This subject introduces important mathematical methods required in engineering such as manipulating vector differential operators, computing multiple integrals and using integral theorems. A range of ordinary and partial differential equations are solved by a variety of methods and their solution behaviour is interpreted. The subject also introduces sequences and series including the concepts of convergence and divergence.

Topics include: Vector calculus, including Gauss’ and Stokes’ Theorems; sequences and series; Fourier series, Laplace transforms; systems of homogeneous ordinary differential equations, including phase plane and linearization for nonlinear systems; second order partial differential equations and separation of variables.

AIMS:

This subject aims to introduce students to the use of computational modelling to apply biomechanical physics to problems in bioengineering research and industry. The course introduces students to important fundamentals of software programming (through the use of MATLAB) and numerical techniques to solving biomechanics equations. The course will introduce students to relevant applications in human movement, soft-tissue mechanics and cellular mechanobiology.

INDICATIVE CONTENT:

Topics include:

• Kinematics – displacement/velocity/acceleration relationships; speed vs velocity; linear and angular velocity.
• Forces, moments, free body diagrams, normal/shear stress and strain.
• Mechanics of materials – stress/strain relations, Young’s modulus, Poisson’s ratio.
• Newton’s laws.
• Deriving ODEs to solve simple dynamics problems – mass and spring; pendulum swing; projectile motion.
• Data structures/types in programs – variables, numbers, characters, arrays, strings, floating point, single and double precision (pointers).
• Writing programs – main program, functions, scope of variables in programs (whole-program vs function-specific variables).
• Control structures – if/else, for loops, while loops, do until loops.
• Numerical methods for solving linear ODEs.
• Approximation and errors in numerical computation.

AIMS

The main aim of this course is to introduce students to the basic concepts of the kinematics and dynamics of human motion and the architectural features and mechanical properties of musculoskeletal tissue. Tissue function is then illustrated in the context of normal and pathological movement.

INDICATIVE CONTENT

Specific topics covered include: Motion of a Rigid Body (reference frames, angular velocity, two points fixed on a rigid body); Measurement and Processing of Kinematic Data; Body Anthropometry (calculation of centre of mass and mass moment of inertia); Forces and Moments (moments of force, muscle moment arm, inverse dynamics analysis); Work, Energy, Power (kinetic energy, potential energy, elastic strain energy); Tissue Biomechanics (muscle, tendon, ligament, cartilage and bone); Orthopaedic Biomechanics: biomechanics of gait across the lifespan, biomechanical adaptations to training, knee osteoarthritis).

AIMS

This subject introduces students to the fundamental principles of circuit and signal measurements and analyses in a biosignals context. In addition to the fundamental concepts, topics to be covered include an introduction to various types of sensors and the basic methods required to analyse measurements, calibrate sensors and evaluate measurement system performance.

In the laboratories, students will learn about laboratory safety, team work and measurement safety in an integrated way.

This subject is one of the subjects that define the Bioengineering Systems Major in the Bachelor of Science and Bachelor of Biomedicine, and it is a core requirement for the Master of Engineering (Biomedical). It provides a foundation for various subsequent subjects, including BMEN90002 Neural Information Processing and BMEN90021 Medical Imaging.

INDICATIVE CONTENT

Topics include:

Basic principles of charge, current, Coulomb's law, electric fields and electrical energy, Kirchhoff's current law, Kirchhoff's voltage law, voltage and current division, node voltage analysis, mesh current analysis, Thévenin and Norton equivalent circuits, transient analysis of RC and RL circuits, steady-state analysis of RLC circuits, phasors and impedance, frequency domain models for signals and frequency response for systems, continuous-time and discrete-time Fourier transforms, frequency response, filtering, transfer functions, Z-transforms, Laplace transforms, poles and zeros, Bode plots, and the relationship to state-space representations.

This material is complemented by the use of software tools (e.g. MATLAB) for computation and simulation, and practical experience with circuits and systems in the laboratory.

AIMS

This subject involves undertaking biosystems design group projects from concept to reporting and communicating the design proposal through to possible development, and so will provide an integrated capstone experience for the Bioengineering major.

The emphasis of each of the projects is associated with a well-defined project description that may be based on a task required by an academic or external, industry-based client. The topics covered will include design processes, formulation of the problem, conceptual designs, partitioning of design activities, analysis of system components, integration of design, quality and safety assessment, project management, and engineering professional attitudes.

The open-ended nature of the design task will result in students having exposure to historical, sociological and environmental factors in invention and innovation, professional ethics, regulatory and statutory requirements, legal and ethical responsibilities, and environmental considerations.

INDICATIVE CONTENT

Topics include:

• Design control processes -design and development planning, design input, design control, design output, design review, and design verification.
• Theory of measurement – understanding and applying the limitations of measurement.
• Amplifier circuits –design and construct basic op-amp circuits to the application of high precision instrumentation amps.
• Data acquisition systems – programming and applying industry standard engineering software and hardware tools.
• Sensors – adapting and implementing simple displacement and electrochemical sensors.
• Physiological dynamics – understanding physiological dynamic parameters and applying parameter estimation techniques to acquire physiological signals.
• Non-invasive physiological system – use of sensors, amplifiers, data acquisition systems and parameter estimation to design and construct a physiological system.

AIMS

This subject introduces transport processes in biomedical systems, complementing and reinforcing material learned in related biology subjects. Students will be introduced to the process of developing engineering models and simple conceptual designs in the context of biological systems. The subject covers fundamental concepts of diffusion and conservation within momentum, heat and mass transport. Within momentum transport, specific topics include Newton’s law of viscosity, viscosity of gases and liquids, conservation of momentum, velocity distributions in simple laminar flows, boundary layer concepts and turbulence and the Reynolds number. Within heat transport, Fourier’s law of conduction is covered. Within mass transport, specific topics include Fick’s first and second laws of diffusion, diffusivities of gases, liquids and solids, binary mixture diffusion and conservation of mass, concentration distributions in simple binary systems including identifying appropriate boundary conditions, concentration boundary layer concepts, Schmidt and Sherwood numbers, definition and use of mass transfer coefficients.

Students will examine transport of molecules and cells in biological systems to describe various key processes, such as cell migration and provision of cell nutrition. The role of transport processes in biological systems and employed in clinical applications, such as dialysis, will be described using simple engineering models.

INDICATIVE CONTENT

Topics covered include momentum transport, viscosity, turbulence, heat transport, mass transport, diffusion in binary systems, unsteady state mass transfer, and modelling biological transport processes.

This objective of this subject is to familiarise students with modern concepts of cell and organismal biology, including structure and function of multicellular organisms including cell function, systems involved in energy transformations, nutrition, water uptake, excretion, gas exchange, circulation, and immune responses; plant and animal reproduction and development; mechanisms involved in responsiveness and coordination: hormonal control in plants and animals, and nervous systems in animals; and animal movement and behaviour.

The subject provides an introduction to stoichiometry; gases; energy and thermochemistry; chemical equilibrium; acid-base chemistry; properties of solutions, aspects of main group chemistry: structure and bonding in elements and compounds of groups 14-18; solutions and pH equilibria; physical properties of solution. intermolecular forces and extended solid state structures; structure and bonding of alkanes, alkenes and alkynes; benzene and its derivatives; functional groups; and spectroscopy and determination of structure.

Critical Communication for Engineers (CCE) addresses the skills vital for professional success. Problem analysis skills and being able to present solutions effectively to your engineering peers, leaders and the broader community are a powerful combination. These are the focus of CCE.

They are challenging skills to learn—and you will likely work to improve them throughout your career. Effective communication is not merely about how to write a report or to give a formal presentation. Developing a strong argument—having something insightful to communicate—is essential for capturing the attention of an audience. This requires developing good interpersonal skills for gathering information and testing ideas.

The subject is divided into four ‘topics’ presented in sequence through the semester. Each topic is self-contained and dedicated to a different engineering issue. There is an assessment for each topic, meaning that you will be able to apply what you have learned from one topic to the following topics. This way, you will have a lot of opportunities to practise and develop your analytical and communication skills.

The aim of this subject is to give participants both practical experience in, and theoretical insights into, elements of engineering innovation.

The subject is intense, challenging, experiential and requires significant self-direction. Participants will work on an innovation project sponsored by a local organisation.

A key theme is that the individual cannot be separated from the technical processes of engineering innovation. The impact of both individual and team contributions to the engineering and innovation processes will be examined in the context of real world challenges.

All project sponsors will require that students maintain the confidentiality of their proprietary information.  Some project sponsors will require students to assign any Intellectual Property created (other than Copyright in their Assessment Materials) to the University.  The projects may vary in the hours needed for a successful outcome.

This subject involves the fundamental theory, design and operational principles of biomedical instrumentation and measurement systems applied to biomedical applications. This includes the design of sensors and electronics for measurement and analysis of physiological parameters of the body and organs.

The subject provides theory and practical exposure to understanding the basis of physiological signals and analysing biomedical signals, including hands-on experience in designing and building bioinstrumentation systems that can measure biological signals including electromyography (EMG), electrocardiography (ECG), electroencephalography (EEG), human motion, blood pressure and other measurements.

Topics include:

• Biomedical sensors and transducers: focus on the design, operation and function of a range of biomedical instruments, components and sensors such as biopotential measurement systems (EEG, EMG, ECG), human motion and force sensors (accelerometers, video motion analysis, strain gauges, load cells, force platforms), blood pressure measurements, cardiac and respiratory measurement and surgical instruments.
• Circuits: Operational amplifier (op amp) circuit design and application, including instrumentation amplifiers, feedback amplifiers and stability.
• Electrical safety and systems: power supplies, alternating and direct current circuits, industrial/medical electrical safety, signal grounding, ground loops, electrical isolation, sources of internal and external noise, interference and shielding, signal-to-noise ratio.
• Signal processing: single/multi-channel acquisition systems, filtering, signal conditioning, signal processing, data conversion and data presentation.

These topics will be complemented by exposure to software tools for electronic circuit simulation and further development of laboratory skills through workshops

AIMS

This course is designed to enable students to apply the fundamental principles in material sciences to biomedical applications. It will address different materials (polymers, metals, ceramics and composites) used in contact with living tissue. In addition, students will be introduced to biological materials like bone, muscles, skin and vasculature.

INDICATIVE CONTENT

A main focus in this subject is to examine the application of materials in the physiological environment. Topics will include host reaction, testing and degradation of biomaterials in biological environment (e.g. blood – material interaction). Finally, students will be introduced to the regulatory, ethical and legal aspects of fielding biomaterials.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

AIMS:

This subject teaches fundamentals of probability and statistics, clinical trial processes and regulations of therapeutic goods and specialised health care environments to Master of Engineering (Biomedical) students.

INDICATIVE CONTENT:

Foundations of probability: independence, conditional probability, Bayes’ rule; Random variables: cumulative distributions, probability mass and probability density functions, expectation and variance, functions of a random variable, important distributions and their properties and uses; Sums, inequalities and limit theorems: Basic statistical concepts: confidence intervals, hypothesis testing, significance levels, correlation, analysis of variance; Decision testing: maximum likelihood, maximum a posteriori, minimum cost and Neyman-Pearson rules, basic minimum mean-square error estimation, regression.

Risk management and international and Australian regulatory guidelines for electrical, chemical, biological and administrative health care processes, in particular medical devices: regulations, classifications and standards; familiarisation with specialised clinical/laboratory environmental control and containment guidelines; ethical standards and sponsor responsibilities.

Clinical trials: Design and analysis of experiments; Clinical trials and ethical consent; Principles of drug development: Global regulation and harmonisation of format of processes, decisions and good clinical practices; Institutional structures, product information and guidelines: clinical trials notification schemes, human ethics, chemical, synthesis and property drug information, and drug guidelines; Drug regulation in Australia.

AIMS:

This subject introduces engineering students to human anatomy and physiology, with direct application of the knowledge to considerations for designing and manufacturing medical devices and equipment to assist in overcoming physical disabilities.

INDICATIVE CONTENT:

Topics include:

Anatomical terminology. The structure and appearance of cells and tissues. The appearance of bone and cartilage, the organisation of dense connective tissues. Skeletal muscle structure and function. Principles of excitable tissues. The structure and function of sensory systems, including the eye and vision and the ear and hearing. Principles of sensory motor control. Cardiac mechanics and cardiac biophysics. Multiscale modelling of physiological systems. Technologies, quantitative measurements and experimental techniques used to investigate the structure and function of different tissues, organs and organ systems.

AIMS

The main aim of this course is to introduce students to the basic concepts of the kinematics and dynamics of human motion and the architectural features and mechanical properties of musculoskeletal tissue. Tissue function is then illustrated in the context of normal and pathological movement.

INDICATIVE CONTENT

Specific topics covered include: Motion of a Rigid Body (reference frames, angular velocity, two points fixed on a rigid body); Measurement and Processing of Kinematic Data; Body Anthropometry (calculation of centre of mass and mass moment of inertia); Forces and Moments (moments of force, muscle moment arm, inverse dynamics analysis); Work, Energy, Power (kinetic energy, potential energy, elastic strain energy); Tissue Biomechanics (muscle, tendon, ligament, cartilage and bone); Orthopaedic Biomechanics: biomechanics of gait across the lifespan, biomechanical adaptations to training, knee osteoarthritis).

AIM

The study of genomics is on the forefront of biology. Current laboratory technologies generate huge amounts of data. Computational analysis is necessary to make sense of these data. This subject covers a broad range of approaches to the computational analysis of genomic data. Students learn the theory behind the different approaches to genomic analysis, preparing them to use existing methods appropriately and positioning them to develop new ways to analyse genomic data.

The subject is a core subject in the MSc (Bioinformatics), and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

This subject covers computational analysis of genomic data, from the perspective of information theory. Topics include information theoretic analysis of genomic sequences; sequence comparison, including heuristic approaches and multiple sequence alignment; and approaches to motif finding and genome annotation, including probabilistic modelling and visualization, computational detection of RNA families, and current challenges in protein structure determination. Practical work includes writing bioinformatics applications programs and preparing a research report that uses existing bioinformatics web resources.

AIMS

This subject introduces students to the engineering, physics and physiology of medical imaging, including the history and progression of medical imaging modalities as well as emerging imaging technologies in clinical and research practise. Topics covered include: x-ray, computed tomography, positron emission tomography, magnetic resonance imaging and ultrasound.

INDICATIVE CONTENT

Topics include:

Image metrics including signal-to-noise and contrast-to-noise ratios, image resolution, image operations including convolution, filtering and edge detection;

Biophysical principles of X-ray, CT, PET, SPECT, MRI and ultrasound, and the mathematics of image reconstruction for each modality, including filtered backprojection and fourier reconstruction methods;

This material is complemented by the use of software tools (e.g. MATLAB) for data simulation, modelling, image manipulation and reconstruction techniques.

AIMS

Introduction to soft condensed matter: a range of applications and products including foods, cosmetics, pharmaceuticals, ceramics, suspensions, minerals and detergents. The course covers the fundamental structure-function and material properties of these complex systems.

INDICATIVE CONTENT

The colloidal domain: brownian motion and the Stokes-Einstein equation. Suspension viscosity.
Interparticle forces: dispersion forces, electrostatic forces (Poisson-Boltzmann), double layer theory and solvation forces. The role of surface forces in colloidal stability. Electrokinetic characterization of nano-particles and the relationship to colloidal stability and suspension rheology. Suspension rheology, measurement, viscoelasticity and the colloidal state. Polymer physics. Polymers as random walks, ideal and real chains scaling concepts and the size of the random walk. Entropy and Elasticity, the Hookean spring. Viscoelastic behaviour of polymer solutions and melts. Gels, sols and gelation including the concept of percolation. The theory of rubber elasticity. Adsorption of polymers to surfaces. Surfactants and self assembly. Micelles, vesicles and hexagonal phases. Aggregation numbers and packing parameters. Lipid bilayers. A review of several papers in biotechnology and nanotechnology.

AIMS

This subject aims to develop students' knowledge and capabilities in experimental and computational biomechanics of cells and soft-tissues. Students will apply fundamental mathematical theory of nonlinear continuum mechanics and computational approaches to solve stress-equilibrium equations. Students will learn fundamentals in cell signalling and how cell- and sub-cellular-level processes affect cell and tissue mechanical properties. These concepts will be put to practice in project-based and examination assessments.

INDICATIVE CONTENT

• Nonlinear continuum mechanics theory
• Computational techniques for solving nonlinear mechanics problems
• Soft-tissue mechanical properties
• Cytoskeletal networks and mechanics
• Signalling pathtways and systems-biology related to mechanics of cells and tissues

AIMS

Technological advances in obtaining high throughput data have stimulated the development of new computational approaches to bioinformatics. This subject will cover core computational challenges in analysing bioinformatics data. We cover important algorithmic approaches and data structures used in solving these problems, and the challenges that arise as these problems increase in scale.

The subject is a core subject in the MSc (Bioinformatics) and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

The subject covers key algorithms used in bioinformatics, with a focus on genomics. Indicative topics are: sequence alignment (dynamic algorithms and seed-and-extend), genome assembly, variant detection, phylogenetic reconstruction, genomic intervals, complexity and correctness of algorithms, clustering and classification of genomics data, data reduction and visualisation.
The subject assumes you have experience in programming and familiarity with the foundations of genomics.

AIMS

This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. The subject builds upon signals and systems modelling approaches to demonstrate the application of mathematical and computation modelling to understanding and simulating neural systems. Aspects of neural modelling that are introduced include: membrane potential, action potentials, neural coding, neural models and neural learning. The application of neural information processing is demonstrated in areas such as: electrophysiology, and neuroprostheses. Material is reinforced through MATLAB and/or NEURON based laboratories.

INDICATIVE CONTENT

Topics include:

Neural information processing analysed using information theoretic measures; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); neural models (binary, rate based, integrate & fire, Hodgkin-Huxley, and multicompartmental); synaptic plasticity and learning in biological neural systems (synaptic basis of learning, short term, medium term and long term, and rate based Hebbian learning models); spike-timing dependent plasticity (STDP) of synapses; higher order neural pathways and systems (cortical structure and circuits).

AIMS and INDICATIVE CONTENT

In this subject students should gain an understanding of the structure and function of the skeletal, muscular, and sensory systems of the human body.

Students should also be able to formulate simple, integrative models of the human neuromusculoskeletal system; and to use computational models of the human body to analyse muscle function during activities like standing, walking, running and jumping.

AIMS

Students studying Tissue Engineering and Stem Cells will become familiar with the history, scope and potential of tissue engineering, and the potential role of stem cells in this field. This subject will address the use of biomaterials in tissue engineering; major scaffold materials and fabrication methods, scaffold strength and degradation; cell sources, selection, challenges and potential manipulation; cell-surface interactions, biocompatibility and the foreign body reaction; the role and delivery of growth factors for tissue engineering applications; in vitro and in vivo tissue engineering strategies, challenges, cell culture, scale-up issues and transport modelling; ethical and regulatory issues; clinical applications of tissue engineering, such as bone regeneration, breast reconstruction, cardiac and corneal tissue engineering, and organogenesis (e.g. pancreas).

This subject provides students with exposure to and understanding of a range of new and emerging applications of biomedical engineering. It includes research-led learning with opportunities to interact with experts and active researchers in the fields of stem cells and tissue engineering. The subject covers aspects of biology, materials engineering and process engineering which underpin tissue engineering and provides examples of the applications of this evolving area of technology.

INDICATIVE CONTENT

Topics covered include tissue organization & tissue dynamics, stem cells, cellular fate processes & signalling, the ECM as scaffold material, natural and synthetic polymers for tissue engineering, bioceramics, scaffold design and fabrication, tailoring biomaterials, cell culture and cell nutrition, bioreactors for tissue engineering, risk management in tissue engineering, ethics in tissue engineering.

AIMS:

This subject introduces mathematical and computational modelling, simulation and analysis of biological systems. The emphasis is on developing models, with examples, using MATLAB.

INDICATIVE CONTENT:

Topics include:

Modelling biochemical reactions. Law of mass action. Enzymes and regulation of enzyme reactions. Thermodynamics of reversible biochemical reactions. Cellular homeostasis. Application of ordinary differential equations to these problems.

Modelling large reaction networks. Flux balance analysis and constraint-based methods. Genome-scale models. Regulation of gene expression. Gene regulatory networks in systems and synthetic biology. Network inference and statistical modelling of –omic data. Knowledge-based modelling in systems biology.

AIMS

This subject covers key aspects of engineering management to help students prepare for working in the biomedical engineering industry.

INDICATIVE CONTENT

Topics include:

The engineer and professional practice, the functions of professional societies; systems engineering and management processes of planning, organisation, leadership and control of human, physical and financial resources; financial performance including the stages of an engineering project, performance measurement, concepts of revenue, capital and operating cost forecasting, simple accounting, profitability analysis; biomedical engineering management including responsibility, authority, human relations, industrial relations, standards and quality management systems including ISO 9000 series requirements; intellectual property and commercialisation.

AIMS

BioDesign Innovation is a “real world” course in creating successful medical devices. The course is given over two semesters of one academic year and is composed of frontal lectures, practical training, and a guided project. The first semester focusses on identifying clinical needs, brainstorming and concept creation. The second semester focusses on concept development and business implementation. Teams of 2-3 students from engineering disciplines will team up with business students and with people from medical and law backgrounds to conceive and design an innovative medical device, taking it through all steps of development. The students in the teams will complete assessment items together, each member primarily contributing according to their specialisation. The teams will create an engineering prototype of their invention, draft a provisional patent application, and compose a detailed business plan. BioDesign Innovation is taught by a combination of academics, medical device entrepreneurs, corporate executives, intellectual property attorneys and venture capitalists. As such, it provides a unique opportunity to gain real world experience while still in an academic environment.

AIMS

This subject involves undertaking a major design project, requiring independent investigation in a team context to produce an advanced biomedical engineering design in a timely and professional manner. Examples of possible design problems include the development of a pacemaker and sensor, creation of new methods for delivering personalized medical treatments, and development of a novel device for interfacing with the brain. In addition to written reports, students will present their findings through oral presentations.

INDICATIVE CONTENT

Topics include:

System-level device descriptions, component interface specifications, regulatory bodies and biomedical device approval processes, intellectual property, component specifications, biomaterials and biocompatibility, manufacturing specifications, economic analyses.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

AIMS

This subject involves undertaking a major research or advanced innovative design project requiring an independent investigation and the preparation of reports on an approved topic. Students will present their findings in a conference presentation format, held at the end of the project cycle in the latter half of semester two.

The emphasis of the project can be associated with either:

• Explorative approach, where students will pursue outcomes associated with new knowledge or understanding within the biomedical engineering or science disciplines, often as an adjunct to existing academic research initiatives.
• A well-defined innovative project, usually based on a research and development required by an external industrial client. Students will be tutored in the synthesis of practical solutions to complex technical problems within a structured working environment, as if they were research and development professional engineers.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

AIMS

This subject involves undertaking a major research or advanced innovative design project requiring an independent investigation and the preparation of reports on an approved topic. Students will present their findings in a conference presentation format, held at the end of the project cycle in the latter half of semester two. The emphasis of the project can be associated with either:

Explorative approach, where students will pursue outcomes associated with new knowledge or understanding within the biomedical engineering or science disciplines, often as an adjunct to existing academic research initiatives.

A well-defined innovative project, usually based on a research and development required by an external industrial client. Students will be tutored in the synthesis of practical solutions to complex technical problems within a structured working environment, as if they were research and development professional engineers.

INDICATIVE CONTENT

Topics include: Technical report writing, engineering design planning and conducting experiments and test, data acquisition and analysis, public speaking, project presentation skills.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

Note: Enrolment in BMEN90031 Biomedical Engineering Capstone Project Part 1 is subject to approval from the subject coordinator. Students commence BMEN90031 Biomedical Engineering Capstone Project Part 1 in Semester 2 and then subsequently continue BMEN90032 Biomedical Engineering Capstone Project Part 2 in Semester 1 in the following year. Upon successful completion of this project, students will receive 25 points credit.

Refer to BMEN90031 Biomedical Engineering Capstone Project Part 1 for details.

AIMS

This subject introduces students to the special requirements necessary for managing Medical Devices and Clinical/Biotechnological Environments. Topics covered include: detailed analysis of the cardiopulmonary system, including computer-aided modelling of the cardiovascular system and respiratory system; electrical devices that monitor/support these systems, international/national electrical/biological regulatory bodies and standards.

INDICATIVE CONTENT

Topics include:

• Management of Medical Devices – the regulations, classifications and standard of Medical Devices. In particular AS3200 series of standards and AS3551 standard.
• Management of Clinical Areas – environmental control and electrical isolation in accordance to AS3000 and AS3003.
• The Respiratory System – anatomy, physiology, mechanics of static and dynamics of breathing is monitored and modelled.
• The Cardiovascular System – anatomy, physiology, mechanics of static and dynamics of blood pressure monitoring systems.
• Electrophysiology – cellular physiology, electrical equivalent models, dipole models and Einthoven’s model of the Electrocardiogram.
• These topics are complemented by exposure to Medical Devices in the Clinical Environment and use of software tools for modelling and parameter estimations in the Laboratory/Clinic.

AIMS

This subject involves students undertaking professional work experience at a Host Organisation’s premises. Students will work under the supervision of both a member of academic staff and an external supervisor at the Host Organisation.

During the period of work experience, students will be introduced to workplace culture and be offered the opportunity to strengthen their employability. Students will undertake seminars covering topics that will include professional standards of behaviour and ethical conduct, working in teams, time management and workplace networking.

AIM

The study of genomics is on the forefront of biology. Current laboratory technologies generate huge amounts of data. Computational analysis is necessary to make sense of these data. This subject covers a broad range of approaches to the computational analysis of genomic data. Students learn the theory behind the different approaches to genomic analysis, preparing them to use existing methods appropriately and positioning them to develop new ways to analyse genomic data.

The subject is a core subject in the MSc (Bioinformatics), and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

This subject covers computational analysis of genomic data, from the perspective of information theory. Topics include information theoretic analysis of genomic sequences; sequence comparison, including heuristic approaches and multiple sequence alignment; and approaches to motif finding and genome annotation, including probabilistic modelling and visualization, computational detection of RNA families, and current challenges in protein structure determination. Practical work includes writing bioinformatics applications programs and preparing a research report that uses existing bioinformatics web resources.

AIMS

This subject introduces students to the engineering, physics and physiology of medical imaging, including the history and progression of medical imaging modalities as well as emerging imaging technologies in clinical and research practise. Topics covered include: x-ray, computed tomography, positron emission tomography, magnetic resonance imaging and ultrasound.

INDICATIVE CONTENT

Topics include:

Image metrics including signal-to-noise and contrast-to-noise ratios, image resolution, image operations including convolution, filtering and edge detection;

Biophysical principles of X-ray, CT, PET, SPECT, MRI and ultrasound, and the mathematics of image reconstruction for each modality, including filtered backprojection and fourier reconstruction methods;

This material is complemented by the use of software tools (e.g. MATLAB) for data simulation, modelling, image manipulation and reconstruction techniques.

AIMS

Introduction to soft condensed matter: a range of applications and products including foods, cosmetics, pharmaceuticals, ceramics, suspensions, minerals and detergents. The course covers the fundamental structure-function and material properties of these complex systems.

INDICATIVE CONTENT

The colloidal domain: brownian motion and the Stokes-Einstein equation. Suspension viscosity.
Interparticle forces: dispersion forces, electrostatic forces (Poisson-Boltzmann), double layer theory and solvation forces. The role of surface forces in colloidal stability. Electrokinetic characterization of nano-particles and the relationship to colloidal stability and suspension rheology. Suspension rheology, measurement, viscoelasticity and the colloidal state. Polymer physics. Polymers as random walks, ideal and real chains scaling concepts and the size of the random walk. Entropy and Elasticity, the Hookean spring. Viscoelastic behaviour of polymer solutions and melts. Gels, sols and gelation including the concept of percolation. The theory of rubber elasticity. Adsorption of polymers to surfaces. Surfactants and self assembly. Micelles, vesicles and hexagonal phases. Aggregation numbers and packing parameters. Lipid bilayers. A review of several papers in biotechnology and nanotechnology.

AIMS

This subject aims to develop students' knowledge and capabilities in experimental and computational biomechanics of cells and soft-tissues. Students will apply fundamental mathematical theory of nonlinear continuum mechanics and computational approaches to solve stress-equilibrium equations. Students will learn fundamentals in cell signalling and how cell- and sub-cellular-level processes affect cell and tissue mechanical properties. These concepts will be put to practice in project-based and examination assessments.

INDICATIVE CONTENT

• Nonlinear continuum mechanics theory
• Computational techniques for solving nonlinear mechanics problems
• Soft-tissue mechanical properties
• Cytoskeletal networks and mechanics
• Signalling pathtways and systems-biology related to mechanics of cells and tissues

AIMS

Technological advances in obtaining high throughput data have stimulated the development of new computational approaches to bioinformatics. This subject will cover core computational challenges in analysing bioinformatics data. We cover important algorithmic approaches and data structures used in solving these problems, and the challenges that arise as these problems increase in scale.

The subject is a core subject in the MSc (Bioinformatics) and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

The subject covers key algorithms used in bioinformatics, with a focus on genomics. Indicative topics are: sequence alignment (dynamic algorithms and seed-and-extend), genome assembly, variant detection, phylogenetic reconstruction, genomic intervals, complexity and correctness of algorithms, clustering and classification of genomics data, data reduction and visualisation.
The subject assumes you have experience in programming and familiarity with the foundations of genomics.

AIMS

This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. The subject builds upon signals and systems modelling approaches to demonstrate the application of mathematical and computation modelling to understanding and simulating neural systems. Aspects of neural modelling that are introduced include: membrane potential, action potentials, neural coding, neural models and neural learning. The application of neural information processing is demonstrated in areas such as: electrophysiology, and neuroprostheses. Material is reinforced through MATLAB and/or NEURON based laboratories.

INDICATIVE CONTENT

Topics include:

Neural information processing analysed using information theoretic measures; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); neural models (binary, rate based, integrate & fire, Hodgkin-Huxley, and multicompartmental); synaptic plasticity and learning in biological neural systems (synaptic basis of learning, short term, medium term and long term, and rate based Hebbian learning models); spike-timing dependent plasticity (STDP) of synapses; higher order neural pathways and systems (cortical structure and circuits).

AIMS and INDICATIVE CONTENT

In this subject students should gain an understanding of the structure and function of the skeletal, muscular, and sensory systems of the human body.

Students should also be able to formulate simple, integrative models of the human neuromusculoskeletal system; and to use computational models of the human body to analyse muscle function during activities like standing, walking, running and jumping.

AIMS

Students studying Tissue Engineering and Stem Cells will become familiar with the history, scope and potential of tissue engineering, and the potential role of stem cells in this field. This subject will address the use of biomaterials in tissue engineering; major scaffold materials and fabrication methods, scaffold strength and degradation; cell sources, selection, challenges and potential manipulation; cell-surface interactions, biocompatibility and the foreign body reaction; the role and delivery of growth factors for tissue engineering applications; in vitro and in vivo tissue engineering strategies, challenges, cell culture, scale-up issues and transport modelling; ethical and regulatory issues; clinical applications of tissue engineering, such as bone regeneration, breast reconstruction, cardiac and corneal tissue engineering, and organogenesis (e.g. pancreas).

This subject provides students with exposure to and understanding of a range of new and emerging applications of biomedical engineering. It includes research-led learning with opportunities to interact with experts and active researchers in the fields of stem cells and tissue engineering. The subject covers aspects of biology, materials engineering and process engineering which underpin tissue engineering and provides examples of the applications of this evolving area of technology.

INDICATIVE CONTENT

Topics covered include tissue organization & tissue dynamics, stem cells, cellular fate processes & signalling, the ECM as scaffold material, natural and synthetic polymers for tissue engineering, bioceramics, scaffold design and fabrication, tailoring biomaterials, cell culture and cell nutrition, bioreactors for tissue engineering, risk management in tissue engineering, ethics in tissue engineering.

AIMS:

This subject introduces mathematical and computational modelling, simulation and analysis of biological systems. The emphasis is on developing models, with examples, using MATLAB.

INDICATIVE CONTENT:

Topics include:

Modelling biochemical reactions. Law of mass action. Enzymes and regulation of enzyme reactions. Thermodynamics of reversible biochemical reactions. Cellular homeostasis. Application of ordinary differential equations to these problems.

Modelling large reaction networks. Flux balance analysis and constraint-based methods. Genome-scale models. Regulation of gene expression. Gene regulatory networks in systems and synthetic biology. Network inference and statistical modelling of –omic data. Knowledge-based modelling in systems biology.