2. Gait analysis is based on measurement …
… if we can’t make good measurements
there is no point us being here.
2
3. 3
14 chapters on how to make measurements.
1 chapter on what to do with them.
4. Measuring walking
• Both a science and an art
We need to
• understand the science
• practice the art
Need training in both and there is very little
available (www.CMAster.eu)
4
7. Normative datasets
For too long we have used normative datasets
as an excuse for doing things differently.
Normative data should be compared between
centres to show we are doing the same things
7
8. Normative datasets
8
Differences in average traces suggest systematic differences in how
markers are applied
Differences in standard deviations suggest one lab has more
repeatable practices than the other.
9. Repeatability studies
Measurement science can be quite simple.
All we need to know is the standard error of
measurement (SEM - Standard deviation of
repeat measurements made on the same
subject).
Two measurements need to differ by 3xSEM
for there to be evidence of difference.
9
10. Other repeatability measure
• Never use a repeatability measure you
don’t understand.
• Never use a repeatability measure that is
not expressed in the original units of
measurement.
• Never trust someone else’s definition of
“acceptable repeatability (particularly a
psychologist)
• “For many clinical measurements ICC should exceed 0.9 to ensure
reasonable validity” (Portney and Watkins, 2009)
10
11. Repeatability studies
11
McGinley, J. L., Baker, R., Wolfe, R., & Morris, M. E. (2009). The reliability of three-dimensional kinematic gait measurements: a
systematic review. Gait and Posture, 29(3), 360-369.
SEM<2° “acceptable” don’t
need to consider
measurement
variability explicitly in
interpretation
2°<SEM<5° “reasonable” need to
consider measurement
variability in
interpretation.
SEM>5° “concerning”
measurement
variability may mis-
lead interpretation.
14. Repeatability studies
Require one or more analyst to make repeat
measurements on same person.
If repeat testing of single analyst space
measurements out.
If comparison of multiple analysts have them
close together.
14
17. Formal repeatability study
• Considerable undertaking
• Extremely difficult on children with cerebral
palsy
• Considerable uncertainty in SEM
estimates
17
18. Quality assurance
• Protocols written by team making measurements
– Process more important than result
• Regular review
• Repeatability studies
• Critical self-appraisal
– by individuals
– within teams
– within community (peer review)
• Open and honest culture
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20. Vigilance for errors
• Check data before the patient leaves
• Requires processed data to be available
before then (preferably before markers
removed)
• Keep assessments short and focussed so
that both patient and analyst are prepared
to repeat tests if necessary.
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21. Is the data likely to be
representative for the patient?
• General health
• Pain
• Fatigue
• Behaviour
• No way of telling this from data
22. Agreement with data from other sources –
Clinical exam0
Pst
Hip Flexion
70
-20
Flex
Ext
deg
Knee Flexion
75
-30
Dwn
Hip
30
-30
Add
Abd
deg
Kne
30Bilateral hip flexion contracture
23. Agreement with data from other sources –
Video.
-20
Flex
Ext
deg
Knee Flexion
75
-15
Flx
Ext
deg
Dorsiflexion
30
Dor
deg
-30
Add
Abd
deg
Knee Adduction
30
-30
Var
Val
deg
Ankle Rotation
30
Int
deg
-30
Int
Ext
deg
Kne
30
-30
Int
Ext
deg
Foot
30
Int
deg
Gait data may help explain the video data but it should not contradict it
25. Smooth data
Be very suspicious of jerky data
If one kinetic graph is wrong you should be highly suspicious of all of them even
if artefact is less obvious.
27. Consistent data
• I can’t see all the detail
• Should you be
interpreting detail you
can’t see?
28. Consistent data
• Be particularly careful if traces fall into
groups.
• If this occurs in kinetics but not in
kinematics then check force plates
Picture from J Stebbins
with permission
32. Consequences of marker
placement error
• Play!
• Place markers erroneously on a colleague
and predict changes in gait graphs.
• If you can’t then you shouldn’t be placing
markers on patients at all.
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33. Professional competencies
• Excellent data quality can only be provided by
excellent gait analysts
• Requires combination of biomechanical and
clinical competencies
• In many centres these are provided by different
people
34. Professional competencies
• Gait analysis requires:
– Patient (and parent) management skills
– Physical examination skills
– Biomechanical measurement skills
– Biomechanical analysis skills
• Recruit staff with some of these skills
• Train them in the others
• Longer term training
• Assessed competencies