HUMAN MOVEMENT AND REHABILITATION - 2020/1
Module code: ENGM260
In light of the Covid-19 pandemic, and in a departure from previous academic years and previously published information, the University has had to change the delivery (and in some cases the content) of its programmes, together with certain University services and facilities for the academic year 2020/21.
These changes include the implementation of a hybrid teaching approach during 2020/21. Detailed information on all changes is available at: https://www.surrey.ac.uk/coronavirus/course-changes. This webpage sets out information relating to general University changes, and will also direct you to consider additional specific information relating to your chosen programme.
Prior to registering online, you must read this general information and all relevant additional programme specific information. By completing online registration, you acknowledge that you have read such content, and accept all such changes.
Module Overview
The module provides students with up-to-date knowledge on the assessment of human movement with a focus on clinical gait analysis. It includes an in-depth evaluation of state-of-the-art measurement and analysis tools currently used in gait and performance management.
Module provider
Mechanical Engineering Sciences
Module Leader
OLDFIELD Matthew (Mech Eng Sci)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: H164
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
Indicative content includes:
- Motor control and development of human movement skills.
- Gait analysis; determinants of gait, the gait cycle, the main classes of measurement (e.g. spatial and temporal, kinematic, kinetic and neurophysiology).
- Technical descriptions and review of tools used in movement analysis, for example: body-worn inertial sensors, force plates and platforms, goniometry, observational gait tools, passive/active marker detection, plantar pressure systems, in-vivo force transducers and EMG.
- Theoretical foundations of three-dimensional kinematic and kinetic analysis of gait.
- Gait patterns associated with pathology and the underpinning biomechanics principles of movement compensation.
- An overview of kinematic analysis of upper-limb motion.
- Related topics such as methods used in sports performance analysis and injury prevention strategies.
- Practical laboratory-based 3D gait measurement, using state of the art motion capture and kinetic measurement systems.
- Analysis of experimental 3D gait data using dedicated professional software.
Assessment pattern
| Assessment type | Unit of assessment | Weighting |
|---|---|---|
| Coursework | COURSEWORK REPORT | 40 |
| Examination | EXAM 2 HOURS | 60 |
Alternative Assessment
N/A
Assessment Strategy
The assessment strategy is designed to provide students with the opportunity to demonstrate
· an understanding of the methods used in analysing movement analysis and the limitations of measurement and analysis technique – examination
· their ability apply their understanding of movement analysis techniques to process and analyse raw movement data and to present their findings in a clear and coherent manner – coursework
Thus, the summative assessment for this module consists of:
· Examination [Learning Outcomes 1, 2, 3, 4, 5 ]
· Coursework [Learning Outcomes 6, 7, 8]
Formative assessment and feedback
Formative feedback will be provided in interactive laboratory sessions and in written format for the coursework submission.
Module aims
- An understanding of the basis of human movement, functional ability and the limitations inherent in current databases.
- An understanding of the scope and limitations of current methods used to measure and analyse human movement
- The skills required to be able to critically evaluate and appropriately interpret movement data in light of the limitations of the methods and relevance to the application.
- The acquisition of first-hand practical skills in collecting, measuring and analysing movement using state of the art equipment and associated software.
Learning outcomes
| Attributes Developed | ||
|---|---|---|
| 001 | Demonstrate a breadth of knowledge of the issues underpinning human movement analysis and gait, and their relevance to the clinic (Q1) (SM1m) | K |
| 002 | Demonstrate ability to identify and integrate relevant biomechanics concepts and fundamentals of human biology to interpret data relevant to human movement analysis (Q1) (SM3m) | C |
| 003 | Reflect on and critically evaluate the measurement and analysis tools used in movement analysis and their appropriateness for different applications – (Q2) (SM2m, EA3m) | CP |
| 006 | Demonstrate basic skills in gait analysis. (Q3) (P3) | P |
| 007 | Identify technical and practical challenges and their subsequent effect on developments in the field. (Q4) (EA3m, EA5m, EA6m, EL1m, P8) | CP |
| 008 | Deal with complex issues related to human movement and make sound conclusions based on a complete movement data set and an appreciation of the limitations of current tools. (Q5) (SM6m, EA6m) | KCP |
| 005 | Independently continue to advance knowledge of the subject from the body of literature in order to tackle new and emerging problems. (EA5m, P9m) | CT |
| 004 | Recognise the scope of the methods used in movement analysis beyond traditional applications in gait analysis e.g. in sports and animation. (Q10) (SM6m, EA6m) | K |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Overall student workload
Independent Study Hours: 104
Lecture Hours: 33
Laboratory Hours: 13
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
- Provide students with knowledge of the fundamental concepts involved in analysing movement and their application, principally through lectures.
- Provide students with hands-on experience in collecting, processing and analysing movement data, through practical sessions.
The learning and teaching methods include traditional lectures, laboratory-based practical work, hands-on processing of movement data and independent study.
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: ENGM260
Programmes this module appears in
| Programme | Semester | Classification | Qualifying conditions |
|---|---|---|---|
| Biomedical Engineering MSc | 2 | Compulsory | A weighted aggregate mark of 50% is required to pass the module |
| Biomedical Engineering MEng | 2 | Optional | A weighted aggregate mark of 50% is required to pass the module |
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.