Module Information
Module Identifier
SS31120
Module Title
Advanced Biomechanics
Academic Year
2018/2019
Co-ordinator
Semester
Semester 1
Pre-Requisite
Other Staff
Course Delivery
| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 22 x 1 Hour Lectures |
| Practical | 11 x 2 Hour Practicals |
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Report: Force, muscle activation and fatigue (1,000 words) | 25% |
| Semester Assessment | Report: Post processing of kinematic data (1,000 words) | 25% |
| Semester Assessment | Worksheet: Inverse Dynamics | 20% |
| Semester Assessment | Report: Interpreting biomechanical data (1,500 words) | 30% |
| Supplementary Assessment | Students must take elements of assessment equivalent to those that led to failure of the module. | 100% |
Learning Outcomes
On successful completion of this module students should be able to:
1. Record motion, force plate and electromyography data using advanced equipment while adhering to scientific, international standards and recommendations.
2. Understand and critically evaluate data analysis techniques, including the ability perform noise reduction methods and integrate various data sources.
3. Process recorded data correctly, including dealing with large data sets and multiple recordings in an effective manner.
4. Complete an inverse-dynamic analysis of a three-segment system.
5. Interpret and communicate the results of inverse dynamical analyses.
Brief description
This module will further develop the skills learned in the second year biomechanics module. A specific focus will be on methods such as 3D motion capture, force measurement and electromyography through the quantitative analysis of human movement and function. An integrated approach will result in the application of inverse dynamics in a clinical or sports related situation. Students will be guided through the principles of 3D motion analysis, with particular reference to clinical gait analysis and sports performance.
Students will develop a portfolio of work to demonstrate achievement of the learning outcomes. The portfolio will contain applications of the procedures, methods, and calculations as provided in the practical, with the lectures providing the core background knowledge. These applications can be based around a sport or exercise situation of the student's choice so that the portfolio represents a complete analysis of their situation of interest using a range of techniques.
Students will develop a portfolio of work to demonstrate achievement of the learning outcomes. The portfolio will contain applications of the procedures, methods, and calculations as provided in the practical, with the lectures providing the core background knowledge. These applications can be based around a sport or exercise situation of the student's choice so that the portfolio represents a complete analysis of their situation of interest using a range of techniques.
Content
Indicative content includes:
1. Three dimensional gait analysis
2. Interpretation of muscle activation and joint function
3. Evaluation of various signal acquisition and processing methods
4. Inverse dynamics application to a thigh-shank-and-foot system or similar for non-constant acceleration
5. Automated data analysis techniques using computer software
6. Motor control and motor learning
7. Electromyography
8. Biomechanical evaluation of movement of special populations
1. Three dimensional gait analysis
2. Interpretation of muscle activation and joint function
3. Evaluation of various signal acquisition and processing methods
4. Inverse dynamics application to a thigh-shank-and-foot system or similar for non-constant acceleration
5. Automated data analysis techniques using computer software
6. Motor control and motor learning
7. Electromyography
8. Biomechanical evaluation of movement of special populations
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | Calculations associated with practical work |
| Communication | Collection of data in groups |
| Improving own Learning and Performance | Using tutorials to gain feedback and improve understanding. Feedback following each component of the portfolio |
| Information Technology | Using computers to collect and process data during practical work. Developing basic programming skills, in MatLab or in Excel |
| Personal Development and Career planning | Receiving and handling constructive feedback |
| Problem solving | Identifying relevant dependent variables to quantify gait. Practical work: designing data collection and performing calculations |
| Research skills | Design of research and data collection. Understanding of noise reduction procedures during data collection. Searching and identifying relevant literature. Scientific writing |
| Subject Specific Skills | Laboratory skills and data collection and processing skills |
| Team work | Collection of data in groups |
Notes
This module is at CQFW Level 6