HAB620 - SPORT BIOMECHANICS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| SPORT BIOMECHANICS | HAB620 | Any Semester/Year | 3 | 2 | 4 | 8 |
| Prequisites | None | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Question and Answer Observation Team/Group Work Preparing and/or Presenting Reports Drill and Practice Project Design/Management | |||||
| Instructor (s) | Dr. Arif Mithat AMCA | |||||
| Course objective | The purpose of this course is to understand and analyze the human movement system with the basis of mechanical principles. This course also aims analysis of advanced and complex dynamics systems of human body parts. | |||||
| Learning outcomes |
| |||||
| Course Content | Methods of kinematics and kinetics of biomechanical systems are covered to analysis of human movement in this course. | |||||
| References | Robertson, G. E., Caldwell, G. E., Hamill, J., Kamen, G., & Whittlesey, S. (2013). Research methods in biomechanics. Human Kinetics. Tözeren, A., Human Body Dynamics: Classical Mechanics and Human Movement, Springer. 2000. ISBN: 978-0387988016 Payton, C., Bartlett, R. (2008). Biomechanical evaluation of movement in sport and exercise: The British Association of Sport and Exercise Sciences guidelines. Routledge. Nigg, B.M., Herzog, W., Biomechanics of the Musculo-Skeletal System, 3rd Edition, (Editors), John Wiley & Son. 2007. ISBN: 978-0470017678 | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Introduction to the course, What is biomechanics? |
| Week 2 | Planar Kinematics: Linear Motion Introduction to Matlab and basic calculations: addition and subtraction of vectors, time derivatives of vectors, position, velocity, and acceleration |
| Week 3 | Planar Kinematics: Angular Motion Introduction to modelling in Simulink |
| Week 4 | Motion Analysis Systems and motion capture Anatomical marker sets, capturing, digitising, processing and kinematical analysis |
| Week 5 | Applied session: Motion capture and analysis |
| Week 6 | Noise in Biomechanics and signal processing |
| Week 7 | Linear and angular kinetics |
| Week 8 | Particles in motion, centre of mass, how to calculate the centre of mass: Dempster, Clauser regression models for centre of mass. |
| Week 9 | Mid-Term exam |
| Week 10 | Force and pressure sensors, measurement, applications and data processing |
| Week 11 | Inverse dynamics and the link segment model, Inverse dynamics modelling with Simmechanics |
| Week 12 | What is electromyography (EMG)? The relationship between EMG signal and the force applied by muscle. |
| Week 13 | Project Studies |
| Week 14 | Project Studies |
| Week 15 | Preparation for Final Exam and Project Presentation |
| Week 16 | Final Exam & Project Presentations |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | ||
| Laboratory | ||
| Application | ||
| Field activities | ||
| Specific practical training | ||
| Assignments | ||
| Presentation | ||
| Project | ||
| Seminar | ||
| Midterms | ||
| Final exam | ||
| Total | ||
| Percentage of semester activities contributing grade succes | ||
| Percentage of final exam contributing grade succes | ||
| Total | ||
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 0 | ||
| Laboratory | 0 | ||
| Application | 0 | ||
| Specific practical training | 0 | ||
| Field activities | 0 | ||
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 0 | ||
| Presentation / Seminar Preparation | 0 | ||
| Project | 0 | ||
| Homework assignment | 0 | ||
| Midterms (Study duration) | 0 | ||
| Final Exam (Study duration) | 0 | ||
| Total Workload | 0 | 0 | 0 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest