Transcript Error Measures in Motor Learning

Measurement of Error in Motor Behavior
Emily Wughalter, Ed.D.
Error Measures
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Error measures provide detail about performance
accuracy in meeting a moving object in space. Error
measures help to quantify performance.
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For example
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As in swinging a bat and meeting a ball in space with the end of a bat
As in wanting to click on an icon by moving cursor on the screen
As in grabbing a stick of deodorant from the medicine cabinet
As in hitting a golf ball off a T, or in hitting the golf ball so that it is
precisely directed in its flight and for its landing location
As in driving a car and being able to drive in a lane with acceptable
variability
Measuring Error
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Error measures are calculated to explain movement
phenomena. They are calculated by applying varying
algorithms. Error measures can help explain performance
in matching personal movement to a moving or stationary
object in space over a series of trials (trial blocks) .
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Consider validity
Consider ecological validity
Consider reliability
Consider objectivity
Consider assumptions
Consider practical value and need
Three Error Measures in Motor Learning
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Constant error
Variable error
Absolute error
Constant Error (CE)
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CE provides information about a performer’s response
bias
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Does the performer generally respond early (undershoot) or
late (overshoot) with respect to the target or matching
location of a movement?
Does the performer have a general tendency?
CE is determined by adding up the algebraic error scores
and dividing by the number of scores or calculating the
mean.
CE should be presented with VE to more fully understand
its meaning.
Variable Error (VE)
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VE helps explain the changes or fluctuations in
performance across a series of trials between a position
in space and the matching of that position.
Calculate VE as the standard deviation of a set of scores
(trial block)
Absolute Error
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AE measures the average difference or average total error
between the target location and the matching
performance across a series of trials.
Calculate absolute error by obtaining the mean of the
absolute value of the algebraic error scores for a series of
trials.