Suchergebnis: Katalogdaten im Frühjahrssemester 2023
Biomedical Engineering Master  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Biomechanics | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 151-0540-00L | Experimental Mechanics | W | 4 KP | 2V + 1U | P. Carrara | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course provides an introduction to experimental mechanics and covers basic and advanced solid mechanics experimental testing methods. The basic working principles of analogic transducers, testing machines and of optical and X-ray tomographic imaging techniques are illustrated along with an overview of the essential image processing and analysis approaches. ccc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Understanding the basic principles of experimental methods in solid mechanics and acquiring the ability to properly design, execute and analyze experimental tests targeted to investigate a mechanical process. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 1. Introduction: testing machines; analogic and digital signals; force, displacement and strain transducers; test control. 2. Analogic transducers: working principles; load cells; LVDTs; strain gauges. 3. Solid mechanics tests: compression, tensile and bending tests; fracture mechanics tests. 4. Optical methods: 2D and 3D digital image correlation, basic principles and applications. 5. 3D X-ray computed tomography (CT): basic principles; CT scanning; image reconstruction and artifacts correction; segmentation, filtering and analysis. 6. Overview of advanced topics: 4D X-ray CT; in-situ testing; digital volume correlation; laser speckle interferometry; dynamic testing and high-speed cameras. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Voraussetzungen / Besonderes | Prerequisites: Mechanics 1 and 2, Physics. Introduction to fracture mechanics is highly recommended. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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 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 robotics are emerging fields taking inspiration from nature to create robots that are inherently safer to interact with. You learn how to create structures, actuators, sensors, models, controllers, and machine learning architectures exploiting the deformable nature of soft robots. You also learn how to apply soft robotic principles to challenges of your research domain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Learning Objective 1: Solve a robotics challenge with a soft robotic design Step 1: Formulate suitable functional requirements for the challenge Step 2: Select soft robotic actuator material Step 3: Design and fabrication approach suitable for the challenge Step 4: Basic controller for robotic functionality Learning Objective 2: Formulate modeling, control, and learning frameworks for highly articulated robots in real-life scenarios Step 1: Formulate the dynamic skills needed for the real-life scenario Step 2: Pick + combine suitable multiphysics modeling, control + learning techniques for this scenario Step 3: Evaluate the modeling/control approach for a real-life scenario Step 4: Modify and enhance the modeling/control approach and repeat the evaluation Step 5: Choose a learning approach for complex robotic skills Learning Objective 3: Apply the principles of mechanical impedance and embodied intelligence to soft robotic challenges in various domains 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 a suitable performance under real-world conditions Learning Objective 4: Rethink robotic approaches 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 suitably highlights your new approach | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Students will learn about the latest research advances in material technologies, fabrication, modeling, and machine learning to design, simulate, build, and control 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 Regular assignments throughout the semester will teach the participants to implement the skills and knowledge learned during the class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | All class materials including slides, recordings, assignments, pre-reads, and tutorials can be found on the Moodle page of the class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | 1) Yasa et al. "An Overview of Soft Robotics." Annu. Rev. Control Robot. Auton. Syst. (2023). 6:1–29. 2) Polygerinos 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) Cianchetti, et al. "Biomedical applications of soft robotics." Nature Reviews Materials 3.6 (2018): 143-153. 4) Ricotti et al. "Biohybrid actuators for robotics: A review of devices actuated by living cells." Science Robotics 2.12 (2017). 5) Sun et al. "Biohybrid robotics with living cell actuation." Chemical Society Reviews 49.12 (2020): 4043-4069. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | - Prerequesites are dynamics, controls, and intro to robotics. - Only for students at master or PhD level. - Due to the limited places, the priority goes first to students from the Robotics, Systems and Control Master and second to the other study programs where the course is offered. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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 | W | 3 KP | 3G | T. Haslwanter | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 travel from Linz, Austria, to Zurich to give this lecture, I plan to hold this lecture online 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-2023/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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 252-0220-00L | Introduction to Machine Learning 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) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Designed to provide a basis for following courses: - Advanced Machine Learning - Deep Learning - Probabilistic Artificial Intelligence - Seminar "Advanced Topics in Machine Learning" | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 252-0312-00L | Mobile Health and Activity Monitoring | W | 6 KP | 2V + 3A | C. Holz | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Health and activity monitoring has become a key purpose of mobile & wearable devices, e.g., phones, watches, and rings. We will cover the phenomena they capture, i.e., user behavior, actions, and human physiology, as well as the sensors, signals, and methods for processing and analysis. For the exercise, students will receive a wristband to stream and analyze activity and health signals. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The course will combine high-level concepts with low-level technical methods needed to sense, detect, and understand them. High-level: – sensing modalities for interactive systems – "activities" and "events" (exercises and other mechanical activities such as movements and resulting vibrations) – health monitoring (basic cardiovascular physiology) – affective computing (emotions, mood, personality) Lower-level: – sampling and filtering, time and frequency domains – cross-modal sensor systems, signal synchronization and correlation – event detection, classification, prediction using basic signal processing as well as learning-based methods – sensor types: optical, mechanical/acoustic, electromagnetic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Health and activity monitoring has become a key purpose of mobile and wearable devices, including phones, (smart) watches, (smart) rings, (smart) belts, and other trackers (e.g., shoe clips, pendants). In this course, we will cover the fundamental aspects that these devices observe, i.e., user behavior, actions, and physiological dynamics of the human body, as well as the sensors, signals, and methods to capture, process, and analyze them. We will then cover methods for pattern extraction and classification on such data. The course will therefore touch on aspects of human activities, cardiovascular and pulmonary physiology, affective computing (recognizing, interpreting, and processing emotions), corresponding lower-level sensing systems (e.g., inertial sensing, optical sensing, photoplethysmography, eletrodermal activity, electrocardiograms) and higher-level computer vision-based sensing (facial expressions, motions, gestures), as well as processing methods for these types of data. The course will be accompanied by a group exercise project, in which students will apply the concepts and methods taught in class. Students will receive a wearable wristband device that streams IMU data to a mobile phone (code will be provided for receiving, storing, visualizing on the phone). Throughout the course and exercises, we will collect data of various human activities from the band, annotate them, analyze, classify, and interpret them. For this, existing and novel processing methods will be developed (plenty of related work exists), based on the collected data as well as existing datasets. We will also combine the band with signals obtained from the mobile phone to holistically capture and analyze health and activity data. Full details: https://teaching.siplab.org/mobile_health_activity_monitoring/2023/ Note: All lectures will be streamed live and recorded for later replay. Hybrid participation will be possible. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Copies of slides will be made available Lectures will be streamed live as well as recorded and made available online. More information on the course site: https://teaching.siplab.org/mobile_health_activity_monitoring/2023/ Note: All lectures will be streamed live and recorded for later replay. Hybrid participation will be possible. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Will be provided in the lecture | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 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, Sequenzanalyse 4. Funktionen, Module, Simulationen und Animationen 5. Matrizen, Zufallsexperimente, 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. Begleitunterlagen zum Onlinekurs und zur Vorlesung, 2022. ISBN: 978-3-7562-1004-6. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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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| 151-0638-00L | MaP Distinguished Lecture Series on Engineering with Living Materials This course is primarily designed for MSc and doctoral students. Guests are welcome. Former title: MaP Distinguished Lecture Series on Soft Robotics | W | 1 KP | 2S | R. Katzschmann, M. Filippi, X.‑H. Qin, Z. Zhang | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course is an interdisciplinary colloquium on the engineering of biohybrid systems and robotics. Internationally renowned speakers from academia and industry give lectures about their cutting-edge research, which highlights the state-of-the-art and frontiers in the field of engineering with living materials and biohybrids. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Participants become acquainted with the state-of-the-art and frontiers in biohybrid systems and 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 speakers from academia and industry who present their cutting-edge research in the field of engineered systems using living materials. In particular, the course will cover fundamentals of bioengineering at a multicellular level (biofabrication), as well as examples of manufacturing and application of living cells to engineered systems for medical applications and beyond. Speakers will show how to combine living cells with non-living, synthetic materials to realize bio-hybrid systems to be applied to many fields of human life, ranging from biomedicine to robotics, biosensing, ecology, and architecture. It will be shown how bio-hybrid technologies and cutting-edge engineering techniques can support cell proliferation and even enhance their cell functions. The course will cover materials and approaches for the biofabrication of living tissue, seen as a biomedical model for pathophysiological discovery research, or as transplantable grafts for tissue regeneration. Speakers will illustrate how living species can contribute to ecological approaches in town planning (such as CO2 sequestration), sensing and processor technologies enabled by connective and signaling abilities of cells, and motile systems actuated by contractile cells (bio-hybrid robots). The main learning objective is to learn about: materials and techniques to build intelligent biological systems for future, sustainable societies; mechanisms of cell and tissue programmability; and applications in bio-robotics, communication, sensing technologies, and medical engineering. The self-study of relevant pre-read literature provided in advance of each lecture serves as a basis for active participation in the critical discussions following each presentation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Selected scientific pre-read literature (around two articles per lecture) relevant for and discussed during the lectures is posted in advance on the course web page. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | This course is taught by a selection of internationally renowned speakers from academia and industry working in the field of bio-hybrid systems and robotics. This lecture series is focusing on the recent trends in engineering with living materials. Participants should have a background in tissue engineering, material science, and/or robotics. To obtain credits, students need to: (i) attend 80% of all lectures; (ii) submit a one-page abstract of 3 different lectures. The performance will be assessed with a "Pass/Fail" format. On-site attendance to the lectures is preferred to foster in-person contacts. However, for lectures given by online speakers, a Zoom link to attend remotely will be provided on Moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-1130-00L | Digital Health in Practice (University of Zurich) Findet dieses Semester nicht statt. No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: 04SM22MAS100 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html | W | 4 KP | 2V | Uni-Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Today, we face the challenge of chronic conditions. Personal coaching approaches are neither scalable nor financially sustainable. The question arises, therefore, to which degree Digital Health Interventions (DHIs) are appropriate to address this challenge. In this lecture, students will learn about the need for, as well as the design, implementation, and assessment of DHIs. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | • To understand the importance of digital health interventions for the prevention, management, and treatment of non-communicable diseases and common mental disorders • To discuss the opportunities and challenges of digital health interventions (e.g., data collection with wearables, smartphone- and chatbot-delivered health interventions) • To gain hands-on experience in the conceptual design, implementation and evaluation of a wearable- and smartphone-based digital health intervention | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Fitbits detect lasting changes after Covid-19 (New York Times, 2022), The promise of the metaverse in cardiovascular health (European Heart Journal, 2022), Can Virtual Reality Help Ease Chronic Pain? (The New York Times Magazine, 2022), First of its Kind Alexa Experience Provides Hands-Free Access at Home to General Medical Care (GlobeNewswire, 2022), Can digital technologies improve health? (The Lancet, 2021), Predictive analytics and tailored interventions improve clinical outcomes (npj Digital Medicine, 2021), Q1 2022 Digital Health Funding Reaches $6B Across 183 Deals (Rock Health, 2022). Digital health applications use information, sensor and communication technology to understand, prevent, manage, or treat diseases. The design of these applications requires interdisciplinary expertise at the intersection of medicine, psychology, computer science, technology, management, economics, and law. Only a close collaboration between experts from these disciplines and a specific target population can lead to a shared understanding of the problem at hand and, as a result, highly effective digital health applications. For this reason, national and international students studying computer science, business informatics, psychology, management, economics, or law are invited to work collaboratively with medical students. Digital health applications and companies have the goal of advancing health care services to fight the ongoing increase of non-communicable diseases (NCDs) and common mental disorders (CMDs) in developed countries. To this end, the question arises of how to develop evidence- based digital health interventions (DHI) that allow medical doctors and other caregivers to scale and tailor long-term treatments to individuals in need at sustainable costs. Through input lectures and practical applications, this module has, therefore, the objective to help students to better understand the need, design, implementation, and evaluation of DHIs. The following topics are covered: 1. DHIs for the prevention, management, and treatment of NCDs and CMDs 2. Strategies for long-term compliance with DHI 3. Conceptual design of a wearable- and smartphone-based DHI 4. Technical implementation of a wearable- and smartphone-based DHI 5. Evaluation of a wearable- and smartphone-based DHI | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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, C. E. Awai | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 carry out a small project including planing, measurement set-up, analysis and discussion. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 work on their own project, develop their own models for different sport types, critically discuss the advantages and disadvantages and evaluate applicable measurement methods. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Handout will be distributed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 376-1308-00L | Development Strategies for Medical Implants | W | 3 KP | 2V + 1U | J. Mayer-Spetzler, N. Mathavan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Introduction to development strategies for implantable devices considering the interdependencies of biocompatibility, clinical, regulatory, and economical requirements; discussion of state of the art and actual trends in orthopedics, sports medicine, cardiovascular surgery, and regenerative medicine (tissue engineering). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Primary considerations in implant development. Concept of structural and surface biocompatibility and its relevance for implant design and surgical technique. Understanding conflicting factors, e.g., clinical need, economics, and regulatory requirements. Tissue engineering concepts, their strengths, and weaknesses as current and future clinical solutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Understanding of clinical and economic needs as guidelines 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 state-of-the-art and actual trends in implant development in sports medicine, spinal and cardio-vascular surgery; introduction to tissue engineering. Commented movies from surgeries will further illustrate selected topics. Seminar: Group seminars on selected controversial topics in implant development. Participation is mandatory. Planned excursions (limited availability, not mandatory, to be confirmed): Participation (as a visitor) in a life surgery (travel at own expense) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Script (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's students; achieved Bachelor's degree is a pre-condition Admission to the lecture is based on a letter of motivation to the lecturer J. Mayer. 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 the student's responsibility. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1620-00L | Skeletal Repair | W | 3 KP | 3G | S. Grad, M. D'Este, F. Moriarty, M. Stoddart | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course gives an introduction into traumatic and degenerative pathologies of skeletal tissues. Emphasis is put on bone, cartilage and intervertebral disc. Established and new treatments are described, including cell, gene and molecular therapy, biomaterials, tissue engineering and infection prevention. In vitro/in vivo models are explained. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The objectives of this course are to acquire a basic understanding of (1) important pathologies of skeletal tissues and their consequences for the patient and the public health (2) current surgical approaches for skeletal repair, their advantages and drawbacks (3) recent advances in biological strategies for skeletal repair, such as (stem) cell therapy, gene therapy, biomaterials and tissue engineering (4) pathology, prevention and treatment of implant associated infections (5) in vitro and in vivo models for basic, translational and pre-clinical studies | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | According to the expected background knowledge, the cellular and extracellular composition and the structure of the skeletal tissues, including bone, cartilage, intervertebral disc, ligament and tendon will briefly be recapitulated. The functions of the healthy tissues and the impact of acute injury (e.g. bone fracture) or progressive degenerative failure (e.g. osteoarthritis) will be demonstrated. Physiological self-repair mechanisms, their limitations, and current (surgical) treatment options will be outlined. Particular emphasis will be put on novel approaches for biological repair or regeneration of critical bone defects, damaged hyaline cartilage of major articulating joints, and degenerative intervertebral disc tissues. These new treatment options include autologous cell therapies, stem cell applications, bioactive factors, gene therapy, biomaterials or biopolymers; while tissue engineering / regenerative medicine is considered as a combination of some of these factors. In vitro bioreactor systems and in vivo animal models will be described for preclinical testing of newly developed materials and techniques. Bacterial infection as a major complication of invasive treatment will be explained, covering also established and new methods for its effective inhibition. Finally, the translation of new therapies for skeletal repair from the laboratory to the clinical application will be illustrated by recent developments. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Basic knowledge in the cellular and molecular composition, structure and function of healthy skeletal tissues, especially bone, cartilage and intervertebral disc are required; furthermore, basic understanding of biomaterial properties, cell-surface interactions, and bacterial infection are necessary to follow this course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1719-00L | Statistics for Experimental Research | W | 3 KP | 2V | R. van de Langenberg | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Students will learn the necessary statistical concepts and skills to independently (1) design experiments (2) analyse experimental data and (3) report analyses and results in a scientifically appropriate manner. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | After successful completion of the course, students should be able to: 1. Determine appropriate experimental designs and choose, justify and perform the appropriate statistical analyses using R. 2. Report analyses and results in a scientifically appropriate manner, as laid out by the Publication Manual of the American Psychological Association (APA, sixth edition). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | We will cover basic statistical concepts (e.g., central tendency, variability, data distribution), the t-test (dependent and independent), ANOVA (univariate, factorial and repeated measures), correlation, multiple regression, nonparametric techniques, validity and reliability tests, effect size, data transformation, power and sample size estimation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Lecture notes will be delivered in the form of commented presentations in Microsoft Powerpoint (i.e. pptx) format. R practical session assignments will be delivered in pdf-format. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Both in the lectures and in the tutorials and practical sessions, we will refer students to the following publication: Field A, Miles J, Field Z (2013) Discovering Statistics Using R. Sage Publications Ltd, London, UK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 376-1721-00L | Bone Biology and Consequences for Human Health | W | 2 KP | 2V | G. A. Kuhn, J. Goldhahn, E. Wehrle | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Bone is a complex tissue that continuously adapts to mechanical and metabolic demands. Failure of this remodeling results in reduced mechanic stability ot the skeleton. This course will provide the basic knowledge to understand the biology and pathophysiology of bone necessary for engineering of bone tissue and design of implants. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | After completing this course, students will be able to understand: a) the biological and mechanical aspects of normal bone remodeling b) pathological changes and their consequences for the musculoskeletal system c) the consequences for implant design, tissue engineering and treatment interventions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Bone adapts continuously to mechanical and metabolic demands by complex remodeling processes. This course will deal with biological processes in bone tissue from cell to tissue level. This lecture will cover mechanisms of bone building (anabolic side), bone resorption (catabolic side), their coupling, and regulation mechanisms. It will also cover pathological changes and typical diseases like osteoporosis. Consequences for musculoskeletal health and their clinical relevance will be discussed. Requirements for tissue engineering as well as implant modification will be presented. Actual examples from research and development will be utilized for illustration. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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