A biomaterial can be described as a material used in a biomedical device intended to interact with biological systems. The selection of an appropriate biomaterial is critical to the performance of an implant. For a hip replacement, properties such as good strength, excellent corrosion resistance, fatigue resistance and biocompatibility are required to ensure the hip replacement does not fail in service. In this module, you will learn about the various polymer, metal and ceramic based materials used as biomaterials, and discover why these materials have been accepted into clinical practice. A series of case studies will be used as examples to show how past failures have led to the materials that are used today, in particular, focussing on hip and knee replacements.
The module aims to provide an integrated understanding of the representation and analysis of dynamical systems (electrical and mechanical), their solution and practical implementation in diagnosis and health monitoring for biomedical engineering problems and applications. The module integrates three components related to the analysis of (1) mechanical system, (2) electrical machines, and (3) power drives, and each component has specific aims: 1.To provide a detailed understanding of mechanical systems, vibration analysis using frequency response and energy approximations methods, which is further extended into continuous mechanical problems. 2.To introduce the students to fundamental concepts and principles of operation of types of electrical machines and provide basic experimental and modelling skills associated with electrical machines. 3.To provide a detailed understanding of all aspects of the selection, sizing and operation of modern electrical drive systems; this will be achieved by consideration of the individual sub-system including power semiconductors, electronic power converters and associated electric motors, mechanical power transmission, speed and velocity transducers, and controllers.
During the process of diagnosis and subsequent treatment, patients routinely undergo imaging, measurement and monitoring procedures using a wide range of techniques. Whether it is the automated monitoring of blood pressure of flow, the electrical signals generated during the contractions of the heart or medical images taken with a state of the art medical scanner, all these techniques produce vast amounts of data, for example in the form of time-series signals representing blood-pressure variation or the large image data-sets from a medical scanner. To help medical practitioners make sense of this flood of information, it is thus becoming increasingly important to provide reliable computational tools that can automatically enhance, analyse and monitor these signals and images, and extract (or facilitate the extractin of) clinically useful information. The same is true in medical and biological research, where similar biomedical monitoring techniques are used to study both healthy biological functions as well as mechanisms of disease and where ever larger studies collect ever larger data-sets of signals and images. Signal and image processing techniques now allow us to predict unobserved biological processes from non-invasive measurements (for example in the control of blood flow), identify specific impairments (for example in executing movements of the limb), reliably screen large populations for common medical conditions (such as breast cancer) and allow us to automatically compare physiological properties between different populations (such as, for example, the change in the size of certain brain regions in epilepsy patients). In this module you will study a range of signal and image processing techniques and will learn how they can be used to analyse a range of biomedical signals and images. Whilst learning general and specific analysis techniques, you will also gain insight into relevant biomedical background (such as the basic physiological properties that give rise to many biomedical signals and images) and many of the engineering principles that underlie the operation of key devices that are used to record biomedical signals or generate biomedical images. The module will also discuss engineering issues in the wider context of exploiting engineering for health-care, including relevant ethical and economic issues and multidisciplinary collaboration and communication. Students should be aware that some knowledge of signal processing or control is strongly recommended. Knowledge of Matlab or Python programming required.
This module teaches the applications of biomedical signal analysis and control systems for biomedicine. The module emphasises developing an understanding through lab-based system design exercises by applying theoretical knowledge taught in the module. The module is split in two parts: 50% control and 50% biomedical signals analysis. The control topics include electrical/mechanical analogues, p notation, block diagrams, electromechanical systems: torque, inertia, motor model. Using this knowledge, you will follow the Stanford bio-design process to develop an Active Tremor Suppression Brace for Parkinsons The biomedical signals analysis part will provide a theoretical understanding of the fundamentals of biomedical signal processing, including representation of signals, signal arithmetics, frequency analysis and time-frequency representation of a signal and the fundamentals of Electrocardiogram (ECG) signals. You will design an automated algorithm for ECG analysis in the lab where you will write programmes to separate artefacts and identify individual ECG waves which are fundamental in clinical diagnosis of cardiac diseases.
This course is designed to develop fundamental mathematical skills which Biomedical engineers need in order to tackle a wide variety of engineering and design problems. There is a particular focus on developing an understanding of mathematics as a toolbox through practical examples based on case studies from academia and industry
Medical Engineering (or Biomedical Engineering) is informed by and contributes to research in physiology, healthcare and engineering and the physical sciences. Creativity and decision making based on research and user needs is then required in the design and development of devices and systems and their effective operation. These activities should be guided by professional practice, in accordance with professional and research ethics and within the regulatory frameworks to ensure robust, cost-effective, safe and sustainable outcomes. This module aims to guide you in developing your understanding, knowledge and skills for these activities.
This module will introduce the main issues in parasitology, the host parasite interaction and how it drives evolutionary changes, the disease burden caused by parasites and how parasite infections can be treated/minimised. Lectures will be accompanied by practicals, some of which involve the use of animal tissue, with alternatives in place if required to meet minimum learning outcomes.
The aim of this module is introduce third year students to the main clinically relevant parasite classes, it will consider their lifecycles, the human/veterinary pathology caused and the treatment methods both of the primary and where applicable intermediate hosts and environment. It will give an understanding of vector borne disease. The module will consider the interaction and evasion methods used by parasites in respect to the immune system and chemical control. It will consider the evidence of possible benefits gained by parasitism. Finally it will demonstrate examples of host:parasite coevolution and consider the likely changes in parasite risk the UK in the light of environmental change.
Biomedical research, applications and many clinical tools are underpinned by modern spectroscopic and imaging techniques. These serve as valuable analytical tools for routine monitoring, diagnosis and prognosis as well as aids to therapeutic intervention such as surgery, transplants, and regular treatments. This module will introduce the key physical principles of different techniques used for spectroscopic and imaging measurements. Based on these principles, the emphasis will be on the applications of relevant techniques to biomedical research and clinical practice, which interrogate various properties of materials and provide information ranging from the molecular to the structural level. Thus they also provide information at different length scales from nano (nm) to macro (m). In this context state-of-the-art developments and applications in spectroscopy, microscopy, super-resolution and large-scale (whole body) imaging will be discussed, including biomedical imaging modalities applied in daily clinical practice. The sessions (lectures, discussion groups and workshops) as well as the lab visits within this module will be offered at the University of Southampton and the Southampton General Hospital by basic and clinical researchers across different disciplines, within the Faculties of Natural and Environmental Sciences, Engineering and the Environment, Physical Sciences and Engineering, and Medicine.
This course is designed to illustrate the ways in which the theoretical principles of biochemistry, cellular and molecular biology presented in previous courses can be applied to yield important commercial or therapeutic products or processes.
