Pedobarographic Features of Gait Measured by FDM1.5 PMD

Igor Gruić, Karlo Cebović, Josipa Radaš, Filip Bolčević and Vladimir Medved

Faculty of Kinesiology, University of Zagreb, Horvaćanski zavoj 15, 10000 Zagreb, Croatia

Keywords: Pedobarography, Gait, PMD, Pressure Acquisition Protocol, Data Processing, Biomechanics.

Abstract: Backgrounds: Main objective was to evaluate methods for assessment of pedobarographic features of gait

using FDM1.5 pressure measuring device (PMD) - within complete gait analysis, with regard to device,

protocol&data analysis, specifically to basic morphology and certain distinctive characteristics. Methods:

Protocol was standardized for descriptive&inferential statistical methods (63 quantitative variables).

Participants characteristics (n=22; 13 male&9 female): age 14-35 y.o., average 172,56cm body height,

average 73.11kg body mass (19.47 BMI), with minimum of 5 years of regular sport&recreational activities.

Results: Protocol output was consistent for repeated measurement of an individual. Tested differences

between genders, before&after ‘partialization’ of results (excluded influence of longitudinal

dimensionality), in both cases reveal significance in: Stride width (t_GSW=4.15), Step time_L

(t_TSTL=2.88), Step time_R (t_TSTR=3.59), bilateral asymmetry in Step time (t_TST_D=3.32), Cadence

(t_TC=-3.44) on p<0.01 level, and Ant/Post position (t_BAP=2.33), bilateral asymmetry in Time to change

heel to forefoot(t_LTP_D=2.26), Time maximum force Midfoot_D % of stance time (t_TMAXM=2.33), and

bilateral asymmetry in Contact time Heel (t_CH_D=2.33), on p<0.05 level. Differences in

barefoot/footwear gait were specially expressed in variable MAXPH (t= -8.84, p<0.05). Conclusions:

Statistical tools, such as partializations of the results by specific characteristic which tend to increase

heterogeneity, may standardize&improve the power of the protocol and method.

1 INTRODUCTION

During ordinary activities, trainings, or

competitions, high intensity foot-ground contacts

affect adaptation depending on movement structure,

type of surface, and generally, footwear. Health

effects of barefoot gait, incidence of injuries and

functional pathologies, footwear characteristics etc.,

are covered trough meta-analysis and reviews (e.g.

Giacomozzi, 2011), primarily in order to standardize

plantar pressure measurement protocols

(Giacomozzi, 2010, Giacomozzi et al, 2012)

Complementarities of normal functions of ankle

joint is conditioned by predisposed and phenotype

factors. Articulatio Talocruraris as angle joint covers

dorsal and plantar flexion (tibia, fibula, and talus).

Art. subtalaris covers inversion and eversion (talus,

calcaneus, cuboideum). Distal interfalangeal joints

as angle joints cover flexion and extension

(phalanges).

In order to reliably associate local pressure data

with foot function and structure, anatomy-based

masking of footprints is recommended (Giacomozzi

et al., 2012). Previous to iFAB-PG convergences (in

Giacomozzi, 2010), simple optic systems, e.g.

Sheffield system (Franks, 1997), were used. Pressure

distribution can be seen as the effectiveness of the

musculoskeletal system in absorbing the ground

reaction forces via the foot and its joints. Excessive

foot pressure may develop into calluses, which

become sites of peak pressure and pain (Caravaggi

et al 2014). Therefore, in assessment of data about

feet structure and function, new kinetic and

kinematic pressure measurement devices (PMDs)

are used (insoles, platforms, trackways, mats, etc.).

After leaving optical systems (Sheffield), new

approach was e.g. in Giacomozzi (2012) usage of

the Oxford kinematic foot model for medio-lateral

regionalisation of the foot – clinically relevant for

clubfoot and flatfoot – and e.g. the Rizzoli model for

longitudinal regionalisation, to clearly distinguish

metatarsal from toe or midfoot loading.

Besides classical kinetic approach for

measurement of vertical (Fz), antero-posterior (Fy)

and medio-lateral (Fx) forces (ELITE system,

Medved and Kasović, 2007), new templates for

plantar pressure measurements were offered by

different producers (e.g. in Giacomozzi, 2010).

Template for Segmented Foot Regions and Length

Measurements (FootMat software, Tekscan) where

Gruic, I., Cebovic, K., Radas, J., Bolcevic, F. and Medved, V..

Pedobarographic Features of Gait Measured by FDM1.5 PMD.

In Proceedings of the 3rd International Congress on Sport Sciences Research and Technology Support (icSPORTS 2015), pages 66-71

ISBN: 978-989-758-159-5

Figure 1: Examples of kinematic&kinetic models for foot analysis (Zebris: ref 13., Tekscan: Cousins et al, 2012.; Rizzoli:

Leardini et al, 2007.; Oxford: Stebings et al, 2006.).

“reliable plantar pressure data that can be collected

in children, aged 7 to 11 years in all regions of the

foot except the lesser toes which consistently

reported poor-to-moderate levels of reliability and

increased variability.” (Cousins et al, 2002), Novel,

Zebris and other, offered their foot model (Figure

1.).

Plantar pressure measurement devices (PMDs)

are now widespread mostly (Giacomozzi et al.,

2012): in the biomechanical research, in the clinical

context, as a key instrument for the prescription,

design and construction of plantar orthoses.

Biomechanical measurements and analyses in

general, encompass spatial kinematic variables,

ground reaction force, and multi-channel surface

electromyography (sEMG) (Medved and Kasović,

2007).

Main objective in this paper is to join, to support,

and to be in line, with mission of three main sections

within i-FAB-PG - 1)Technical Assessments, 2)

Data Analysis and 3) Applications, e.i. evaluation of

methods for assessment of pedobarographic features

of gait using FDM 1.5 PMD (Zebris Medical,

Gmbh).

Trough initial insight of possibilities that FDM

1.5 platform offers, it is a goal: 1) to test

preconditions for standardization of measuring

protocol for complete gait analysis within

Biomechanics Laboratory, Institute of Kinesiology,

Faculty of Kinesiology (analysis of metric

characteristics of tests, trough basic pedobarographic

indicators of forces, pressures, time-spatial, and

derived indicators, bilateral asymmetries), 2) to test

relations of pedobarographic characteristics with

basic morphology (later with kinetic and isokinetic),

and 3) to analyse differences with regard to

distinctive characteristics (e.g. gender, body height,

bilateral asymmetries, barefoot/footwear, ect.), in

order to capacitate laboratory for more demanding

analysis regarding different kinesiological activities.

2 METHODS

Measurement protocol: from initial standing position

(barefoot), subject walks over the trackway 9,5 m

long (with centrally positioned 158 cm long and 60,5

cm wide platform - FDM1.5, ZEBRIS medical,

Gmbh; sensor area 149,0x54.2 cm – L x W,

sampling rate 100 Hz, optional 200 Hz/300 Hz), to

the end of the trackway, turns around and goes back

(6 times). During the gait, subject should be

instructed to develop and reach velocity normal for

aiming him/herself towards ordinary activity/duty

when there are no disturbing gait aspects (late for

meeting, uncomfortable footwear, company etc.).

Measurements on platform are supported by 11264

capacitive sensors with density of 1.4 sensors/cm2,

with measuring range 1-120 N (accuracy ±5% FS).

Reports (accessible by Zebris Medical FDM

software for qualitative and quantitative analysis; for

reliability Zebris refers to Giacomozzi C, 2010)

offer 63 quantitative variables and graphics within

groups (table 1): pressure plots, gait parameters

(geometry, phases, timing) COP analysis,

force&pressure parameters&curves, three foot zone

analysis (Zebris model). Protocol was standardized

for descriptive and inferential statistical methods.

Normality of distributions of results was tested with

K-S test, reliability with Cronbach alpha: 0.99

(Standardized alpha: 0.99), homogeneity with

Average inter-item corr.: .99. Participants

characteristics (n=22; 13 male, 9 female): age 14-35

y.o., average 172,56 cm body height, average 73.11

kg body mass (and average 19.47 BMI), with

minimum of 5 years of regular sport and recreational

activities.

Pedobarographic Features of Gait Measured by FDM1.5 PMD

Table 1: Pedobarographic variables (Zebris protocol).

code description, unit, (L/D) code description, unit, (L/D foot) code description, unit, (L/D foot)

GFRL Foot rotation, degree L BLL Length of gait line, mm L MHL Maximum force H, N L

GFRR Foot rotation, degree D BLR Length of gait line, mm D MHR Maximum force Hl, N D

GSLL Step length, cm L BSL Single support line, mm L MAXPFL Max pressure FF, N/cm2 L

GSLR Step length, cm D BSR Single support line, mm D MAXPFR Max pressure FF, N/cm2 D

GSL Stride length, cm BAP Ant/Post position, m

MAXPML Max pressure MF, N/cm2 L

GSW Stride width, c

BLS Lateral symmetry, m

MAXPMR Max pressure MF, N/cm2 D

PSTPL Stance phase, % L FMF1L Maximum force1, N L MAXPHL Max pressure H, N/cm2 L

PSTPR Stance phase, % D FMF1R Maximum force1, N D MAXPHR Max pressure H, N/cm2 D

PSTLRL Load response, % L FTMF1L Time maximal force1, % L TMAXFL Time max force FF, %L*

PSTLRR Load response, % D FTMF1RTime maximal force1, % D TMAXFR Time max force FF , % D *

PSTMSL Mid stance, % L FMF2L Maximum force2, N L TMAXML Time max force MF, %L*

PSTMSR Mid stance, % D FMF2R Maximum force2, N D TMAXMR Time max force MF, % D *

PSTPSL Pre-Swing, % L FTMF2L Time maximal force2, % L TMAXHL Time max force H, %L*

PSTPSR Pre-Swing, % D FTMF2RTime maximal force2, % D TMAXHR Time max force H, % D *

PSWPL Swing phase, % L LTL Time to change heel to FF, sec L CFL Contact time FF, %L*

PSWPR Swing phase, % D LTR Time to change heel to FF, sec D CFR Contact time FF, % D *

PDSTP Double stance phase, % LTPL Time to change heel to FF, % L CML Contact time MF, %L*

TSTL Step time, sec L LTPR Time to change heel to FF, % D CMR Contact time MF% D *

TSTR Step time, sec D MFL Maximum force FF, N L CHL Contact time H, %L*

TST Stride time, sec MFR Maximum force FF, N D CHR Contact time H, % D *

TC Cadence, steps/min MML Maximum force MF, N L TVI

ody height

TV Velocity, km/h MMR Maximum force MF, N D

eg height

(*% of stance time; FF-Forefoot, MF-Midfoot, H-Heel)

Table 2: Pedobarographic parameters (n=22;'_D’ is measure of bilateral asymmetry (L – R =_D)).

code X±SD code X±SD code X±SD code X±SD

TVIS 172.56±15.97 PSWPL 38.75±1.88 FMF2L 705.23±213.29 MAXPML 10.65±5.58

L_ASIS 97.81±9.56 PSWPR 37.62±2.15 FMF2R 711.08±199.45 MAXPMR 12.42±6.00

D_ASIS 98.87±9.74 PSWPR_D 1.13±1.87 FMF2_D -5.85±30.73 MAXPM_D -1.77±4.21

ASIS_D -1.06±2.40 PDSTP 23.65±3.39 FTMF2L 45.73±1.80 MAXPHL 39.41±11.59

GFRL 8.15±4.09 TSTL 0.55±0.05 FTMF2R 46.45±1.74 MAXPHR 40.13±11.51

GFRR 9.94±4.45 TSTR 0.54±0.05 FTMTF2_D -0.73±2.45 MAXPH_D -0.72±5.17

GFR_D -1.79±4.84 TST_D 0.01±0.02 LTL 0.25±0.06 TMAXFL 75.13±2.00

GSLL 67.86±9.74 TST 1.09±0.09 LTR 0.24±0.06 TMAXFR 75.32±1.67

GSLR 69.82±5.72 TC 111.41±9.40 LT_D 0.01±0.05 TMAXF_D -0.19±1.30

GSL_D -1.95±10.11 TV 4.56±0.54 LTPL 36.36±6.13 TMAXML 42.22±8.74

GSL 137.73±12.13 BLL 217.33±32.63 LTPR 34.25±6.78 TMAXMR 39.71±8.72

GSW 11.50±3.61 BLR 223.74±22.34 LTP_D 2.11±4.39 TMAXM_D 2.50±6.51

PSTPL 61.25±1.88 BL_D -6.41±19.01 MFL 694.84±196.64 TMAXHL 18.35±3.00

PSTPR 62.38±2.15 BSL 131.04±14.45 MFR 700.46±193.24 TMAXHR 17.08±3.23

PSTP_D -1.13±1.87 BSR 131.29±17.70 MF_D -5.62±21.33 TMAXH_D 1.27±2.70

PSTLRL 12.05±1.69 BS_D -0.25±11.74 MML 122.55±69.23 CFL 89.78±2.77

PSTLRR 11.48±1.89 BAP 137.99±15.71 MMR 142.56±74.94 CFR 89.66±3.60

PSTLR_D 0.57±1.46 BLS -1.47±2.96 MM_D -20.01±29.40 CF_D 0.12±1.58

PSTMSL 37.63±1.82 FMF1L 679.59±187.11 MHL 490.35±119.63 CML 66.95±6.87

PSTMSR 38.89±1.85 FMF1R 684.57±186.33 MHR 476.80±108.42 CMR 68.39±6.28

PSTMS_D -1.25±1.71 FMF1_D -4.99±31.78 MH_D 13.55±34.54 CM_D -1.44±5.36

PSTPSL 11.49±1.90 FTMF1L 19.00±23.98 MAXPFL 42.14±10.21 CHL 53.52±8.60

PSTPSR 12.15±1.87 FTMF1R 14.23±1.57 MAXPFR 42.05±11.52 CHR 50.84±9.29

PSTPS_D -0.66±1.73 FTMF1_D 4.77±23.78 MAXPF_D 0.09±5.27 CH_D 2.69±5.63

icSPORTS 2015 - International Congress on Sport Sciences Research and Technology Support

Collected data were processed within

Reliability/Item analysis, K-S normality tests,

descriptive analysis, correlation analysis, t-test, in

Statistica for W/5.0.

3 RESULTS

Pedobarographic features of normal gait are

presented trough results in 63 standard, and 29

derived variables in Table 2. Gender based

heterogeneity of subjects is presented in Table 3.,

and differences based on barefoot/footwear gait (as

additional source of heterogeneity) in Table 4.,

followed by Figure 2. Results in Table 5 present

gender based differences in certain pedobarographic

features before and after using statistical tools for

excluding common variance.

Table 3: Longitudinal dimensionality by gender (X±SD;

M=13, F=9); t-test differences.

x_M x_F t-value p

TVIS 178.59±14.41 163.84±14.60 2.35 0.03

L_ASIS 101.35±8.45 92.70±9.12 2.28 0.03

D_ASIS 102.55±8.37 93.56±9.50 2.34 0.03

Table 4: T-test for barefoot/footwear differences.

Mean SD t

MAXPH_barefoot -1.8 4.37

-8.84

0.01

MAXPH _shoes 0.9 4.16

4 DISCUSSION & CONCLUSIONS

Different approaches to assess pedobarographic

features of gait (e.g. (Lorkowski and Zarzycki, 2006;

Skopljak et al., 2014; Pomarino and Pomarino,

2014; Maurer et al., 2014, ect.), bring conclusions

based on different PMDs and protocols. Consistency

and repeatability were provided.

Pedobarographic parameters, acquired by

measurement protocol on tested PMD, have shown

consistent output for repeated measurement of an

individual. However, within small data base and

heterogeneous sample of participants, conclusions

and generalizations are limited. It is the case in this

paper, too.

Statistical tools, however, may improve power of

the method. By ‘partializations’ of the results by

specific characteristic which tend to increase

heterogeneity (age, sex, longitudinal dimensionality,

bilateral asymmetries, time-spatial parameters, etc.)

Table 5: Pedobarographic features; analysis of differences by gender (t-test), correlations between anthropometric variables

(M+F), and variables differentiating two groups by gender criterion (r), and analysis of differences by gender after

partializations on longitudinal dimensionality (t-test (p)).

X ±SD (M=13, F=9) r

t-test t -test(p)

code

X ±SD _M X ±SD _F TVIS LASIS DASIS t p t p

GSW 13.85±2.67 8.11±1.27 0.53 0.56 0.51 5.96 0.00 4.15 0.00

TSTL 0.57±0.03 0.51±0.03 0.53 0.49 0.51 4.44 0.00 2.88 0.01

TSTR 0.57±0.03 0.50±0.03 0.54 0.50 0.49 5.39 0.00 3.59 0.00

TST_D 1.14±0.06 1.00±0.06 0.55 0.52 0.52 5.07 0.00 3.32 0.00

TC 105.62±5.61 119.78±7.19 -0.58 -0.54 -0.54 -5.19 0.00 -3.44 0.00

BLL 232.22±26.58 195.83±29.24 0.84 0.80 0.81 3.03 0.01 1.47 0.16

BLR 233.78±21.95 209.23±13.67 0.91 0.89 0.84 2.97 0.01 1.84 0.08

BAP 145.65±14.83 126.91±9.19 0.88 0.83 0.80 3.36 0.00 2.33 0.03

BLS -2.49±2.92 0.01±2.46 -0.16 -0.18 -0.13 -2.10 0.05 -1.81 0.09

FMF1L 749.17±168.57 579.08±173.32 0.90 0.87 0.82 2.30 0.03 0.60 0.56

FMF1R 759.06±169.64 576.98±161.03 0.92 0.90 0.86 2.53 0.02 0.94 0.36

FMF2L 787.57±187.20 586.30±199.81 0.89 0.84 0.85 2.41 0.03 0.62 0.54

FMF2R 787.45±182.08 600.76±177.53 0.91 0.88 0.87 2.39 0.03 0.56 0.58

LTP_D 3.68±3.84 -0.16±4.32 0.01 -0.02 -0.03 2.19 0.04 2.26 0.04

MFL 768.88±181.97 587.88±173.34 0.91 0.86 0.86 2.34 0.03 0.50 0.62

MFR 773.98±175.11 594.26±174.79 0.92 0.89 0.87 2.37 0.03 0.51 0.62

MAXPMR 14.54±6.96 9.36±1.97 0.35 0.41 0.34 2.16 0.04 1.48 0.16

TMAXM 5.41±6.62 -1.69±3.50 0.20 0.20 0.22 2.93 0.01 2.33 0.03

CF -0.50±0.87 1.02±1.98 -0.53 -0.44 -0.44 -2.47 0.02 -1.53 0.14

CML 69.68±4.82 62.99±7.70 0.60 0.64 0.61 2.52 0.02 1.26 0.22

CH 4.76±5.92 -0.31±3.68 0.00 -0.02 -0.03 2.28 0.03 2.33 0.03

Pedobarographic Features of Gait Measured by FDM1.5 PMD

Figure 2: Barefoot gait (left graphs)/footware gait (right graphs) (Zebris); axes – x for % of measured time, y for Force (N),

and 4 lines (developing from left to right – total, heel, midfoot, forefoot).

it is possible to improve power of arguments.

Partializations imply extracting the common

variance, and comparison between rests of true

variances (explained in Milas, 2009). It goes in line

with 3

fundamental step that have to be followed

towards standardisation in the use of PMDs

(Giacomozzi et al, 2012), i.e. definition and

standardisation of data processing and reporting (1

is definition and standardisation of tools and

protocols for the technical assessment of PMD

hardware performance, and 2

is definition and

standardisation of pressure acquisition protocols)

Pedobarographic features are expectedly

different in male and female population due to well

analysed differences in valgus knee inclinations.

Tested differences between genders (table 5.), before

and after partialization of results (by excluding

influence of longitudinal dimensionality of subjects),

in both cases reveal significance in variables: Stride

width (t_GSW=4.15), Step time L (t_TSTL=2.88),

Step time R (t_TSTR=3.59), bilateral asymmetry in

Step time (t_TST_D=3.32), Cadence (t_TC=-3.44)

on P<0.01 level, and Ant/Post position

(t_BAP=2.33), bilateral asymmetry in Time to

change heel to forefoot, % L (t_LTP_D=2.26), Time

maximum force Midfoot D % of stance time

(t_TMAXM=2.33), and bilateral asymmetry in

Contact time Heel (t_CH_D=2.33), on p<0.05 level.

Differences in barefoot/footwear gait (table 4.)

were specially expressed in variable MAXPH (t= -

8.83782, p<0.05). It can be (limited) assumption,

that wearing shoes influences neuromuscular and

motor control(learning) decision mechanisms in a

way that individual 'delegates' amortisation

mechanisms in first contact (heel strike/load

response) to the shoe and elastic structures of its

composite materials (figure 2.). Initial greater force

(during contact with shoe) spreads, and transposes

impact on upper skin. Normal feet with „smaller

joint mobility are associated with larger pressure at

the rear- and forefoot. A trend for decreased pressure

at the midfoot was also detected in feet with a stiffer

medial longitudinal arch. A more flexible foot may

allow better distribution of pressure at the plantar

foot surface during gait thus limiting the

contribution to plantar tissue damage especially in

at-risk groups such as the diabetic feet.“ (Caravaggi

et al, 2014).

ACKNOWLEDGEMENTS

Research was conducted by Research Group of

Biomechanics Laboratory, Institute of Kinesiology,

Faculty of Kinesiology, as closure of UniZg project

“Pedobarographic features of human locomotion in

sports and medicine” intended to support future

developments in gait analysis.

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Pedobarographic Features of Gait Measured by FDM1.5 PMD