Integrated Movement Analysis

Curriculum guideline

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Course
SPSC 3154
Discontinued
No
Course code
SPSC 3154
Descriptive
Integrated Movement Analysis
Department
Sport Science
Faculty
Science & Technology
Credits
3.00
Start date
End term
Not Specified
PLAR
No
Semester length
15 weeks
Max class size
30
Course designation
None
Industry designation
None
Contact hours

Lecture: 3 hours/week

and

Lab: 1 hour/week

Method(s) of instruction
Lecture
Lab
Learning activities

Classroom time will be used for lectures, small and large group discussions, problem-based learning, reflections, lab-based activities and/or in-class assignments.

Course description
This course provides students with an overview of comprehensive and observational diagnostic models to evaluate human movement. Using inquiry-based approaches, this course integrates and applies principles from kinesiology sub-disciplines to movement diagnosis. Students use various data acquisition technologies to evaluate and improve human movement and performance in three different contexts: lab, field and clinic.
Course content
  • Movement diagnosis framework
    • Applications of movement diagnosis in kinesiology
    • Interdisciplinary – intradisciplinary contributions
    • Models of movement diagnosis
    • Differences between context: the lab, field and clinic
  • Sensory and perceptual contributions to movement
    • Theoretical background
    • Human movement diagnosis from both the performer and observer perspective
    • Concepts of motor control and learning related to movement diagnosis
    • Application of biomechanics concepts to movement diagnosis
  • The four tasks of movement diagnosis analysis
    • Preparation, observation, evaluation and diagnosis, and intervention. 
  • Technologies in movement diagnosis
    • Motion capture technology
    • Computer, tablet and smartphone technology with various motion analysis software or apps
    • Force acquisition, electromyography and/or accelerometer instrumentation to supplement diagnosis of motor performance
    • Emerging movement analysis technologies
    • Data collection, processing, interpretation and presentation
Learning outcomes

Upon successful completion of the course, students will be able to:

  • reflect on and apply experiential and academic knowledge from various kinesiology sub-disciplines to a movement diagnosis model;
  • apply experiential and academic knowledge to analyze human movement;
  • determine performer characteristics and analyze a variety of movement patterns from that performer;
  • evaluate and diagnose human movement performance strengths and errors;
  • prescribe and implement intervention strategies for improving human movement performance;
  • apply movement diagnosis models to lab, field and clinical settings;
  • collect, process, interpret and present data from video capture with motion analysis software, force acquisition and/or electromyography technologies.
Means of assessment

Assessment will be in accordance with the ÌÇÐÄvlog´«Ã½Evaluation Policy. The instructor will present a written course outline with specific evaluation criteria at the beginning of the semester. Evaluation will be based on the following:

Term Test(s)                                                 10-25%
Movement Diagnosis Project(s)                      10-30%
Presentation(s)                                               0-20%
Labs (minimum 3)                                         20-60%
Assignments/Reflections                                  0-20%
Participation                                                   0-10%

Total         100%

Textbook materials

Consult the ÌÇÐÄvlog´«Ã½Bookstore for the latest required textbooks and materials. Example textbooks and materials may include:

Knudson, D. (Current Edition) Qualitative Diagnosis of Human Movement: Improving Performance in Sport and Exercise. Human Kinetics Publishers.

Prerequisites

60 Credits, including SPSC 1151 and SPSC 1164

Corequisites

None

Equivalencies

None