Module overview
Aims and Objectives
Learning Outcomes
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Use standard engineering software to assess failure
- Extract, interpret and present data
- Develop advanced adaptive modelling techniques to simulate time dependent processes
- Apply analytical skills to practical problems
- Explain and defend modelling decisions
- Prepare technical reports
Full CEng Programme Level Learning Outcomes
Having successfully completed this module you will be able to:
- As part of the individual assignment students will analyse complex problems to reach substantiated conclusions. This will involve evaluating a variety of biomedical engineering data which can include biomedical imaging, 3D surface and volume model, but also motion capture and other experimental data using first principles of mathematics, statistics, natural science and engineering principles, and using your engineering judgment to work with information and data sets that may be uncertain or incomplete, discussing the limitations of the techniques employed.
- As part of the individual assignment students will apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems in biomedical engineering. Much of the knowledge will be at the forefront of biomedical engineering and informed by a critical awareness of new developments in numerical modelling and analysis methods relevant to the development of technology, devices, and procedures for the prevention, diagnosis, treatment and rehabilitation of ill-health.
- As part of the individual assignment students will select and critically evaluate technical literature and other sources of information to solve the specific complex biomedical engineering problems they address.
- As a central task in the individual assignment students will select and apply appropriate computational and analytical techniques ranging from, e.g. manual to automated image segmentation, various model fitting and data approximation techniques, to analytical and iterative numerical methods to model complex biomedical engineering problems related to optimisation and performance evaluation of methods and devices, discussing the limitations of the techniques employed.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Suitable methods for developing computational models of the musculoskeletal system
- Selection of appropriate methods to consider both technical uncertainty but also assess the influence of patient and surgical variability
- Customer and end-user needs incl. the importance of aesthetics in presenting dedicated simulation tools
- Implementation design of experiments and probabilistic techniques into computer simulations
- Techniques for computational modelling of common failure modes, including: bone remodelling; tissue differentiation; damage accumulation and wear
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Assess the strengths and limitations of computational models for assessing the performance of biomedical devices
- Identify suitable sources of data to both drive and verify and asses the quality of computational simulations
- Apply appropriate modelling strategies to assess the performance of biomedical devices and conceive designs that promote sustainable development
Partial CEng Programme Level Learning Outcomes
Having successfully completed this module you will be able to:
- In the written reports for their individual assignments students summarise the background of their work, the methods, findings and provide a critical discussion you will communicate effectively on the complex biomedical engineering matters in a manner appropriate for technical and non-technical audiences.
Syllabus
Learning and Teaching
Teaching and learning methods
| Type | Hours |
|---|---|
| Completion of assessment task | 40 |
| Lecture | 30 |
| Follow-up work | 80 |
| Total study time | 150 |
Resources & Reading list
General Resources
Software requirements. MATLAB
Software requirements. OpenSim (opensim.stanford.edu)
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Continuous Assessment | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Set Task | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Set Task | 100% |
Repeat Information
Repeat type: Internal & External