Cga ifa 2015 6 measurement artefact

1. Recognising artefact
Richard Baker
Professor of Clinical Gait Analysis
Blog: wwRichard.net
1

2. Artefact
Any non-natural feature accidentally
introduced, e.g. during a scientific study.
2

3. Artefact
Important to recognise to prevent incorrect
interpretation of results.
Important to recognise to improve
measurrement technique.
Ability to recognise artefact is strongly
indicative of your understanding of the
measurement process.
3

4. Sources: Gait data
• Marker misplacement
• Marker movement
• Variable gait pattern
• Soft tissue artefact
• Modelling error
• Gap filling
• Force plate malfunction
• “Dirty” force plate contact
• Poor system calibration
4

5. Repeatability studies
5
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.

6. Sources: Physical exam
• Measurement technique
• Measurement variability
6

7. Physical examination
McDowell et al. Gait & Posture, 2000Fosang et al. Dev Med Child Neurol, 2003

8. Recognising artefact
• Some artefacts have characteristic shapes
• Most are recognised through
inconsistencies between different types of
data
• Some artefacts are more likely than others
so you should develop a sense of where to
look
8

9. Recognising artefact
• Looking at the video can be extremely
useful for recognising artefact.
• Gait data should explain what you are
seeing on video but should not contradict it.
9

10. Consequences of artefact
• Artefacts rarely affect one graph in isolation
• If you identify a possible artefact on one
graph always think carefully as to whether it
might also be affecting other data,
10

11. Some artefacts are more likely than
others so you should develop a sense
of where to look
11

12. Knee axis malalignment
12

13. 13
Knee axis malalignment

14. Knee axis malalignment
5° offsets of KAD

15. Knee axis malalignment
5° offsets of KAD

16. Pelvic obliquity
16

17. Pelvic obliquity
17

18. Hip flexion
18

19. Hip flexion
19
13 year old boy with diplegic
cerebral palsy
Gait data suggests reduced
anteriot pelvic tilt …
… and good hip extension

20. Hip flexion
20

21. Hip flexion
21

22. Hip flexion
22
Left Right Left Right
Hip extension range
(Thomas)
5°flex 3°flex Dorsiflexor strength 4+(2) 4(2)
Hip flexor strength 4(0) 3+(1) Confusion (+/-) pos(inv) pos(inv)
Hip extensor strength (knee
0°) 4(0) 4(0) Dorsiflexion (knee 90°) 3°df 10°df
Hip extensor strength (Knee
90°) 3(0) 3(0) Dorsiflexion (knee 0°) 3°pf 5°df
Hip abduction range (hip 0,
knee 0)
25°abd 27°abd
Plantarflexor spasticity
(Tardieu)
30°pf 7°pf
Hip abduction range (hip 0,
knee 90)
nt nt
Plantarflexor tone
(Ashworth)
1+ 1
Hip abductor strength 4(2) 4(2)
Plantarflexor strength
(knee 90°)
4(2) 4+(2)
Hip adductor tone
(Ashworth)
1 1 Invertor strength 4(1) 4(1)
Hip internal rotation range 78°int 78°int Evertor strength 4+(2) 4+(2)
External rotation range 25°ext 23°ext
Femoral anteversion 26°int 26°int Tibial torsion 10°ext 7°ext
Knee extension range
(capsule)
8°hyp 6°hyp Thigh-hindfoot angle 6°int 0°
Popliteal angle 60°flex 60°flex Hindfoot-forefoot angle 5°int 6°int
True popliteal angle 55°flex 52°flex Ankle equinus/calcaneus
mild
calcaneus
mild
calcaneus
Dynamic popliteal angle 68°flex 90°flex Hindfoot valgus/varus
moderate
valgus
mild
valgus
Knee flexor strength 4(0) 4(0) Planus/cavus
severe
planus
severe
planus
Knee extensor strength 4+(0) 4(0) Forefoot abd/add neutral neutral
Quadriceps lag 5°flex 0°flex
Duncan-Ely (slow) rise rise Weight (kg) 33kg
Duncan-Ely (fast) rise rise Height (cm) 145cm
True leg length (cm) 78cm 79cm
GMFCS III Apparent leg length (cm) 83cm 84cm
FMS 551

23. Hip flexion
23
On basis of gait data and
clinical exam we suspect that
anterior pelvic tilt might be
under-estimated and hip
extension over-estiamted.

24. Gait variability
24

25. Average trace
25

26. 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

27. 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.

28. Swing phase ankle moments

29. Smooth data
Gait data is almost always smooth (it has
been filtered to be so)

30. Protecting against artefact
30

31. Quality assurance
• Staff training and education
• Vigilance for errors in data

32. 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
32

33. Normative datasets
33
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.

34. Informal repeatability study
34
Measurements from three therapists (different colours) each
measuring the same person on two different days

35. 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.
35

36. 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

37. 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

38. Thanks for listening
Richard Baker
Professor of Clinical Gait Analysis
Blog: wwRichard.net
38