RSscan footscan, Руководство пользователя

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Chapter 19
Risk analysis and the gait ratios graphs.
References:
[1] Franklyn-Miller A, Bilzon J, Wilson C, McCrory P. Can RSScan footscan D3D
software predict injury in a military population following plantar pressure
assessment? A prospective cohort study. Foot 2013;24:6–10.
doi:10.1016/j.foot.2013.11.002.
[2] Franklyn-Miller A, Wilson C, Bilzon J, McCrory P. Foot orthoses in the prevention
of injury in initial military training: a randomized controlled trial. Am J Sports Med
2011;39:30–7. doi:10.1177/0363546510382852.
Description:
The footscan 9 software has the risk analysis and gait ratios graphs as functionality,
these were also present in the footscan 7 software, but were named differently. The
‘D3D software’ in footscan 7 contained the risk analysis and the construction of
insoles. In the footscan 9 software this is divided in the risk analysis screen and the
construction of insoles is available through the Phits and D3D design wizards. The
footscan 9 gait ratios graphs were named the ‘Balance’ graphs in footscan 7.
The risk analysis algorithm used by the footscan 9 software is based on a study of
runners’ service in which long distance runners (100km/week) that were at least three
years pain and injury free (very low injury risk profile) participated as well as knowledge
gained from over 25.000 footscan measurements performed by several collaborating
universities and internal researchers. As the correlation between static foot posture
parameters and dynamics is not confirmed, the aim of this study was to determine
relevant parameters to describe the risk on injury as well as the optimal orthotic support
for an individual based on dynamic plantar pressure measurements (in contrast to the
conventional static techniques used). The relevant parameters derived from this study
are balance within one foot (rearfoot balance during heel strike phase, 0-15% stance
phase (SP); midfoot balance during midstance, 25-40% SP; forefoot balance during
heel off phase, 50-80% SP).
The footscan risk analysis algorithm was scientifically validated in a prospective cohort
study [1] that aimed to identify the ability of footscan to predict the injury risk in 200
male subjects from a military population. Participants were graded using the footscan
risk analysis as to high (≥ 2 correction), medium (= 1 correction) and low risk (= no
corrections) of injury and were followed up for injury through their basic training.
Results showed that participants categorized in the high-risk group for injury were
significantly more likely to sustain injury than in medium or low groups (p < 0.001, OR
5.28 with 95% CI 2.88, 9.70). This proved the predictive value of footscan 9 software in
the correct prediction of lower limb injury risk.
The algorithm was furthered to provide advice towards optimal orthoses based on
individual dynamic plantar pressure measurements. Both a modular insole (D3D insole)
as a 3D printed insole (Phits insole) are based on this algorithm. The effectiveness of
the modular insoles based on the D3D algorithm is proven within a randomized
controlled study [2]. Within this study, 400 male subjects from a military population that
presented medium or high risk on injuries participated. Participants were randomized to
either receive or not receive D3D orthoses (produced based on footscan analysis) and
followed up for injury during their training. Results demonstrated the effectiveness of
the D3D orthoses an absolute risk reduction of 49% from the use of D3D orthoses.
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