2101. Introduction to Biomedical Engineering

Fundamental concepts and techniques of engineering and medical science and their integration. The art and science of medicine and the process of medical diagnosis and treatment. Topics include: diagnostic instrumentation, diagnostic measurements and their interplay; bioelectric phenomena, biomechanics, and biomaterials; biochemical engineering; computers in medicine; molecular medicine and biotechnology; medical imaging.

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2193. International Study

Special Biomedical Engineering topics taken in an international study program. May be repeated for up to six credits with change in topic. May count toward the major with consent of the adviser and approved plan of study.

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3100. Physiological Modeling

Techniques for analysis and modeling of biomedical systems. Application of advanced mathematics (including Differential Equations, Laplace Transforms and Statistics) and computer-aided methods to study problems at the interface of engineering and biology. Elements of physiological modeling and the solution of the transient and forced response for a variety of biomechanical, biomaterial, bioelectrical and biochemical systems.

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3120. LabVIEW Basics for Engineers

Introduces LabVIEW programming environment. The fundamentals of using graphical programming to collect, analyze, display and store data are covered. Learn techniques for designing stand alone applications, creating interactive user interfaces and optimizing data flow.

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3193. International Study

Special Biomedical Engineering topics taken in an international study program. May be repeated for up to six credits with change in topic. May count toward the major with consent of the adviser and approved plan of study.

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3300. Biochemical Engineering for Biomedical Engineers

Introduction to chemical reaction kinetics; enzyme and fermentation technology; microbiology, biochemistry, and cellular concepts; biomass production; organ analysis; viral dynamics.

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3320. Biosensors and Nanodevices for Biomedical Applications

Current and emerging technologies in biosensors for biomedical applications. Topics include principles of molecular and bio/chemical sensing, techniques for sensor integration, nano/micro electro mechanical systems (NEMS/MEMS) technologies used in biosensors, and commercial/clinical applications of biosensors.

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3400. Biosystem Analysis

A lecture course that covers Fourier analysis, Laplace analysis and Z-transforms. Techniques for generating quantitative mathematical models of physiological control systems; the behavior of physiological control systems using both time and frequency domain methods.

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3401. Introduction to Computational and Systems Biology

Introduction to the role of computational and mathematical analyses in biological sequence (DNA, RNA, proteins) analysis and quantitative mathematical models of cell biological processes (systems and quantitative biology). Algorithms for sequence alignment, analysis of networks involved in transcription, development, and signal transduction. Programming in the Python language will be an integral part of the course, but no prior experience with Python is necessary.

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3420. Stem Cells for Regenerative Medicine

Introduces the fundamental concept and translational application of regenerative medicine such as stem cells, gene therapy, cell and tissue therapy. Topics include tissue-specific stem cells, embryonic stem cells, induced pluripotent stem cells and their potential therapeutic applications for musculoskeletal, cardiovascular and nervous systems.

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3500. Biomedical Engineering Measurements

A lecture and laboratory course that covers fundamentals of biomedical measurement and patient safety. Measurements of physical quantities by means of electronic instruments, mechanical devices and biochemical processes. Analysis of measurement systems using mathematical models. Methods of measuring signals in the presence of noise. Use of computers in measurement systems.

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3520. Developing Mobile Apps for Healthcare

Mobile apps are changing the way doctors and patients approach health care. Designed for use by doctors, patients or both, the apps available range from handy databases about drugs and diseases to sophisticated monitors that read a person's physiological signals. Students will learn the basic elements of apps development on Android platforms, including XML, and Java, UI amongst others. Topics include how to handle patient data in the cloud using HIPAA-Compliant web service and how to integrate machine learning models in app development. No previous programming experience is needed.

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3540. Principles of Biomedical Optical Sensing: A Laboratory-Based Course

Undergraduate laboratory course that covers the fundamental optical sensing principles of devices used in medicine and research. Topics include laser beam manipulation and forming, optical fibers and photodetectors, polarizers and polarimetry, molecular sensing, pressure mapping via FTIR, blood oxygen concentration (Pulse Oximetry), interferometric-based imaging systems and photo spectrometry. The course is designed for students’ who seek to acquire skills in handling and working with optical components.

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3600. Biomechanics

Application of solid mechanics theory to describe and analyze mechanical behaviors of biological tissues. Basic concepts in mechanics of materials, including the essential mathematics, kinematics of deformation and motion, stress, constitutive relations. Biomechanics principles; identifying, formulating and solving problems related to bone, cartilage, tendon, cardiac and vascular tissues. Introduction of experimental methods and computational modeling of biological tissues. A separate laboratory component will introduce students to experimental methods in more detail. Laboratory reports with revisions are required.

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3620. Failure Analysis for Biomedical Application

Study and analysis of the causes of material and device failures as it relates to biomedical engineering. Types of material failures and failure mechanisms. Discussion of appropriate material selection, design and application as it relates to mitigating failure risk. Case studies of historical material failures in biomedical engineering.

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3630. Multiphysics Finite Element Analysis

The course material emphasizes basic mathematical and physical principles underlying finite element analysis (FEA), general procedure of identifying and solving engineering problems using COMSOL Multiphysics FEA software, and interpretation of FEA results.

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3640. Human Factors Engineering

This course introduces students to the field of human factors engineering. Topics include user-centered design and the different tools available to anticipate and solve human-use issues.

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3700. Biomaterials

A lecture and laboratory course that introduces a series of implant materials including metals, ceramics, glass ceramics, polymers, and composites. These materials are compared with the natural materials, with consideration given to issues of mechanical properties, biocompatibility, degradation of materials by biological systems, and biological response to artificial materials. Particular attention is given to the materials for the total hip prosthesis, dental restoration, and implantable medical devices.

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3720. Drug Delivery

Introduction to drug delivery systems that provide pharmaceutical agents at target tissues, the mechanism of pharmacokinetic regulation, the basics, technology, and applications of drug delivery systems. Emphasis on understanding the principles of pharmacokinetics and drug delivery systems to improve clinical efficacy as well as to reduce side effects.

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3740. Introduction to Microscopy and Biophotonics

Basic principles of modern light microscopy and related biophotonics techniques. Matlab will be used to model various imaging platforms. Topics include geometrical optics; image processing in spatial and Fourier domain; lensless microscopy imaging; light scattering and absorption in tissue; wave propagation; coherent and incoherent imaging; lens-based imaging systems; optical aberrations; phase retrieval; brightfield, darkfield, phase-contrast, and confocal microscopy; holographic imaging; light field microscopy; 3D tomographic imaging; autofocusing for whole slide imaging; two-photon imaging; structured illumination and other super-resolution techniques; Fourier ptychographic imaging; detectors and photon transfer curve; image denoising via regularization; optical coherent tomography.

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3750. Tissue Engineering Laboratory

This is an undergraduate laboratory course designed to provide hands on training in tissue engineering methods and techniques. Students will learn the necessary skills required for culturing and maintaining cells to practice tissue engineering strategies. The students will also learn basic tissue engineering lab techniques and develop assays and staining methods related to the development and evaluation of in vitro tissue engineering products.

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3760. Microfluidics and Lab-on-Chip

The course provides a broad overview of microfluidics technology, lab-on-chip, wearable/implantable devices and smartphone-based optical sensing technology, and their biomedical applications. It also covers the fundamentals of micro/nano fabrication technologies and additive manufacturing (e.g., 3D printing). In addition, the basic principles of biology and chemistry, with a focus on how to integrate them into microfluidic devices and biomedical microsystems are introduced and discussed.

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3780. Introduction to Biomanufacturing: Pharmaceutical Proteins

This course provides an overview of the large scale bioprocessing and biomanufacturing of biopharmaceutical products (biologics). Topics include conventional versus biologic drug manufacturing, key phases in the process of drug manufacturing (bench to bottle), upstream and downstream operations, bioreactor design, purification process, safety and efficiency of biologics, quality assurance, regulation and introduction to Good Manufacturing Practices (GMP) in bio-manufacturing.

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3810. Computational Genomics

Computational methods for genomic data analysis. Topics covered include statistical modeling of biological sequences, probabilistic models of DNA and protein evolution, expectation maximization and Gibbs sampling algorithms, genomic sequence variation, and applications in genomics and genetic epidemiology.

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3900. Junior Design

Students work through a structured process that emulates an open-ended, real-world design of a biomedical engineering product. Project definition and product specifications, project scheduling and management, team interactions, failure and safety criteria, progress reporting, marketing concepts, ethical issues, prototype development, proper documentation and technical presentation of the final project outcomes. Includes a significant writing component, makes use of computers and design software, and involves hands-on design explorations. Students will complete a semester-long design project that demonstrates the skills and knowledge learned during the course in preparation for the capstone design experience.

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4120. Neural Information Processing and Sensory Coding

Processing, transmission, and storage of information in the central and peripheral nervous systems. Mechanisms of signal generation, transmission and coding by neurons and dendrites. Analysis of invertebrate and vertebrate visual and auditory systems, including: mechanisms of neurosensory transduction, coding, and signal-to-noise ratio enhancement. Neural spatio-temporal filters for feature extraction and pattern recognition. Information theoretic analysis of signal encoding and transmission in the nervous system. Assumes a background in linear systems and feedback control systems.

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4130. Neural Prostheses

Development of neural prostheses. Topics will cover physiology of neurological disorders, key concepts of neural prostheses, electrode designs and materials, fabrication methodologies, measurement techniques, histological evaluations, and clinical translations. Students will also learn to critique journal articles and to write their own NIH research proposal.

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4170. Nanomedicine: From Concepts to Applications

Teaches students competency and practical skills in applying nanotechnology to solve problems in medicine. Upon completion of the course, the students will be able to understand the basic concept of Nanomedicine and have an overview of the Nanomedicine field; understand principles and experimental methods in designing, generating, charactering and evaluating nanotechnology-enabled therapeutics; understand how Nanomedicine is translated from scientific innovation to clinical applications; understand how Nanomedicine is applied in the cutting-edge breakthroughs of biotechnology and medicine; develop critical thinking and independent learning skills; and design a successful Nanomedicine project.

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4201. Introduction to Medical Imaging

Introduction to spatial signals including spatial impulse response, spatial sampling and filtering, spatial Fourier transforms, and back projection. Principles, systems and clinical applications of X-ray, X-ray CT, ultrasound, Positron Emission Tomography (PET) and Single Photon Emission Tomography (SPECT), and MRI imaging.

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4300. Physiological Control Systems

Analysis of human physiological control systems and regulators through the use of mathematical models. Identification and linearization of system components. Systems interactions, stability, noise, and the relation of system malfunction to disease. The analysis and design of feedback systems to control physiological states through the automatic administration of drugs.

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4400. Dynamical Modeling of Biological Networks

Construction and analysis of biochemical pathway models. Mass action kinetics and the S-matrix formalism, nonlinear differential equations, bistability, bifurcations, linear stability analysis, and nonlinear oscillations. Possible applications include kinetic proofreading, classical enzyme kinetics, biological switches, and dynamical behavior of simple biochemical circuits.

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4401. Computational Foundations of Systems Biology

Introduction to computational systems biology, which focuses on studying the dynamic and intelligent features (e.g., adaptation and robustness) of biological systems. Through a variety of assignments and projects using MATLAB, LabVIEW and C#, students will obtain a deeper understanding of physical and engineering principles and methods (e.g., computational physics, digital signal processing, control engineering, and digital logic) applied to biological systems.

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4410. Systems Biology of Cells and Tissues

The course will present a broad systems level overview of how cells and tissues interact with each other at different physical scales to create complex physiological outcomes. In addition, it will cover a variety of techniques and experimental models in biology, as well as introduce examples to observe cells and tissues at multiple scales.

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4500. Bioinstrumentation

Modeling, analysis, design, and operation of transducers, sensors, and electrodes, for physiological systems; operational and instrumentation amplifiers for bioelectric event signal conditioning, interfacing and processing; A/D converters and hardware and software principles as related to sampling, storing, processing, and display of biosignals and digital computers.

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4520. Digital Image Processing for Biomedical Engineering

Fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. Principles and algorithms for processing both deterministic and random signals. Topics include ECG, image modalities, discrete Fourier transform, Fast Fourier transform, data acquisition, sampling, filtering, denosing, regularization, coding, feature extraction and modeling, image segmentation and registration, and machine learning. Includes the training of a neural network to classify images with different diseases.

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4560. Biomedical Signal Processing Laboratory

This course provides students the opportunity to develop skills to use computational methods in time- and frequency domains to analyze some of most commonly used biomedical signals such as ECG, photoplethysmogram (PPG), electromyogram (EMG), and electrodermal activity (EDA). All data analyses are performed using Matlab software.

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4600. Biosolid Mechanics

Mechanical behavior of biological solids. Applications of the theories of elasticity, viscoelasticity, and poroelasticity to bones, ligaments and tendons, skeletal muscle, and articular cartilage. Axial, bending, shearing and torsional loadings. Bone morphology and growth. Biphasic theory. Failure theories. Topics may be modified slightly to accomodate student interests.

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4701. Biomedical Materials and Implants

This advanced course will enable students to further expand their knowledge in various aspects of biomaterials science, engineering and applications. The course will focus on the strategies to improve cell-material and tissue-implant interaction. An emphasis is placed on the biomaterial innovations and technologies that integrate bioactivity, functionality to improve the performance of the implants. The course will also provide an overview of the FDA regulatory pathways for biomaterial and implant approvals.

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4710. Tissue Engineering

Presents basic principles of biological, medical, and material science as applied to implantable medical devices, drug delivery systems and artificial organs.

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4720. Cellular Engineering

Cellular engineering emphasizes the navigation and understanding of discoveries in stem cell, molecular, and developmental biology from an engineering perspective. Student projects and an active learning approach enable students to practice the complex and open-ended process of synthesizing and translating basic discoveries for the rational design of tissue regeneration therapies.

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4730. Biomicrofluidics, Biofabrication, and Biomanufacturing

This course is an introduction to the fundamentals of micro- and nanofabrication processes. In addition, transport phenomena in microfluidic systems, bioprinting and additive manufacturing technologies are discussed. Topics covered during the semester include microfabrication, non-conventional microfabrication, microfluidics, transport phenomena in miniaturized systems, microfluidic assisted manufacturing, bioprinting, biofabrication and organs-on-a-chip.

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4800. Bioinformatics

Fundamental mathematical models and computational techniques in bioinformatics. Exact and approximate string matching, suffix trees, pairwise and multiple sequence alignment, Markov chains and hidden Markov models. Applications to sequence analysis, gene finding, database search, phylogenetic tree reconstruction.

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4810. Machine Learning Methods for Biomedical Signal Analysis

The objective of this course is to learn the basic machine learning concepts and tools that are required in modern biomedical engineering to model, analyze, and classify physiological time series. Specific focus is on multivariate data and time series extracted from multiple physiological sources, including (but not limited to) ECG, EEG, and EMG. Through a mix of lectures and hands-on laboratory experiences, the students will learn how to design and implement a machine learning project, how to use advanced statistical tools and methods to classify data, infer predictions, and validate data-driven predictive models.

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4900. Biomedical Engineering Design I

Discussion of the design process; project statement, specifications project planning, scheduling and division of responsibility, ethics in engineering design, safety, environmental considerations, economic constraints, liability, manufacturing, and marketing. Projects are carried out using a team-based approach. Selection and analysis of a design project to be undertaken in BME 4910 is carried out. Written progress reports, a proposal, an interim project report, a final report, and oral presentations are required.

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4910W. Biomedical Engineering Design II

Design of a device, circuit system, process, or algorithm. Team solution to an engineering design problem as formulated in BME 4900, from first concepts through evaluation and documentation. Written progress reports, a final report, and oral presentation are required.

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4985. Special Topics in Biomedical Engineering

Classroom and/or laboratory courses in special topics as announced for each semester. With a change of topic, this course may be repeated for credit.

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4999. Independent Study

Independent study project carried on by the student under the guidance of a faculty member. The student is required to submit a report on the study at the end of the semester. With a change in content, this course may be repeated for credit.

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