Graduate Course Descriptions

The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

5000. Physiological Systems I

3.00 credits

Prerequisites: Recommended preparation: BME 3100.

Grading Basis: Graded

Eleven major human organ systems are covered in this course, including: integumentary, endocrine, lymphatic, digestive, urinary, reproductive, circulatory, respiratory, nervous, skeletal, and muscular.

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5010. Research Methods in Biomedical Engineering

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Inquiry into the nature of research with emphasis on the spirit, logic, and components of the scientific methods. Health related research literature is used to aid the student in learning to read, understand, and critically analyze published materials. The preparation of research proposals and reports is emphasized.

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5020. Clinical Engineering Fundamentals

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Provides the fundamental concepts involved in managing medical technology, establishing and operating a clinical engineering department, and the role of the clinical engineering designing facilities used in patient care. Topics covered include managing safety programs, technology assessment, technology acquisition, the design of clinical facilities, personnel management, budgeting and ethical issues of concern to the clinical engineer.

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5030. Human Error and Medical Device Accidents

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Basic principles needed to analyze medical devices, medical device users, medical device environments and medical device accidents. It particularly focuses on human factors engineering as an important step to minimizing human error. The role of medical device manufacturers, medical device regulators and medical device owners are examined to identify their role in reducing medical device use errors and medical device accidents. The nature and types of human error as well as a taxonomy of medical device accidents are presented. Investigative techniques involving root cause analysis and failure modes and effects analysis are taught and applied to industrial and medical device accidents. Operating room fires, electrosurgical and laser burns, anesthesia injuries, infusion device accidents, catheters and electrode failures and tissue injury in the medical environment are in detail. A semester project will require the student to employ these tools and techniques to analyze a medical device accident.

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5040. Medical Instrumentation in the Hospital

3.00 credits

Prerequisites: None.

Grading Basis: Graded

This course will examine current major technologies in use by healthcare practitioners. It will review the physiological principles behind each technology, the principles of operation, major features, methods for testing and evaluating each technology and will highlight available versions of the devices on the market today. Technologies to be covered will be selected from anesthesia equipment, surgical and ophthalmic lasers, cardiac assist devices, surgical & endoscopic video systems, radiographic and fluoroscopic devices, CT, MRI, ultrasound imaging equipment, radiation therapy, nuclear medicine, clinical chemistry analyzers, spectrophotometers and hematology analyzers. Course is based on one text, selected manufacturers training documents as well as journal articles from current medical publications. Grading will be based on exams, quizzes, a semester project and class participation. Several classes will take place on site in Hartford area hospitals in order to observe and examine the equipment being discussed.

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5050. Engineering Problems in the Hospital

3.00 credits

Prerequisites: Instructor consent; open to students in the M.S. Biomedical Engineering Clinical Engineering Internship Program or the M.Eng. Clinical Engineering Program.

Grading Basis: Graded

Covers engineering solutions to problems that are found in the healthcare environment. Includes a wide variety of topics such as electrical power quality of and the reliable operation of high tech medical equipment, electrical safety in the patient care environment, electromagnetic compatibility of various medical devices and electromagnetic interference, radiation shielding and radiation protection, medical gas systems, medical ventilation systems and indoor air quality, fire protection systems required in the hospital, project management, functionality and design implications of emerging technologies, and hospital architecture and the design of patient care facilities.

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5060. Clinical Engineering Rotations I

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Associated with the clinical engineering rotations that interns experience in hospitals, such as surgeries, CT, MRI, ICU, clinical laboratory and physical therapy.

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5061. Clinical Engineering Rotations II

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Associated with the clinical engineering rotations that interns experience in hospitals, such as surgeries, CT, MRI, ICU, clinical laboratory and physical therapy.

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5070. Clinical Systems Engineering

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Primarily covers medical device connectivity and interoperability. This includes connecting medical devices to the hospital computer network to pass data to the patient medical record or to other medical devices for the purpose of feedback and control. The course will cover basic networking concepts, hospital network architecture, medical systems security and risk management, the role of interconnecting middleware, HL7 and DICOM data standards, moving data on the network, clinical information systems, digital imaging and image storage systems, medical device plug-and-play concepts, and a medical device integration project walkthrough.

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5080. Medical Device Cybersecurity

3.00 credits

Prerequisites: Instructor consent.

Grading Basis: Graded

Today’s medical devices are increasingly complex, integrated, and ubiquitous. However, these same characteristics increasingly expose medical devices to a growing number of cyber security risks. Compounding the challenge, safeguards that are appropriate for traditional IT equipment cannot easily be applied to medical devices. This course is designed to provide health technology professionals with an overview of the challenges and foundational knowledge on the topic of medical device security. The course will also offer specific guidance, skill sets, and tools appropriate for those professionals that can be used in mitigating security risks that exist in the expanding medical device ecosystem.

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5099. Independent Study

1.00 - 3.00 credits | May be repeated for a total of 18 credits.

Prerequisites: None.

Grading Basis: Graded

Individual exploration of special topics as arranged by the student with an instructor of his or her choice.

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5100. Physiological Modeling

3.00 credits

Prerequisites: Recommended preparation: BME 3100 and 3400 (or equivalent).

Grading Basis: Graded

Unified study of engineering techniques and basic principles in modeling physiological systems. Focuses on membrane biophysics, biological modeling, and systems control theory. Significant engineering and software design is incorporated in homework assignments using MATLAB and SIMULINK.

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5150. Dynamical Modeling of Biochemical Networks

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Recent advances in biological measurement technology have opened up a new era in quantitative biology. Part of this revolution is the new field of systems biology, which consists of viewing processes in biological cells as a whole, rather than considering one gene or protein at a time. Systems biology relies heavily on mathematical models of cellular processes, often derived from the microscopic laws of chemical and enzyme kinetics. Focus primarily on continuum (differential equation) models of cellular processes arising from these microscopic laws. Because most of these models wind up being nonlinear, time is devoted to learning techniques to analyze systems of nonlinear ordinary differential equations, and we will explore the fundamental differences between linear and nonlinear systems. Biological applications will include modeling observed error rates in protein translation, using system nonlinearities to design biological toggle switches, and exploring biological motifs that lead to oscillations, switches, and other behaviors.

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5210. Biomedical Optics: Tissue Optics, Instruments and Imaging

3.00 credits

Prerequisites: PHYS 1502Q and ECE 3101.

Grading Basis: Graded

Principles and imaging of biomedical optics. Optical absorption, scattering and their biological origins, radiative transfer equation and diffusion theory, diffuse optical tomography, Monte Carlo modeling and photon transport in biological tissue, ballistic light imaging, time domain, frequency domain and continuous light measurement systems, optical coherence tomography, and photoacoustic tomography.

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5302. Biochemical Engineering for Biomedical Engineers

3.00 credits

Prerequisites: Not open to students who have passed BME 3300.

Grading Basis: Graded

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

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5320. Biosensors and Nanodevices for Biomedical Applications

3.00 credits

Prerequisites: Open only to Biomedical Engineering majors, others by instructor consent. Not open for credit to students who have passed BME 3320, 4985 or 6086 when taught as "Biosensors and Nanodevices for Biomedical Applications."

Grading Basis: Graded

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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5339. Introductory Ergonomics for Biomedical Scientists and Engineers

3.00 credits

Prerequisites: BME 5600. Recommended preparation: BME 3600, CE 3110.

Grading Basis: Graded

This problem-based course begins with a work-related overview of the design strengths and limitations of human anatomy and physiology (molecular, tissue and systems levels) and the contribution of work/worker mismatches to the development of disease. Measurement of the response of these biological tissues and systems to work-related stressors is examined, to define the mechanism and presentation of musculoskeletal disorders. Addresses physiological and anatomical damage due to biomechanical, psychosocial and work organization stressors and explores the range of possible control strategies of interest to the engineer and public health practitioner. To measure presence and levels of risk factors, students will be introduced to the use of laboratory techniques (e.g., EMG, digital motion capture, force cells) as well as field methods used in ergonomic work-site assessment, ranging from simple check-lists (geared towards worker-based interventions), through detailed time/motion studies, self-report effort scales, epidemiological instruments, and psychosocial and organizational measurement tools. A research project is required.

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5341. Exposure Assessment in Ergonomics

3.00 credits

Prerequisites: BME 5339.

Grading Basis: Graded

The goal of the course is to develop a broad understanding of ergonomic risk factors, knowledge of the measurement modalities available for characterizing workplace risk, and an appreciation of the advantages and disadvantages of each modality. Students will be introduced to the use of laboratory techniques (EMG, videotaping and digitization, digital motion capture, force cells, accelerometry and exercise physiology). They will also be instructed in methods used in ergonomic work-site assessment, ranging from simple checklists (geared towards worker-based interventions), through detailed time/motion studies, self-report effort scales, epidemiological instruments, and psychosocial and organizational measurement tools. The grade will depend on completion of a laboratory-based, field or epidemiological project.

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5500. Clinical Instrumentation Systems

3.00 credits

Prerequisites: Recommended preparation: ECE 2001W; BME 3400 and 3500.

Grading Basis: Graded

Analysis and design of transducers and signal processors; measurements of physical, chemical, biological, and physiological variables; special purpose medical instruments, systems design, storage and display, grounding, noise, and electrical safety. These concepts are considered in developing devices used in a clinical or biological environment.

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5520. Developing Mobile Apps for Healthcare

3.00 credits

Prerequisites: Recommended preparation: A laptop with at least 8G memory is needed for the class.

Grading Basis: Graded

Mobile apps for smartphones and tablets are changing the way doctors and patients approach health care. This course will cover the basic elements of apps development on Android platforms, including XML, Java, UI amongst others. Topics include how to handle 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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5600. Human Biomechanics

3.00 credits

Prerequisites: Recommended preparation: BME 3600W.

Grading Basis: Graded

Applies principles of engineering mechanics in the examination of human physiological subsystems such as the musculoskeletal system and the cardiovascular system. Topics drawn for biosolid mechanics, biofluids, and biodynamics, the viscoelastic modeling of muscle and bone, non-Newtonian fluid rheology, blood flow dynamics, respiratory mechanics, biomechanics of normal and impaired gait, and sport biomechanics.

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5630. Multiphysics Finite Element Analysis

3.00 credits

Prerequisites: BME 3600 or instructor consent. Recommended preparation: course is designed for BME juniors and seniors who have taken BME 3600, and for graduate students with generic background in mechanics.

Grading Basis: Graded

Fundamentals of the finite element method (FEA) via hands-on experience of solving typical design problems in the multidisciplinary field of biomedical engineering, including mechanical structures, heat transfer, fluid flow and electrical field distribution. Emphasizes basic mathematical and physical principles underlying the FEA, general procedure of identifying and solving engineering problems using COMSOL Multiphysics FEA software, interpretation of FEA analysis results and evaluation of the quality of the numerical solution. Students are expected to demonstrate a basic understanding of the concepts and mathematical formulation of FEA, and possess the ability to apply FEA procedures in biomedical problems and technology development.

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5700. Biomaterials and Tissue Engineering

Also offered as: MEDS 5313, MSE 5700

3.00 credits

Prerequisites: Recommended preparation: BME 3700.

Grading Basis: Graded

A broad introduction to the field of biomaterials and 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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5800. Bioinformatics

3.00 credits

Prerequisites: Recommended preparation: BME 4800 or equivalent

Grading Basis: Graded

Advanced mathematical models and computational techniques in bioinformatics. Topics covered include genome mapping and sequencing, sequence alignment, database search, gene prediction, genome rearrangements, phylogenetic trees, and computational proteomics.

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6086. Special Topics In Biomedical Engineering

1.00 - 6.00 credits | May be repeated for a total of 30 credits.

Prerequisites: None.

Grading Basis: Graded

Classroom and/or laboratory courses in special topics as announced in advance for each semester.

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6094. BME Graduate Seminar

1.00 credits | May be repeated for a total of 10 credits.

Prerequisites: None.

Grading Basis: Graded

Presentations will be given by invited speakers from outside, faculty members, and student presenters on current research topics in biomedical engineering.

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6100. Neural Prostheses

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Advanced microelectrode technologies are well-positioned to drive the next generation neuromodulation and neural prostheses for treatment of neurological diseases such as profound hearing loss, spinal cord injury, brain-machine interfaces, and Parkinson’s disease. This course discusses key technical issues related to implantable neural prostheses, in particular, 3D microelectrode arrays that interface with individual neurons directly, in various stages of development, from proof-of-concept to translation toward clinical approval. Students will also learn to critique journal articles and to write their own NIH research proposal.

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6110. Computational Neuroscience

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Explores the function of single neurons and neural systems by the use of simulations on a computer. Combines lectures and classroom discussions with conducting computer simulations. The simulations include exercises and a term project.

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6120. Neuronal Information Processing and Sensory Coding

3.00 credits

Prerequisites: BME 5100. This course and ECE 6311 may not both be taken for credit.

Grading Basis: Graded

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. This course assumes a background in linear systems and feedback control system

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6125. Digital Image Processing

Also offered as: ECE 6125

3.00 credits

Prerequisites: Not open to students who have passed ECE 6125

Grading Basis: Graded

Problems and applications in digital image processing, two-dimensional linear systems, shift invariance, 2-D Fourier transform analysis, matrix Theory, random images and fields, 2-D mean square estimation, optical imaging systems, image sampling and quantization, image transforms, DFT, FFT, image enhancement, two-dimensional spatial filtering, image restoration, image recognition, correlation, and statistical filters for image detection, nonlinear image processing, and feature extraction.

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6126. Fundamentals of Optical Imaging

Also offered as: ECE 6126

3.00 credits

Prerequisites: Not open for credit to students who have passed BME 6126

Grading Basis: Graded

Learning optical imaging fundamentals. Topics include: review of two-dimensional linear system theory; scalar diffraction theory, wave optics, Fresnel and Fraunhofer diffraction; imaging properties of lenses; image formation; optical resolution in imaging, frequency analysis of optical imaging systems; imaging with coherent and incoherent sources, coherent transfer function; optical transfer function, point spread function, fundamentals of microscopy, two-dimensional spatial filtering; coherent optical information processing; frequency-domain spatial filter synthesis; holography.

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6140. Cellular Systems Modeling

3.00 credits

Prerequisites: BME 5600.

Grading Basis: Graded

Cellular response to drugs and toxins, as well as normal cell processes such as proliferation, growth and motility often involve receptor-ligand binding and subsequent intracellular processes. Focuses on mathematical formulation of equations for key cellular events including binding of ligands with receptors on the cell surface, trafficking of the receptor-ligand complex within the cell and cell signaling by second messengers. Background material in molecular biology, cell physiology, estimation of parameters needed for the model equations from published literature and solution of the equations using available computer programs are included. Examples from the current literature of cell processes such as response to drugs and proliferation will be simulated with the model equations.

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6143. Pattern Recognition and Neural Networks

Also offered as: ECE 6143

3.00 credits

Prerequisites: Not open to students who have passed BME 6143

Grading Basis: Graded

Review of probability and stochastic processes. Statistical pattern recognition. Nonlinear signal processing and feature extraction. Correlation filters. Metrics for pattern recognition. Baysian classifiers. Minimum probability of error processors. Supervised and unsupervised learning. Perception learning methods. Multilayer neural networks. Applications to security and encryption.

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6160. Computational Genomics

3.00 credits

Prerequisites: CSE 5800 or BME 5800.

Grading Basis: Graded

Advanced computational methods for genomic data analysis. Topics covered include motif finding, gene expression analysis, regulatory network inference, comparative genomics, genomic sequence variation and linkage analysis.

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6170. Nanomedicine: From Concepts to Applications

3.00 credits

Prerequisites: None.

Grading Basis: Graded

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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6180. Computational Foundations of Systems Biology

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Focuses on studying dynamic and intelligent features (e.g., adaptation and robustness) of biological systems such as gene networks. Emphasizes the tools and methods of computational systems biology come from other computation-oriented fields such as computational physics, digital signal processing, control engineering, and digital logic. Programming using MATLAB, LabVIEW, and C# in the context of modeling, analyzing, estimating, and controlling real biological systems. Through a variety of assignments and projects, students will obtain a deeper understanding of physical and engineering principles applied to biological systems. Students will also read and present journal articles on topics covered in class, which will expose them to interdisciplinary research and views.

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6190. Bioelectrical Signals in Neuronal Tissues

3.00 credits

Prerequisites: MATH 1132Q, 2410Q, or instructor consent.

Grading Basis: Graded

Neuronal tissues react to trigger signals such as electrical, mechanical, or chemical energy by generating action potentials, i.e., depolarization and repolarization of their membrane electrical potentials within ~1/1000 second. What underlies this rapid electrical event is the intricate timing of the opening and closing of ion channels, i.e., pore-forming transmembrane proteins that allow charged ions to pass through the lipid bilayer membrane. The overarching objective of this course is to help engineering students establish a top-down theoretical understanding of the nervous system, which are targets for biomedical devices like neuromodulators and stimulators to manage disease conditions. This course teaches the fundamentals of neuronal tissues by introducing the experimental observations and the integration of experimental evidence with quantitative modeling. The course is designed for BME seniors and for graduate students with a generic background in neuroscience and neurophysiology. Students are expected to demonstrate the ability to apply basic bioelectrical theories to solving relevant biomedical problems via engineering design and analysis.

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6400. Biomedical Imaging

3.00 credits

Prerequisites: Recommended preparation: BME 3400 or ECE 3111.

Grading Basis: Graded

Fundamentals of detection, processing and display associated with imaging in medicine and biology. Topics include conventional and Fourier optics, optical and acoustic holography, thermography, isotope scans, and radiology. Laboratory demonstrations will include holography and optical image processing. Assumes a background in linear systems.

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6420. Medical Imaging Systems

3.00 credits

Prerequisites: BME 5500 or BME 6500.

Grading Basis: Graded

This course covers imaging principles and systems of x-ray, ultrasound, optical tomography, magnetic resonance imaging, positron emission tomography.

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6450. Optical Microscopy and Bio-imaging

Also offered as: MEDS 6450

3.00 credits

Prerequisites: Not open to students who have passed MEDS 6450

Grading Basis: Graded

Presents the current state of the art of optical imaging techniques and their applications in biomedical research. The course materials cover both traditional microscopies (DIC, fluorescence etc.) that have been an integrated part of biologists' tool-box, as well as more advance topics, such as single-molecule imaging and laser tweezers. Four lab sessions are incorporated in the classes to help students to gain some hand-on experiences. Strong emphasis will be given on current research and experimental design.

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6500. Biomedical Instrumentation I

3.00 credits

Prerequisites: BME 5500 or consent of the instructor.

Grading Basis: Graded

Origins of bioelectric signals; analysis and design of electrodes and low noise preamplifiers used in their measurement. Statistical techniques applied to the detection and processing of biological signals in noise, including the treatment of nerve impulse sequences as stochastic point processes. Methods of identifying the dynamic proper ties of biosystems. Assumes a background in linear systems and electronics.

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6510. Biomedical Instrumentation Laboratory

3.00 credits

Prerequisites: None.

Grading Basis: Graded

Experimental investigation of electrodes, transducers, electronic circuits and instrumentation systems used in biomedical research and clinical medicine.

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6520. Biosensors

3.00 credits

Prerequisites: BME 5500 or consent of the instructor.

Grading Basis: Graded

Principles and design of acoustic imaging transducers, and force, pressure and hearing sensors. Covers also optical biosensors including oxygen monitoring sensors, glucose sensors and optical sensors used in imaging.

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6620. Biosolid Mechanics

3.00 credits

Prerequisites: BME 5600. Recommended preparation: BME 3600, CE 3110.

Grading Basis: Graded

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. Research paper. Topics may be modified slightly to accommodate student interests.

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6810. Machine Learning Methods for Biomedical Signal Analysis

3.00 credits

Prerequisites: Instructor consent; CSE 1010 and STAT 3025Q or equivalent. Not open for credit to students who have passed BME 4810.

Grading Basis: Graded

Acquire the basic machine learning concepts and tools that are necessary 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 machine learning projects and how to use advanced statistical tools and methods to classify data, infer predictions, and validate data-driven predictive models.

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