will focus on techniques, scalability, and science-driven analysis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | 1. Introduction of applied image processing for research science covering basic image processing, quantitative methods, and statistics. 2. Understanding of imaging as a means to accomplish a scientific goal. 3. Ability to apply quantitative methods to complex 3D data to determine the validity of a hypothesis | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Imaging is a well established field and is rapidly growing as technological improvements push the limits of resolution in space, time, material and functional sensitivity. These improvements have meant bigger, more diverse datasets being acquired at an ever increasing rate. With methods varying from focused ion beams to X-rays to magnetic resonance, the sources for these images are exceptionally heterogeneous; however, the tools and techniques for processing these images and transforming them into quantitative, biologically or materially meaningful information are similar. The course consists of equal parts theory and practical analysis of first synthetic and then real imaging datasets. Basic aspects of image processing are covered such as filtering, thresholding, and morphology. From these concepts a series of tools will be developed for analyzing arbitrary images in a very generic manner. Specifically a series of methods will be covered, e.g. characterizing shape, thickness, tortuosity, alignment, and spatial distribution of material features like pores. From these metrics the statistics aspect of the course will be developed where reproducibility, robustness, and sensitivity will be investigated in order to accurately determine the precision and accuracy of these quantitative measurements. A major emphasis of the course will be scalability and the tools of the 'Big Data' trend will be discussed and how cluster, cloud, and new high-performance large dataset techniques can be applied to analyze imaging datasets. In addition, given the importance of multi-scale systems, a data-management and analysis approach based on modern databases will be presented for storing complex hierarchical information in a flexible manner. Finally as a concluding project the students will apply the learned methods on real experimental data from the latest 3D experiments taken from either their own work / research or partnered with an experimental imaging group. The course provides the necessary background to perform the quantitative evaluation of complicated 3D imaging data in a minimally subjective or arbitrary manner to answer questions coming from the fields of physics, biology, medicine, material science, and paleontology. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Available online. https://imaginglectures.github.io/Quantitative-Big-Imaging-2021/weeklyplan.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Will be indicated during the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Ideally, students will have some familiarity with basic manipulation and programming in languages like Python, Matlab, or R. Interested students who are worried about their skill level in this regard are encouraged to contact Anders Kaestner directly (anders.kaestner@psi.ch). More advanced students who are familiar with Python, C++, (or in some cases Java) will have to opportunity to develop more of their own tools. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0220-00L | Introduction to Machine Learning Limited number of participants. Preference is given to students in programmes in which the course is being offered. All other students will be waitlisted. Please do not contact Prof. Krause for any questions in this regard. If necessary, please contact studiensekretariat@inf.ethz.ch | W | 8 KP | 4V + 2U + 1A | A. Krause, F. Yang | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course introduces the foundations of learning and making predictions based on data. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The course will introduce the foundations of learning and making predictions from data. We will study basic concepts such as trading goodness of fit and model complexitiy. We will discuss important machine learning algorithms used in practice, and provide hands-on experience in a course project. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | - Linear regression (overfitting, cross-validation/bootstrap, model selection, regularization, [stochastic] gradient descent) - Linear classification: Logistic regression (feature selection, sparsity, multi-class) - Kernels and the kernel trick (Properties of kernels; applications to linear and logistic regression); k-nearest neighbor - Neural networks (backpropagation, regularization, convolutional neural networks) - Unsupervised learning (k-means, PCA, neural network autoencoders) - The statistical perspective (regularization as prior; loss as likelihood; learning as MAP inference) - Statistical decision theory (decision making based on statistical models and utility functions) - Discriminative vs. generative modeling (benefits and challenges in modeling joint vy. conditional distributions) - Bayes' classifiers (Naive Bayes, Gaussian Bayes; MLE) - Bayesian approaches to unsupervised learning (Gaussian mixtures, EM) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Textbook: Kevin Murphy, Machine Learning: A Probabilistic Perspective, MIT Press | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Designed to provide a basis for following courses: - Advanced Machine Learning - Deep Learning - Probabilistic Artificial Intelligence - Seminar "Advanced Topics in Machine Learning" | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0840-02L | Anwendungsnahes Programmieren mit Python | W | 2 KP | 2G | L. E. Fässler, M. Dahinden | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Diese Lehrveranstaltung vermittelt wichtige Basiskonzepte zur Bearbeitung interdisziplinärer Programmierprojekte mit Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Die Studierenden können... - selbstständig Aufgabenstellungen als Programm codieren, Programme testen und Fehler beheben. - bestehenden Programmcode verstehen, hinterfragen und verbessern. - mit der Komplexität realer Daten umgehen. - Daten in einer geeigneten Datenstruktur speichern. - Modelle aus den Naturwissenschaften als Simulation umzusetzen. - Zufallsexperimente durchführen und die Resultate interpretieren. - Standard-Algorithmen erklären und anwenden. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | In der Vorlesung werden folgende Basis-Konzepte behandelt: 1. Variablen und Datentypen 2. Kontrollstrukturen und Logik 3. Sequentielle Datentypen, Such- und Sortieralgorithmen, Simulationen 4. Funktionen, Module und Animationen 5. Matrizen, Zufallsexperimente und Zelluläre Automaten. 6. Klassen und Objekte Im praktischen Teil der Lehrveranstaltung werden selbstständig kleine Programmierprojekte mit naturwissenschaftlichem Kontext bearbeitet. Als Vorbereitung werden elektronische Tutorials bereitgestellt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | L. Fässler, M. Dahinden, D. Komm, and D. Sichau: Einführung in die Programmierung mit Python und Matlab. Begleitunterlagen zum Onlinekurs und zur Vorlesung, 2016. ISBN: 978-3741250842. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Für diese Lehrveranstaltung werden keine Vorkenntnisse vorausgesetzt. Sie basiert auf anwendungsorientiertem Lernen. Den grössten Teil der Arbeit verbringen die Studierenden damit, Programmierprojekte mit naturwissenschaftlichen Daten zu bearbeiten und die Resultate mit Assistierenden zu diskutieren. Für die Aneignung der Programmier-Grundlagen stehen elektronische Tutorials zur Verfügung. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 327-2225-00L | MaP Distinguished Lecture Series on Soft Robotics Findet dieses Semester nicht statt. This course is primarily designed for MSc and doctoral students. Guests are welcome. | W | 1 KP | 2S | R. Katzschmann | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course is an interdisciplinary colloquium on Soft Robotics involving different internationally renowned speakers from academia and industry giving lectures about their cutting-edge research, which highlights the state-of-the-art and frontiers in the Soft Robotics field. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Participants become acquainted with the state-of-the-art and frontiers in Soft Robotics, which is a topic of global and future relevance from the field of materials and process engineering. The self-study of relevant literature and active participation in discussions following presentations by internationally renowned speakers stimulate critical thinking and allow participants to deliberately discuss challenges and opportunities with leading academics and industrial experts and to exchange ideas within an interdisciplinary community. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This course is a colloquium involving a selected mix of internationally renowned speaker from academia and industry who present their cutting-edge research in the field of Soft Robotics. The self-study of relevant pre-read literature provided in advance to each lecture serves as a basis for active participation in the critical discussions following each presentation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Selected scientific pre-read literature (max. three articles per lecture) relevant for and discussed during the lectures is posted in advance on the course web page. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Participants should have a solid background in materials science and/or engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 363-1130-00L | Digital Health | W | 3 KP | 2V | T. Kowatsch | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Today, we face the challenge of non-communicable diseases. Personal coaching approaches are neither scalable nor financially sustainable. The question arises therefore to which degree digital health interventions are appropriate to address this challenge. In this lecture, students will learn about the assessment of digital health interventions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Can medical Alexas make us more healthy? (The New York Times, April 2021), Wearables as a tool for measuring therapeutic adherence in behavioral health (npj Digital Medicine, May 2021), Improving community healthcare screenings with smartphone‐based AI technologies (The Lancet Digital Health, May 2021), Predictive analytics and tailored interventions improve clinical outcomes (npj Digital Medicine, June 2021), H1 2021 secured $14.7B in digital health funding, already surpassing all of 2020ʹs funding (Rock Health, 2021) What are the implications and rationale behind the recent developments in the field of digital health? Digital Health is the use of information and communication technology for the prevention, management and treatment of diseases. It covers topics such as digital health interventions, digital biomarker research, digital coaches and healthcare chatbots, telemedicine, mobile and wearable computing, self-tracking, personalised medicine, connected health, smart homes or smart cars. In the 20th century, healthcare systems specialised in acute care. In the 21st century, we now face the challenge of dealing with the specific characteristics of chronic conditions. These are now responsible for around 70% of all deaths worldwide and 85% of all deaths in Europe and are associated with an estimated economic loss of $7 trillion between 2011 and 2025. Chronic diseases require an intervention paradigm that focuses on prevention and lifestyle change. Lifestyle (e.g., diet, physical activity, tobacco, or alcohol consumption) can reduce the risk of suffering from a chronic condition or, if already present, can reduce its burden. However, a lifestyle change is only implemented by a fraction of those affected, partly because of missing or inadequate interventions or health literacy, partly due to socio‐cultural influences. Individual personal coaching of these individuals is neither scalable nor financially sustainable. Against this background, the question arises of how digital health interventions (DHIs) can allow medical doctors and other caregivers to scale and tailor long‐term treatments to individuals in need at sustainable costs. At the intersection of information systems research, computer science, behavioural medicine, and health economics, this lecture has the objective to help students and upcoming healthcare executives interested in the multi‐disciplinary field of digital health to better understand the design and assessment of DHIs. After the course, students will be able to... 1. know design and assessment frameworks for DHIs 2. assess DHIs 3. discuss the advantages and disadvantages of DHIs 4. propose a DHI incl. business model that addresses an unmet need of existing DHIs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | To reach the learning objectives, the following topics are covered: 1. Overview of design and assessment frameworks 2. Preparation of DHIs 3. Optimization of DHIs 4. Evaluation of DHIs The lecture is structured in two parts and follows the concept of a hybrid treatment consisting of live sessions and complementary online lessons. In the first part, participants will learn and discuss the learning topics. Complementary learning material (e.g., video and audio clips), multiple-choice questions and exercises are provided online. In the second part, participants work in teams and will use their knowledge from the first part of the lecture to critically assess DHIs, identify unmet needs and propose a DHI incl. a business model that addresses the unmet need. Each team will then present and discuss their findings with their fellow students who will provide peer-reviews. Additional online coaching sessions are offered to support the teams with the preparation of their presentations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | 1. Cohen AB Dorsey ER Mathews SC et al. (2020) A digital health industry cohort across the health continuum Nature Digital Medicine 3(68), 10.1038/s41746‐020‐0276‐9 2. Collins LM (2018) Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST) New York: Springer, 10.1007/978-3-319-72206-1 3. Coravos A. Khozin S. and K. D. Mandl (2019) Developing and Adopting Safe and Effective Digital Biomarkers to Improve Patient Outcomes Nature Digital Medicine 2 Paper 14, 10.1038/s41746‐019‐0090‐4 4. Fleisch E Franz C Herrmann A (2021) The Digital Pill: What Everyone Should Know about the Future of Our Healthcare System, Emerald Publishing: Bingley,UK, 10.1108/9781787566750 5. Katz DL Frates EP Bonnet JP Gupta SK Vartiainen E and Carmona RH (2018) Lifestyle as Medicine: The Case for a True Health Initiative American Journal of Health Promotion 32(6), 1452-1458, 10.1177/0890117117705949 6. Kvedar, JC, Fogel AL, Elenko E and Zohar D (2016) Digital medicine’s march on chronic disease Nature Biotechnology 34(3), 239-246, 10.1038/nbt.3495 7. Kowatsch T Otto L Harperink S Cotti A Schlieter H (2019) A Design and Evaluation Framework for Digital Health Interventions it ‐ Information Technology 61(5‐6), 253‐263, 10.1515/itit‐2019‐0019 8. Kowatsch T Fleisch E (2021) Digital Health Interventions, in: Gassmann O Ferrandina F (eds): Connected Business: Creating Value in the Networked Economy, Springer: Berlin, 10.1007/978-3-030-76897-3_4 9. Kowatsch T Schachner T Harperink S et al (2021) Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study, Journal of Medical Internet Research (JMIR) 23(2):e25060 10.2196/25060 10. Kowatsch T Lohse KM Erb V et al (2021) Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: 4 Design and Evaluation Studies, Journal of Medical Internet Research (JMIR) 23(2):e23612, 10.2196/23612 11. Nahum‐Shani I Smith SN Spring BJ Collins LM Witkiewitz K Tewari A Murphy SA (2018) Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support Annals of Behavioral Medicine 52 (6), 446‐462, 10.1007/s12160-016-9830-8 12. Sim, I. (2019) Mobile Devices and Health The New England Journal of Medicine, 381(10), 956‐ 968, 10.1056/NEJMra1806949 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 376-1217-00L | Rehabilitation Engineering I: Motor Functions | W | 4 KP | 2V + 1U | R. Riener, M. Xiloyannis | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | “Rehabilitation” is the (re)integration of an individual with a disability into society. Rehabilitation engineering is “the application of science and technology to ameliorate the handicaps of individuals with disability”. Such handicaps can be classified into motor, sensor, and cognitive disabilities. In general, one can distinguish orthotic and prosthetic methods to overcome these disabilities. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The goal of this course is to present classical and new technical principles as well as specific examples applied to compensate or enhance motor deficits. In the 1 h exercise the students will learn how to solve representative problems with computational methods applied to exoprosthetics, wheelchair dynamics, rehabilitation robotics and neuroprosthetics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Modern methods rely more and more on the application of multi-modal and interactive techniques. Multi-modal means that visual, acoustical, tactile, and kinaesthetic sensor channels are exploited to display information to the patient. Interaction means that the exchange of information and energy occurs bi-directionally between the rehabilitation device and the human being. Thus, the device cooperates with the patient rather than imposing an inflexible strategy (e.g., movement) upon the patient. These principles are recurrent in modern technological tools to support rehabilitation, including prosthesis, orthoses, powered exoskeletons, powered wheelchairs, therapy robots and virtual reality systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Books: Burdet, Etienne, David W. Franklin, and Theodore E. Milner. Human robotics: neuromechanics and motor control. MIT press, 2013. Krakauer, John W., and S. Thomas Carmichael. Broken movement: the neurobiology of motor recovery after stroke. MIT Press, 2017. Teodorescu, Horia-Nicolai L., and Lakhmi C. Jain, eds. Intelligent systems and technologies in rehabilitation engineering. CRC press, 2000. Winters, Jack M., and Patrick E. Crago, eds. Biomechanics and neural control of posture and movement. Springer Science & Business Media, 2012. Selected Journal Articles: Abbas, James J., and Robert Riener. "Using mathematical models and advanced control systems techniques to enhance neuroprosthesis function." Neuromodulation: Technology at the Neural Interface 4.4 (2001): 187-195. Basalp, Ekin, Peter Wolf, and Laura Marchal-Crespo. "Haptic training: which types facilitate (re) learning of which motor task and for whom Answers by a review." IEEE Transactions on Haptics (2021). Calabrò, Rocco Salvatore, et al. "Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?." Neurological Sciences 37.4 (2016): 503-514. Cooper, R. (1993) Stability of a wheelchair controlled by a human. IEEE Transactions on Rehabilitation Engineering 1, pp. 193-206. Gassert, Roger, and Volker Dietz. "Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective." Journal of neuroengineering and rehabilitation 15.1 (2018): 1-15. Laver, Kate E., et al. "Virtual reality for stroke rehabilitation." Cochrane database of systematic reviews 11 (2017). Marquez-Chin, Cesar, and Milos R. Popovic. "Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: a review." Biomedical engineering online 19 (2020): 1-25. Miller, Larry E., Angela K. Zimmermann, and William G. Herbert. "Clinical effectiveness and safety of powered exoskeleton-assisted walking in patients with spinal cord injury: systematic review with meta-analysis." Medical devices (Auckland, NZ) 9 (2016): 455. Raspopovic, Stanisa. "Advancing limb neural prostheses." Science 370.6514 (2020): 290-291. Riener, R. (2013) Rehabilitation Robotics. Foundations and Trends in Robotics, Vol. 3, nos. 1-2, pp. 1-137. Riener, R., Lünenburger, L., Maier, I. C., Colombo, G., & Dietz, V. (2010). Locomotor training in subjects with sensori-motor deficits: An overview of the robotic gait orthosis Lokomat. Journal of Healthcare Engineering, 1(2), 197-216. Riener, R., Nef, T., Colombo, G. (2005) Robot-aided neurorehabilitation for the upper extremities. Medical & Biological Engineering & Computing 43(1), pp. 2-10. Sigrist, Roland, et al. "Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review." Psychonomic bulletin & review 20.1 (2013): 21-53. Xiloyannis, Michele, et al. "Soft Robotic Suits: State of the Art, Core Technologies, and Open Challenges." IEEE Transactions on Robotics (2021). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Target Group: Students of higher semesters and PhD students of - D-MAVT, D-ITET, D-INFK - Biomedical Engineering - Medical Faculty, University of Zurich Students of other departments, faculties, courses are also welcome | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1150-00L | Clinical Challenges in Musculoskeletal Disorders | W | 2 KP | 2G | M. Leunig, S. J. Ferguson, Z.‑M. Manjaly | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course reviews musculoskeletal disorders focusing on the clinical presentation, current treatment approaches and future challenges and opportunities to overcome failures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Appreciation of the surgical and technical challenges, and future perspectives offered through advances in surgical technique, new biomaterials and advanced medical device construction methods. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Foot deformities, knee injuries, knee OA, hip disorders in the child and adolescent, hip OA, spine deformities, degenerative spine disease, shoulder in-stability, hand, rheumatoid diseases, neuromuscular diseases, sport injuries and prevention | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1168-00L | Sports Biomechanics | W | 3 KP | 2V | S. Lorenzetti | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Various types of sport are studied from a mechanical point of view. Of particular interest are the key parameters of a sport as well as the performance relevant indicators. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The aim of this lecture is to enable the students to study a sport from a biomechanical viewpoint and to develop significant models for which evaluations of the limitations and verifications can be carried out. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Sport biomechanics is concerned with the physical and mechanical basic principles of sports. The lecture requires an in-depth mechanical understanding on the side of the student. In this respect, the pre-attendance of the lectures Biomechanics II and Movement and Sports Biomechanics or an equivalent course is expected. The human body is treated as a mechanical system during sport. The interaction of the active and passive movements and outside influences is analysed. Using sports such as ski-jumping, cycling, or weight training, applicable models are created, analyzed and suitable measuring methods are introduced. In particular, the constraints as well as the limitations of the models are of great relevance. The students develop their own models for different sport types, critically discuss the advantages and disadvantages and evaluate applicable measurement methods. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Handout will be distributed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1308-00L | Development Strategies for Medical Implants Maximale Teilnehmerzahl: 25 bis 30. Die Einschreibungen werden nach chronologischem Eingang berücksichtigt. | W | 3 KP | 2V + 1U | J. Mayer-Spetzler, N. Mathavan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Introduction to development strategies for implantable devices considering the interdependecies of biocompatibility, clinical, regulatory and economical requirements ; discussion of the state of the art and actual trends in in orthopedics, sports medicine and cardio-vascular surgery as well as regenerative medicine (tissue engineering). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Basic considerations in implant development Concept of structural and surface biocompatiblity and its relevance for the design of implant and surgical technique Understanding of conflicting factors, e.g. clinical need, economics and regulatory requirements Concepts of tissue engineering, its strengths and weaknesses as current and future clinical solution | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Understanding of clinical and economical needs as guide lines for the development of medical implants; implant and implantation related tissue reactions, biocompatible materials and material processing technologies; implant testing and regulatory procedures; discussion of the state of the art and actual trends in implant development in sports medicine, spinal and cardio-vascular surgery; introduction to tissue engineering. Selected topics will be further illustrated by commented movies from surgeries. Seminar: Group seminars on selected controversial topics in implant development. Participation is mandatory Planned excursions (limited availability, not mandatory, to be confirmed): 1. Participation (as visitor) on a life surgery (travel at own expense) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Scribt (electronically available): - presented slides - selected scientific papers for further reading | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Reference to key papers will be provided during the lectures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Only Master students, achieved Bachelor degree is a pre-condition The number of participants in the course is limited to 30 students in total. Students will be exposed to surgical movies which may cause emotional reactions. The viewing of the surgical movies is voluntary and is on the student's own responsability. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1614-00L | Principles in Tissue Engineering | W | 3 KP | 2V | K. Maniura, M. Rottmar, M. Zenobi-Wong | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Fundamentals in blood coagulation; thrombosis, blood rheology, immune system, inflammation, foreign body reaction on the molecular level and the entire body are discussed. Applications of biomaterials for tissue engineering in different tissues are introduced. Fundamentals in medical implantology, in situ drug release, cell transplantation and stem cell biology are discussed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Understanding of molecular aspects for the application of biodegradable and biocompatible Materials. Fundamentals of tissue reactions (eg. immune responses) against implants and possible clinical consequences will be discussed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This class continues with applications of biomaterials and devices introduced in Biocompatible Materials I. Fundamentals in blood coagulation; thrombosis, blood rheology; immune system, inflammation, foreign body reaction on the level of the entire body and on the molecular level are introduced. Applications of biomaterials for tissue engineering in the vascular system, skeletal muscle, heart muscle, tendons and ligaments, bone, teeth, nerve and brain, and drug delivery systems are introduced. Fundamentals in medical implantology, in situ drug release, cell transplantation and stem cell biology are discussed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Handouts provided during the classes and references therin. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | The molecular Biology of the Cell, Alberts et al., 5th Edition, 2009. Principles in Tissue Engineering, Langer et al., 2nd Edition, 2002 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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