# Suchergebnis: Katalogdaten im Frühjahrssemester 2019

Biomedical Engineering Master | ||||||

Vertiefungsfächer | ||||||

Bioelectronics | ||||||

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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227-1032-00L | Neuromorphic Engineering II Information für UZH Studierende: Die Lerneinheit kann nur an der ETH belegt werden. Die Belegung des Moduls INI405 ist an der UZH nicht möglich. Beachten Sie die Einschreibungstermine an der ETH für UZH Studierende: Link | W | 6 KP | 5G | T. Delbrück, G. Indiveri, S.‑C. Liu | |

Kurzbeschreibung | This course teaches the basics of analog chip design and layout with an emphasis on neuromorphic circuits, which are introduced in the fall semester course "Neuromorphic Engineering I". | |||||

Lernziel | Design of a neuromorphic circuit for implementation with CMOS technology. | |||||

Inhalt | This course teaches the basics of analog chip design and layout with an emphasis on neuromorphic circuits, which are introduced in the autumn semester course "Neuromorphic Engineering I". The principles of CMOS processing technology are presented. Using a set of inexpensive software tools for simulation, layout and verification, suitable for neuromorphic circuits, participants learn to simulate circuits on the transistor level and to make their layouts on the mask level. Important issues in the layout of neuromorphic circuits will be explained and illustrated with examples. In the latter part of the semester students simulate and layout a neuromorphic chip. Schematics of basic building blocks will be provided. The layout will then be fabricated and will be tested by students during the following fall semester. | |||||

Literatur | S.-C. Liu et al.: Analog VLSI Circuits and Principles; software documentation. | |||||

Voraussetzungen / Besonderes | Prerequisites: Neuromorphic Engineering I strongly recommended | |||||

Wahlfächer der Vertiefung Diese Fächer sind für die Vertiefung in Bioelectronics besonders empfohlen. Bei abweichender Fächerwahl konsultieren Sie bitte den Track Adviser. | ||||||

Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |

151-0172-00L | Microsystems II: Devices and Applications | W | 6 KP | 3V + 3U | C. Hierold, C. I. Roman | |

Kurzbeschreibung | The students are introduced to the fundamentals and physics of microelectronic devices as well as to microsystems in general (MEMS). They will be able to apply this knowledge for system research and development and to assess and apply principles, concepts and methods from a broad range of technical and scientific disciplines for innovative products. | |||||

Lernziel | The students are introduced to the fundamentals and physics of microelectronic devices as well as to microsystems in general (MEMS), basic electronic circuits for sensors, RF-MEMS, chemical microsystems, BioMEMS and microfluidics, magnetic sensors and optical devices, and in particular to the concepts of Nanosystems (focus on carbon nanotubes), based on the respective state-of-research in the field. They will be able to apply this knowledge for system research and development and to assess and apply principles, concepts and methods from a broad range of technical and scientific disciplines for innovative products. During the weekly 3 hour module on Mondays dedicated to Übungen the students will learn the basics of Comsol Multiphysics and utilize this software to simulate MEMS devices to understand their operation more deeply and optimize their designs. | |||||

Inhalt | Transducer fundamentals and test structures Pressure sensors and accelerometers Resonators and gyroscopes RF MEMS Acoustic transducers and energy harvesters Thermal transducers and energy harvesters Optical and magnetic transducers Chemical sensors and biosensors, microfluidics and bioMEMS Nanosystem concepts Basic electronic circuits for sensors and microsystems | |||||

Skript | Handouts (on-line) | |||||

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 | Class notes and special papers will be distributed. | |||||

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. | |||||

151-0980-00L | 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. | |||||

227-0125-00L | Optics and Photonics | W | 6 KP | 2V + 2U | J. Leuthold | |

Kurzbeschreibung | This lecture covers both - the fundamentals of "Optics" such as e.g. "ray optics", "coherence", the "Planck law" or the "Einstein relations" but also the fundamentals of "Photonics" on the generation, processing, transmission and detection of photons. | |||||

Lernziel | A sound base for work in the field of optics and photonics will be given. | |||||

Inhalt | Chapter 1: Ray Optics Chapter 2: Electromagnetic Optics Chapter 3: Polarization Chapter 4: Coherence and Interference Chapter 5: Fourier Optics and Diffraction Chapter 6: Guided Wave Optics Chapter 7: Optical Fibers Chapter 8: The Laser | |||||

Skript | Lecture notes will be handed out. | |||||

Voraussetzungen / Besonderes | Fundamentals of Electromagnetic Fields (Maxwell Equations) & Bachelor Lectures on Physics. | |||||

227-0390-00L | Elements of Microscopy | W | 4 KP | 3G | M. Stampanoni, G. Csúcs, A. Sologubenko | |

Kurzbeschreibung | The lecture reviews the basics of microscopy by discussing wave propagation, diffraction phenomena and aberrations. It gives the basics of light microscopy, introducing fluorescence, wide-field, confocal and multiphoton imaging. It further covers 3D electron microscopy and 3D X-ray tomographic micro and nanoimaging. | |||||

Lernziel | Solid introduction to the basics of microscopy, either with visible light, electrons or X-rays. | |||||

Inhalt | It would be impossible to imagine any scientific activities without the help of microscopy. Nowadays, scientists can count on very powerful instruments that allow investigating sample down to the atomic level. The lecture includes a general introduction to the principles of microscopy, from wave physics to image formation. It provides the physical and engineering basics to understand visible light, electron and X-ray microscopy. During selected exercises in the lab, several sophisticated instrument will be explained and their capabilities demonstrated. | |||||

Literatur | Available Online. | |||||

227-0395-00L | Neural Systems | W | 6 KP | 2V + 1U + 1A | R. Hahnloser, M. F. Yanik, B. Grewe | |

Kurzbeschreibung | This course introduces principles of information processing in neural systems. It covers basic neuroscience for engineering students, experimental techniques used in studies of animal behavior and underlying neural mechanisms. Students learn about neural information processing and basic principles of natural intelligence and their impact on efforts to design artificially intelligent systems. | |||||

Lernziel | This course introduces - Methods for monitoring of animal behaviors in complex environments - Information-theoretic principles of behavior - Methods for performing neurophysiological recordings in intact nervous systems - Methods for manipulating the state and activity in selective neuron types - Methods for reconstructing the synaptic networks among neurons - Information decoding from neural populations, - Sensorimotor learning, and - Neurobiological principles for machine learning. | |||||

Inhalt | From active membranes to propagation of action potentials. From synaptic physiology to synaptic learning rules. From receptive fields to neural population decoding. From fluorescence imaging to connectomics. Methods for reading and manipulation neural ensembles. From classical conditioning to reinforcement learning. From the visual system to deep convolutional networks. Brain architectures for learning and memory. From birdsong to computational linguistics. | |||||

Voraussetzungen / Besonderes | Before taking this course, students are encouraged to complete "Bioelectronics and Biosensors" (227-0393-10L). As part of the exercises for this class, students are expected to complete a (python) programming project to be defined at the beginning of the semester. | |||||

227-0690-10L | Advanced Topics in Control (Spring 2019)New topics are introduced every year. | W | 4 KP | 2V + 2U | J. Warrington, A. Eichler | |

Kurzbeschreibung | Advanced Topics in Control (ATIC) covers advanced research topics in control theory and is jointly organised by Profs Dörfler, Lygeros, and Smith at the Automatic Control Lab in D-ITET. It is offered each Spring semester with the topic rotating from year to year. Repetition for credit is possible, with consent of the instructor. | |||||

Lernziel | During Spring 2019 the course will be taught by Dr Joe Warrington and Dr Annika Eichler, and will cover a range of topics in robust control and convex optimization. The course content and style is distinct from Control Systems II (CSII), which also includes some robust control, in that it is geared towards the most recent research in the field, has a substantial optimization theory component, and is partly assessed via a written report that offers an excellent opportunity to develop scientific writing skills. In contrast, CSII offers a greater focus on engineering practice and is assessed by exam. | |||||

Inhalt | An optimization based approach to robust control theory and applications. Topics will include: H-infinity and H-2 control design; structured-singular value analysis and synthesis; model reduction; convex optimization; semi-definite programming; and interior-point methods. | |||||

Skript | Copies of the projection slides are available for downloading via the course website. | |||||

Literatur | Relevant material will be made available on the course website, Link | |||||

Voraussetzungen / Besonderes | Control systems (227-0216-00L), Linear system theory (227-0225-00L), or equivalents, as well as sufficient mathematical maturity. | |||||

227-0966-00L | Quantitative Big Imaging: From Images to Statistics | W | 4 KP | 2V + 1U | K. S. Mader, 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. | |||||

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 Kevin Mader directly (Link). 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. | |||||

227-0973-00L | Translational Neuromodeling | W | 8 KP | 3V + 2U + 1A | K. Stephan | |

Kurzbeschreibung | This course provides a systematic introduction to Translational Neuromodeling (the development of mathematical models for diagnostics of brain diseases) and their application to concrete clinical questions (Computational Psychiatry/Psychosomatics). It focuses on a generative modeling strategy and teaches (hierarchical) Bayesian models of neuroimaging data and behaviour, incl. exercises. | |||||

Lernziel | To obtain an understanding of the goals, concepts and methods of Translational Neuromodeling and Computational Psychiatry/Psychosomatics, particularly with regard to Bayesian models of neuroimaging (fMRI, EEG) and behavioural data. | |||||

Inhalt | This course provides a systematic introduction to Translational Neuromodeling (the development of mathematical models for diagnostics of brain diseases) and their application to concrete clinical questions (Computational Psychiatry/Psychosomatics). The first part of the course will introduce disease concepts from psychiatry and psychosomatics, their history, and clinical priority problems. The second part of the course concerns computational modeling of neuronal and cognitive processes for clinical applications. A particular focus is on Bayesian methods and generative models, for example, dynamic causal models for inferring neuronal mechanisms from neuroimaging data, and hierarchical Bayesian models for inference on cognitive mechanisms from behavioural data. The course discusses the mathematical and statistical principles behind these models, illustrates their application to various psychiatric diseases, and outlines a general research strategy based on generative models. Lecture topics include: 1. Introduction to Translational Neuromodeling and Computational Psychiatry/Psychosomatics 2. Psychiatric nosology 3. Pathophysiology of psychiatric disease mechanisms 4. Principles of Bayesian inference and generative modeling 5. Variational Bayes (VB) 6. Bayesian model selection 7. Markov Chain Monte Carlo techniques (MCMC) 8. Bayesian frameworks for understanding psychiatric and psychosomatic diseases 9. Generative models of fMRI data 10. Generative models of electrophysiological data 11. Generative models of behavioural data 12. Computational concepts of schizophrenia, depression and autism 13. Model-based predictions about individual patients Practical exercises include mathematical derivations and the implementation of specific models or inference methods. In additional project work, students are required to use one of the examples discussed in the course as a basis for developing their own generative model and use it for simulations and/or inference in application to a clinical question. Group work (up to 3 students) is permitted. | |||||

Literatur | See TNU website: Link | |||||

Voraussetzungen / Besonderes | Knowledge of principles of statistics, programming skills (MATLAB or Python) | |||||

227-1046-00L | Computer Simulations of Sensory Systems | W | 3 KP | 2V + 1U | 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 (or Matlab). 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 Link | |||||

Literatur | Open source information is available as wikibook Link For good overviews I recommend: • 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. • 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. • P Wallisch, M Lusignan, M. Benayoun, T. I. Baker, A. S. Dickey, and N. G. Hatsopoulos. MATLAB for Neuroscientists, Academic Press, 2009. Compactly written, it provides a short introduction to MATLAB, as well as a very good overview of MATLAB’s functionality, focusing on applications in different areas of neuroscience. • 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. | |||||

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). | |||||

252-0220-00L | Introduction to Machine Learning Previously called Learning and Intelligent Systems. | W | 8 KP | 4V + 2U + 1A | A. Krause | |

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 - Probabilistic Graphical Models - Seminar "Advanced Topics in Machine Learning" | |||||

376-1217-00L | Rehabilitation Engineering I: Motor Functions | W | 4 KP | 2V + 1U | R. Riener, J. Duarte Barriga | |

Kurzbeschreibung | “Rehabilitation engineering” is the application of science and technology to ameliorate the handicaps of individuals with disabilities in order to reintegrate them into society. The goal of this lecture is to present classical and new rehabilitation engineering principles and examples applied to compensate or enhance especially motor deficits. | |||||

Lernziel | Provide theoretical and practical knowledge of principles and applications used to rehabilitate individuals with motor disabilities. | |||||

Inhalt | “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 (also communicational) disabilities. In general, one can distinguish orthotic and prosthetic methods to overcome these disabilities. Orthoses support existing but affected body functions (e.g., glasses, crutches), while prostheses compensate for lost body functions (e.g., cochlea implant, artificial limbs). In case of sensory disorders, the lost function can also be substituted by other modalities (e.g. tactile Braille display for vision impaired persons). The goal of this lecture is to present classical and new technical principles as well as specific examples applied to compensate or enhance mainly motor deficits. 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 by displaying the patient with a maximum amount of information in order to compensate his/her impairment. 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. Multi-modality and interactivity have the potential to increase the therapeutical outcome compared to classical rehabilitation strategies. 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. | |||||

Skript | Lecture notes will be distributed at the beginning of the lecture (1st session) | |||||

Literatur | Introductory Books Neural prostheses - replacing motor function after desease or disability. Eds.: R. Stein, H. Peckham, D. Popovic. New York and Oxford: Oxford University Press. Advances in Rehabilitation Robotics – Human-Friendly Technologies on Movement Assistance and Restoration for People with Disabilities. Eds: Z.Z. Bien, D. Stefanov (Lecture Notes in Control and Information Science, No. 306). Springer Verlag Berlin 2004. Intelligent Systems and Technologies in Rehabilitation Engineering. Eds: H.N.L. Teodorescu, L.C. Jain (International Series on Computational Intelligence). CRC Press Boca Raton, 2001. Control of Movement for the Physically Disabled. Eds.: D. Popovic, T. Sinkjaer. Springer Verlag London, 2000. Interaktive und autonome Systeme der Medizintechnik - Funktionswiederherstellung und Organersatz. Herausgeber: J. Werner, Oldenbourg Wissenschaftsverlag 2005. Biomechanics and Neural Control of Posture and Movement. Eds.: J.M. Winters, P.E. Crago. Springer New York, 2000. Selected Journal Articles Abbas, J., Riener, R. (2001) Using mathematical models and advanced control systems techniques to enhance neuroprosthesis function. Neuromodulation 4, pp. 187-195. Burdea, G., Popescu, V., Hentz, V., and Colbert, K. (2000): Virtual reality-based orthopedic telerehabilitation, IEEE Trans. Rehab. Eng., 8, pp. 430-432 Colombo, G., Jörg, M., Schreier, R., Dietz, V. (2000) Treadmill training of paraplegic patients using a robotic orthosis. Journal of Rehabilitation Research and Development, vol. 37, pp. 693-700. Colombo, G., Jörg, M., Jezernik, S. (2002) Automatisiertes Lokomotionstraining auf dem Laufband. Automatisierungstechnik at, vol. 50, pp. 287-295. Cooper, R. (1993) Stability of a wheelchair controlled by a human. IEEE Transactions on Rehabilitation Engineering 1, pp. 193-206. Krebs, H.I., Hogan, N., Aisen, M.L., Volpe, B.T. (1998): Robot-aided neurorehabilitation, IEEE Trans. Rehab. Eng., 6, pp. 75-87 Leifer, L. (1981): Rehabilitive robotics, Robot Age, pp. 4-11 Platz, T. (2003): Evidenzbasierte Armrehabilitation: Eine systematische Literaturübersicht, Nervenarzt, 74, pp. 841-849 Quintern, J. (1998) Application of functional electrical stimulation in paraplegic patients. NeuroRehabilitation 10, pp. 205-250. Riener, R., Nef, T., Colombo, G. (2005) Robot-aided neurorehabilitation for the upper extremities. Medical & Biological Engineering & Computing 43(1), pp. 2-10. Riener, R., Fuhr, T., Schneider, J. (2002) On the complexity of biomechanical models used for neuroprosthesis development. International Journal of Mechanics in Medicine and Biology 2, pp. 389-404. Riener, R. (1999) Model-based development of neuroprostheses for paraplegic patients. Royal Philosophical Transactions: Biological Sciences 354, pp. 877-894. | |||||

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 | |||||

376-1308-00L | 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, M. Rubert | |

Kurzbeschreibung | Introduction to development strategies for implantable devices considering the interdependecies of biocompatibility, clinical and economical requirements ; discussion of the state of the art and actual trends in in orthopedics, sports medicine, traumatology 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 | Biocompatibility as bionic guide line 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 orthopedics, sports medicine, traumatology, 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 | Achieved Bachelor degree is mandatory The number of participants in the course is limited to 25-30 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. | |||||

376-1397-00L | Orthopaedic Biomechanics Number of participants limited to 48. | W | 3 KP | 2G | R. Müller, P. Atkins | |

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 ILIAS. | |||||

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. | |||||

376-1614-00L | Principles in Tissue Engineering | W | 3 KP | 2V | K. Maniura, J. Möller, 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 | |||||

376-1712-00L | 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. | |||||

376-1724-00L | Appropriate Health System Design Maximale Teilnehmerzahl: 42 | W | 3 KP | 2V | W. Karlen | |

Kurzbeschreibung | This course elaborates upon relevant aspects in the conception, implementation and distribution of health devices and systems that effectively meet peoples and societies' needs in a local context. Four key elements of appropriateness (usage, cost, durability and performance) that are integral to the engineering design process are extensively discussed and applied. | |||||

Lernziel | The main goals are to > Evaluate the appropriateness of health systems to the cultural, financial, environmental and medical context in which they will be applied and > Design health systems from a user's perspective for a specific context At the end of the course, students can > name, understand and describe the 4 main principles that define appropriate technology > apply these principles to critically analyze and assess health systems and technology > project him/herself into a unfamiliar person and context and create hypotheses as to that person's needs, requirements, and priorities > modify specifications of existing systems to improve appropriateness > discuss the challenges and illustrate the the ethical and societal consequences of proposed design modifications > communicate effectively the results of his/her system analysis and implementation strategies to non-specialists | |||||

Inhalt | The course will be interactive and involve roleplay. Please do not sign up for this course if you are not ready to leave your comfort zone in class. The lectures are divided in two parts: The first part elaborates upon the important concepts of the design of health care devices and systems, and discusses implementation and dissemination strategies. We focus on communities such as low income households, the elderly, and patients with chronic illnesses that have special needs. Topics covered include point-of-care diagnostics, information and communication technologies, mobile health, user interactions, and also the social-cultural considerations. The second part consists of elaboration of an appropriate device conducted by student groups. Each group will analyse an existing product or solution, critically assess its appropriateness according to the criteria learned in class, and provide explanations as to why the system succeeds or fails. The students will also present design improvements. Grading will be based on a written case report due in the middle of the semester and a final seminar presentation in form of a poster discussion and demo. | |||||

Literatur | WHO, "Medical Devices: Managing the Mismatch", 2010. Link PATH, "The IC2030 report. Reimagining Global Health," 2015. Link R. Malkin and K. Von Oldenburg Beer, "Diffusion of novel healthcare technologies to resource poor settings," Annals of Biomedical Engineering, vol. 41, no. 9, pp. 1841:50, 2013. | |||||

Voraussetzungen / Besonderes | Target Group: Students of higher semesters and doctoral students of - D-MAVT, D-ITET, D-INFK, D-HEST - Biomedical Engineering, Robotics, Systems and Control - Medical Faculty, University of Zurich Students of other departments, faculties, courses are also welcome | |||||

376-1984-00L | Lasers in MedicineFindet dieses Semester nicht statt. | W | 3 KP | 3G | ||

Kurzbeschreibung | Fragen wie "Was ist ein Laser, wie funktioniert er und was macht ihn so interessant für die Medizin?", aber auch "Wie breitet sich Licht im Gewebe aus und welche Wechselwirkungen treten dabei auf?" sollen beantwortet werden. Speziell wird auf therapeutische, diagnostische und bildgebende Anwendungen anhand von ausgewählten Beispielen eingegangen. | |||||

Lernziel | Einführung in die für medizinische Anwendungen relevanten Lasertechniken. Vermittlung der physikalischen Grundlagen der Laser-Gewebe-Wechselwirkung mit dem Ziel, den Einfluss der unterschiedlichen Bestrahlungsparameter auf den Gewebeeffekt zu verstehen. Grundlagen der diagnostischen Laseranwendungen und der Lasersicherheit. | |||||

Inhalt | Die Anwendung des Lasers in der Medizin gewinnt zunehmend dort an Bedeutung, wo seine speziellen Eigenschaften gezielt zur berührungslosen, selektiven und spezifischen Wirkung auf Weich- und Hartgewebe für minimal invasive Therapieformen oder zur Eröffnung neuer therapeutischer und diagnostischer Methoden eingesetzt werden können. Grundlegende Arbeiten zum Verständnis der Lichtausbreitung im Gewebe (Absorptions-, Reflexions- und Transmissionsvermögen) und die unterschiedlichen Formen der Wechselwirkung (photochemische, thermische, ablative und optomechanische Wirkung) werden eingehend behandelt. Speziell wird auf den Einfluss der Wellenlänge und der Bestrahlungszeit auf den Wechselwirkungsmechanismus eingegangen. Die unterschiedlichen medizinisch genutzten Lasertypen und Strahlführungssysteme werden hinsichtlich ihres Einsatzes im Bereich der Medizin anhand ausgesuchter Anwendungsbeispiele diskutiert. Neben den therapeutischen Wirkungen wird auf den Einsatz des Lasers in der medizinischen Diagnostik (z.B. Tumor-Fluoreszenzdiagnostik, Bildgebung) eingegangen. Die beim Einsatz des Lasers in der Medizin erforderlichen Schutzmassnahmen werden diskutiert. | |||||

Skript | wird im Internet bereitgestellt | |||||

Literatur | - M. Born, E. Wolf, "Principles of Optics", Pergamon Press - B.E.A. Saleh, M.C. Teich, "Fundamentals of Photonics", John Wiley and Sons, Inc. - A.E. Siegman, "Lasers", University Science Books - O. Svelto, "Principles of Lasers", Plenum Press - J. Eichler, T. Seiler, "Lasertechnik in der Medizin", Springer Verlag - M.H. Niemz, "Laser-Tissue Interaction", Springer Verlag - A.J. Welch, M.J.C. van Gemert, "Optical-thermal response of laser-irradiated tissue", Plenum Press |

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