COMPUTER METHODS IN BIOMEDICAL ENGINEERING RESEARCH - 2020/1

Module Overview

The module introduces the student to the application of modern computational methods in biomedical research. Within the context of real-life problems encountered in biomedical engineering practice, the student will be introduced to and provided with practical experience in using:

• Finite element software (ANSYS, LS-DYNA).


• Software for reconstruction of anatomically realistic geometries from clinical images (Simpleware).


• High-end programming languages for a wide range of data analysis and mathematical simulation tasks (Matlab).

Module provider

Mechanical Engineering Sciences

Module Leader

CIROVIC Srdjan (Mech Eng Sci)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

Normal entry requirements for the Biomedical Engineering MSc degree programme.

Module content

Reconstruction of anatomically accurate geometries

• Introduction to the Simpleware software


• Strategies for extracting geometries from stacks of MRI and CT scan images: manual painting, thresholding, flood-filling.


• Filtering strategies for smoothing and noise removal.


• Exporting of geometries in CAD file formats.

• Introduction to the finite element method. Nodes, elements, types of elements, meshing strategies, level of geometric approximation: 3D solids, shells, beams/trusses.

• Basic concepts: pre-processing, constraints, loads, material definition, post-processing of the results.


• Advanced concepts: Geometry construction from CAD models, advanced material models, large deformations and geometric non-linearity.


• Biomedical applications: Bone implants, soft-tissue modelling.

• Time step control and meshing strategies for explicit methods.


• Initial and boundary conditions.


• Modelling of contacts and constraints between objects.


• Multi-body systems of rigid objects, springs, dampers, cables, seatbelts, force generators.


• Post-processing for dynamic problems.


• Biomedical applications: impact and acceleration trauma, pressure-wave therapy, modelling of active muscle tissue.

• Introduction to Matlab: basic commands, loops and logical statements; mathematical functions, linear and vector algebra, control structures and functions.


• An introduction to biomedical signal processing: sampling, discrete Fourier transform, methods to estimate the power spectrum of a signal.


• An introduction to basic digital filter design applied to biomedical signals.


• Statistical analysis of (experimental biomedical) data and its implementation in Matlab; basic statistics, distribution testing, statistical significance, parametric and non-parametric testing.


• Numerical solution for systems of ordinary differential equations: lumped-parameter models of vascular and other physiological systems.

Assessment pattern

Alternative Assessment

Not applicable.

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate that they have developed a sound understanding of the application of engineering software for the solution of problems in biomedical engineering, as well as the practical skills needed to implement that software. The students will also have the opportunity to demonstrate their competence in analysing and presenting results.

Thus, the summative assessment for this module consists of:

·         Individual project [ Learning outcomes 1, 2,3,4,5 ]                             (80 hours)                  {70%}

·         Presentation     [ Learning outcomes 1,4 ]                                        (25 hours)                 {30%}

Formative assessment and feedback

• 
  Formative verbal feedback is given in computer lab sessions.
  


• 
  One-to-one consultations are available for the individual project, in which formative feedback is given on the practical aspects of modelling.
  


• 
  Written feedback is given for the individual project report/model. The students are allowed/encouraged to improve their computer model according to the recommendations given in the feedback, and present updated results in the Presentation session.
  

Module aims

• A comprehensive understanding of  computer techniques  widely used in biomedical engineering research as well as the current state of the art of their application in the field.
• A set of practical skills in using advanced software for design and analysis in biomedical engineering, which can also be applied to other engineering fields.
• A broad knowledge base on which to independently build further expertise in using advanced engineering software.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to: Introduce the student to the use of advanced computer methods in various fields of biomedical engineering. The emphasis is on hands-on sessions with guidance from the lecturers, and on the individual learning through the individual project.

The module is delivered intensively over a two week period.: The learning and teaching methods include:

• 15 hours of lectures


• 30 hours of lab sessions/demonstrations

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENGM259

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.