1. The effect on gait of AFO use in people with ankle
osteoarthritis
Lauren Forsyth1, Philip Rowe2, Andy Kerr2
1- Biomedical Engineering, University of Strathclyde, Glasgow (lauren.forsyth@strath.ac.uk)
2- Biomedical Engineering, University of Strathclyde, Glasgow
Osteoarthritis (OA) is the most common musculoskeletal
disorder in older adults. It affects 8.75 million people in the
UK, with 20% seeking treatment for the foot or ankle (50). It is
a multifactorial process causing degradation of the entire joint
(11). End stage OA can be as debilitating as end stage kidney
disease, or congestive heart failure (5). It is fast becoming a
more prevalent problem with a more obese and aging
population (35).
There is no cure, and treating ankle OA is difficult. Ankle-foot
Orthoses (AFOs) are prescribed daily in clinical practice
acting to externally fuse the ankle but evidence is limited as
to the effects of these on pain, joint degradation and avoiding
surgical treatment.
As osteoarthritic changes develop, pain
and stiffness severely affect the ability to
move (124). Gait adaptations adopted in
an attempt to relieve pain may hinder
stability and balance, increasing the risk of
falling. It is unknown whether an AFO
alters this.
Primary: Does an AFO positively affect the gait of a patient with ankle osteoarthritis immediately after application
and/or after 6 weeks of use?
Secondary: Can biomechanical visualisation be used to assess ankle osteoarthritis patients?
7 VICON cameras set up around a self-paced treadmill.
Step 1: Participant wears clusters of markers and calibrated using
pointer. This produces a visualisation in D-Flow for movement to
be tracked.
Step 2: Participant walks 100 steps. This is performed twice
- with and without AFO.
Hairmyers
Hospital
•12 ankle OA patients recruited
•Participants assessed and cast for an AFO
Coathill
Hospital
• AFO collection and fitting
• Gait analysis without and with AFO
Coathill
Hospital
• Gait analysis without and with AFO
6 weeks later
 Spatiotemporal parameters
 Stability of centre of mass (COM)
- Uncontrolled manifold hypothesis
- Sagittal and frontal ratio of variability
of COM
 Karlsson and Peterson scoring system
for ankle function
Speed
Step
length
Step
time
Stride
length
Stride
time
Stance:
swing %
References
1. Arthritis Research UK. 2013. Osteoarthritis in general practice: data and perspectives [PDF].
2. Bijlsma, J., Berenbaum, F., Lafeber, F. 2011. Osteoarthritis: an update with relevance for clinical practice. The lancet. 377, pp. 2115-2126.
3. Nguyen, M., Pedersen, D., Gao, Y., Saltzman, C., Amendola, A. 2015. Intermediate-term follow-up after ankle distraction for treatment of end-stage OA. Journal of bone and joint surgery. 97,
pp. 590-596.
4. Hunter, D. and Felson, D. 2006. Osteoarthritis. BMJ. 332, pp. 639-642.
5. Schrager, M., Kelly, V., Price, R., Ferrucci, L., Shumway-Cook, A. 2008. The effects of age on medio-lateral stability during normal and narrow base walking. Gait Posture. 28(3), pp. 466-471.
6. Toro, B., Nester, C., Farren, P. 2003. The status of gait assessment among physiotherapists in the United Kingdom. Archives of physical and medical rehabilitation. 84, pp. 84.
Within clinical practice, diagnosis and prescription of
treatment is performed primarily by eye, occasionally aided
by a mirror or video camera.
5 main reasons were apparent for the lack of gait
assessment tools among NHS physiotherapists in the UK:
1. Lack of time (41.8%)
2. Budget constraints (38.8%)
3. Lack of space (28.8%)
4. Lack of awareness (27%)
5. Availability of any tool (27%) (38)
Development of new biomechanical software has the ability
to run applications quickly and easily. This could provide
quantitative real-time feedback which is understandable to
clinicians and patients. Feedback of performance plays a
central role in skill acquisition. Monitoring results and
knowledge of performance could enhance patient diagnosis
and assessment as well as progression during
rehabilitation.
Osteoarthritis & AFOs
Gait analysis and biomechanics
Research Questions
Instrumentation & Protocol Participant Process
Analysis
Figure 3 Strathclyde Cluster model and pointer.
Figure 2. System set up at Coathill Hospital.
Figure 4. Visualisation.
Figure 1. AFO