KNR 257 Lecture Notes - Lecture 1: Scatter Plot

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6 May 2015
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KNR 257 Exam 1 02/09/2015
1. Define…
actions: objective of how someone is moving goal directed movements
example: throwing
skills=actions
movements: actual limb configurations used to achieve actions/skills
differ from person to person and within the skill
actual limb configurations to achieve task
example: throwing(skill)  underhand throw (movement)
2. Types of skills
gross motor skills: large musculature
uses large muscles
example: trampoline
fine motor skills: small musculature
uses smaller muscles
example: painting
discrete: brief, one action (controlled by planning)
example: kick or throw
continuous: non-stop action (controlled by feedback)
example: walking, swimming
open: changing environment
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example: layup  defenders
closed: unchanging environment
example: free throw  always the same
3. Three classifications of continua
fine/gross: what muscles you use
discrete/continuous: duration
open/closed: environment
4. Performance outcome measure
only focuses on the result/outcome
does not indicate movement used to achieve the result
example: field goal %, 40 m dash
5. Performance production measure
focus on the descriptors of movement used
how you obtained the result
example: joint angle changes, position time graphs
6. Reaction Time
time from the presentation (“on set”) of stimulus to the start (“initiation”) of the movement
initiation refers to observed or measured physical movement, and is usually particular to measurement
device
example: 100 meter dash
7. Movement Time
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from the “initiation” of the response to the termination of the response
8. Response Time
The total time
The time from the signal all the way until the termination of the response
9. Simple vs. Choice Reaction Time
simple reaction time: one signal, one action
choice reaction time: more than one signal, more than one action
10. Absolute error
accuracy
average of positive deviations from the target
the average distance between errors
positive and negative cancel each other out
11. Constant Error
bias
average deviation positive and negative both count
average position  a “bit short” or a “bit long”
12. Variable error
consistency
grouping how close are the throws from each other?
Clustering
13. Angle-angle diagrams
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