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from each of the 2 operator.

Abstracts / Gait & Po

3) the longitudinal axis of the humerus, according to the followingchema:

Regardless of the study we also measured the execution timef the test (reception and patient preparation, system calibration,mplementation and enforcement without registration with reg-stration test) between 10 and 12 min. The acquisition phase iso make to the patient in a passive manner, and assisted by anperator, abduction–adduction of the shoulder, according to a pre-etermined trajectory and recording the quantities specified above.e evaluated 3 times at different times and with different opera-

ors (T1, T2 and T3), 50 healthy control subjects aged between 18nd 50 years.

esultsThe results are shown in the table below. Angles of abduc-

ion and adduction of the upper ranged on average between 5.6◦

nd 117.3◦ at the first measurement, between 4.9◦ and 116.4◦

t the second measurement and between 5.2◦ and 113.2◦ at thehird measurement, noting homogeneity and repeatability in mea-urements, and no statistical significance in comparisons betweenroups p < 0.05 (Student’s t-test).

Min(media)

DevStd(min)

Max(media)

DevStd(max)

Misura Angolo(max − min)

T1 5.6◦ 1.5◦ 117.3◦ 2.1◦ 111.7◦T2 4.9◦ 1.4◦ 116.4◦ 1.9◦ 111.5◦T3 5.2◦ 1.4◦ 113.2◦ 2.0◦ 108.0◦

iscussionThe results, although performed only for the movement in

bduction of the shoulder joint, for ease of performance, repeata-ility and reproducibility and accuracy compared with analyticalssessments made by different goniometers, seem to confirmhe hypothesis that goniometric measurement system through anvaluation tool El.i.Te. is easy to apply and effective. Further devel-pment of the study will be able to use this tool in patients witheurologic outcome, including non-compliant ones [2].

eferences

1] Boccardi S, Lissoni A. Cinesiologia, vol. II. Società Editrice Universo, Roma.2] Melinda Rybski, Kinesiology for occupational therapy. p. 26–32 [Chapter 3].

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33S (2011) S1–S66 S43

P14

Comparison between multiple calibration and direct skin mark-ers in multisegment foot 3D kinematics

A. Guiotto 1, Z. Sawacha 1, C. Fassina 1, L. Tersi 2, S. Fantozzi 2, R.Stagni 2, C. Cobelli 1

1 Department of Information Engineering, University of Padova,Padova, Italy2 Department of Electronics, Computer Sciences and Systems, Univer-sity of Bologna, Bologna, Italy

IntroductionSoft tissue artefact (STA) has been identified as one of the most

important sources of error in gait analysis and has been recognizedto critically affect relevant joint kinematics. So far many publica-tions and research focused on developing methods to compensatefor STA [1] and among these, multiple calibration (MC) resultedparticularly effective in compensating for STA propagation to kneekinematics [2]. The purpose of the present work was to assessthe performance of the MC in quantifying subject-specific multi-segment foot 3 dimensional (3D) kinematics during gait and tocompare this method with the single calibration (SC) [4] and theanatomical landmarks direct skin marker placement (DS) method[3].

Materials and methodsA 3D multisegment foot protocol [3] was applied on the same

subject first by means of DS and second in a modified version whichentails calibrating each anatomical landmark with respect to a localcluster of marker. Six cameras BTS S.r.l. motion capture system(60–120 Hz) were used to acquire 3 walking trials and a static one.MC was performed [2] in 3 different positions: maximum passiveplantarflexion (Fig. 1a), neutral position (Fig. 1b), maximum passivedorsiflexion (Fig. 1c). The MC procedure was carried out by 2 physi-cians (op1 and op2) in order to test the inter-operator repeatabilityof this technique. Anatomical reference frames were computed and3D foot subsegment relative angles, during the stance phase of gait,were calculated through DS [3], SC with the calibration in neutralposition [4] and MC [2]. The latter was performed using, as controlvariable, the ankle dorsi/plantarflexion (DP) angle evaluated withthe SC. The following relative angles were evaluated over the stancephase of gait: DP, inversion/eversion (IEV) and internal/externalrotation (IER) of hindfoot–tibia (HT), midfoot–hindfoot (MH) andforefoot–midfoot (FM). Coefficients of multiple correlation (CMC)[5] and intra-class correlation (ICC) [6] were also estimated for eachsubsegment angle evaluated applying the 3 methods performed

ResultsMean and standard deviation have been reported for the 3 meth-

ods in operator 1 (Table 1). In Tables 2 and 3 the results of the

Fig. 1. Multiple calibration.

dx.doi.org/10.1016/j.gaitpost.2010.10.051

S44 Abstracts / Gait & Posture

Table 1Foot subsegments angles.

DS SC MCMean ± SD Mean ± SD Mean ± SD

HTIEV 6.8 ± 2◦ 7.9 ± 2.2◦ 6.2 ± 0.4◦HTIER −6.1 ± 2.6◦ −5.7 ± 2.9◦ −11.2 ± 2.5◦HTDP 23.1 ± 2.6◦ 26.3 ± 3.8◦ 23.6 ± 2.8◦MHIEV 20.3 ± 1.2◦ 16.4 ± 2.8◦ 22.7 ± 3.3◦MHIER −3.3 ± 4.2◦ −1.2 ± 1.8◦ −0.5 ± 0.9◦MHDP 22.9 ± 4.1◦ 13.9 ± 5.2◦ 18.7 ± 2.9◦FMIEV −18.2 ± 1.4◦ −15.8 ± 0.8◦ −15.4 ± 1.1◦FMIER 12.7 ± 2.9◦ 10.3 ± 0.4◦ 13 ± 1.4◦FMDP 8.7 ± 6.3◦ −6.2 ± 2.4◦ −8.7 ± 2.4◦

Table 2CMC and ICC coefficients for the comparisons between the trials, the methods andthe operators. *ICC > 0.75; *CMC > 0.75.

CMC (a) – op 2, trials 1–3

SC MC

HTIEV 0.35 ± 0.713 0.03 ± 1.232HTIER 0.88 ± 0.241* 0.81 ± 0.302*HTDP 0.87 ± 0.323* 0.89 ± 0.184*MHIEV 0.73 ± 0.542 0.84 ± 0.301*MHIER 0.63 ± 0.561 0.80 ± 0.667*MHDP 0.84 ± 0.234* 0.40 ± 0.8FMIEV 0.98 ± 0.045* 0.88 ± 0.503*FMIER 0.92 ± 0.151* 0.94 ± 0.131*FMDP 0.52 ± 0.756 0.65 ± 0.184

Table 3CMC and ICC coefficients for the comparisons between the trials, the methods andthe operators. *ICC > 0.75; *CMC > 0.75.

ICC (b) – op1 ICC (c) – op1 vs op2

co(

D

tovcmo

R

[[[[[[

d

MP vs CS vs cm SC MC

HT 0.99 ± 0.01* 0.98 ± 0.01* 0.98 ± 0.005MH 0.95 ± 0.02* 0.84 ± 0.05* 0.72 ± 0.04FM 0.94 ± 0.01* 0.86 ± 0.01* 0.85 ± 0.004*

omparison among (a) the 3 trials, (b) the 3 methods and (c) the 2perators have been reported in terms of CMC and ICC coefficientsTables 2 and 3).

iscussionThe present results did not show important differences among

he 3 methodologies in term of repeatability. So far future devel-pments will include first the introduction of a specific controlariable for evaluation of FM kinematics (i.e. FM DP), second theomparison of the 3D multisegment foot kinematics obtained byeans of stereophotogrammetry with the one provided by 3D flu-

roscopy in each tested condition.

eferences

1] Peters A, et al. Gait Posture 2010;31(1):1–8 [Systematic Rev].2] Cappello A, et al. IEEE-TBE 2005;52(6):992–8.3] Sawacha Z, et al. J Neuroeng Rehabil 2009;23:6–37.

4] Cappozzo A, et al. Clin Biomech 1995;10(4):171–8.5] Kadaba MP, et al. J Orthop Res 1989;7:849–60.6] Patrick E, et al. Psychol Bull 1979;86(2):420–8.

oi:10.1016/j.gaitpost.2010.10.052

33S (2011) S1–S66

P15

Use of a novel graphical representation in gait analysis for trunkkinematics

F. Biagi 1,2, A. Merlo 1,2, M.G. Benedetti 1,2, L. Berti 1,2, A.Leardini 1,2

1 Movement Analysis Laboratory, Istituto Ortopedico Rizzoli, Bologna,Italy2 Movement Analysis Laboratory, AUSL di Reggio Emilia, Correggio,Italy

IntroductionGait analysis provides a large number of kinematics and kinet-

ics variables by means of modern instrumentations and protocols.These data are utilised clinically to distinguish between differentpopulations of patients, as well as to follow the functional recoveryof a single patient, typically before and after treatments. In mostof these cases, also a control population is analysed as reference.This complex analysis is usually performed visually on the variabletime-history plots over the gait cycle, where patterns from the sub-ject populations are represented by colour bands. Typically a solidcurve represents the time-history of the average, a band reportsthe average plus and minus one standard deviation at each time-normalised sample, conveying the concept of the range of relevantnormal motion, or moment/power. This graphical representationsuffers of several limitations, including the sensibility to outliersand the necessary symmetry along the average. A novel represen-tation, proposed in [1], is used, to signify better the original curvesfrom which a summarising description is however necessary. Thisis exploited initially on gait variables describing multi-segmentkinematics of the upper body, according to an original protocol [2]defined after comparisons of a number from the relevant literature[3].

Materials and methodsThe thorax segment (Tho) was tracked by optimal spatial match-

ing of four thoracic markers; its rotations both in the laboratory(Lab) and pelvis (Pel) reference frames were calculated accordingto standard conventions. The separate shoulder line (Sh) rotationswith respect to the thorax were calculated by markers on thetwo acromions. These were tracked (Vicon Motion Systems) in 10healthy subjects during level walking, step up/down and chair ris-ing/sitting. One curve over the three repetitions was selected fromeach subject. The novel graphical representation is based on per-centiles, and does not make any assumption on data distribution.

ResultsExemplary original curves are shown (Fig. 1.) together with the

traditional and novel representations of the motion bands. In addi-tion to the different specific sides over the average curve, the novelcan reveal better the presence of two distincts patterns (see Chair),either for the magnitude or for the timing of the peaks.

DiscussionThe graphical representation of the typical bands for

population-to-population and patient-to-control assessments

is here dealt with. The present technique, in addition to twodifferent groups of curves, i.e. distinguished percentile ranges, isable to represent deviations differently above and below the meancurve. It can be used also on small sample sizes and is robust tooutliers.

dx.doi.org/10.1016/j.gaitpost.2010.10.052