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Journal of Biomechanics 43 (2010) 19972001Contents lists available at ScienceDirectjournal homepage: www.elsevier.com/locate/jbiomech

Journal of Biomechanics0021-92

doi:10.1

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E-mwww.JBiomech.comThe variability and complexity of sitting postural control are associatedwith discomfortKaren H.E. Sndergaard a, Christian G. Olesen a,b, Eva K. Sndergaard a, Mark de Zee a,Pascal Madeleine a,n

a Center for SensoryMotor Interaction (SMI), Department of Health Science and Technology, Fredrik Bajers vej 7, 9220 Aalborg East, Denmarkb Department of Mechanical and Manufacturing Engineering, Aalborg University, Denmarka r t i c l e i n f o

Article history:Accepted 3 March 2010The present investigation examined the variability of sitting postural movement in relation to the

development of perceived discomfort by means of linear and nonlinear analysis. Nine male subjectsKeywords:

Complexity

Sitting posture

Postural control

Discomfort

Variability90/$ - see front matter & 2010 Elsevier Ltd. A

016/j.jbiomech.2010.03.009

esponding author. Tel.: +45 99408833; fax:

ail address: pm@hst.aau.dk (P. Madeleine).a b s t r a c t

participated in this study. Discomfort ratings, kinetic and kinematics data were recorded during

prolonged sitting. Body part discomfort index, displacement of the center of pressure (COP) in anterior

posterior and mediallateral directions as well as lumbar curvature were calculated. Mean, standard

deviation and sample entropy values were extracted from COP and lumbar curvature signals. Standard

deviation and sample entropy were used to assess the degree of variability and complexity of sitting.

A correlation analysis was performed to determine the correlation of each parameter with discomfort.

There were no correlations between discomfort and any of the mean values. On the contrary, the

standard deviations of the COP displacement in both directions and lumbar curvature were positively

correlated to discomfort, whereas sample entropies were negatively correlated. The present study

suggests that the increase in degree of variability and the decrease in complexity of sitting postural

control are interrelated with the increase in perceived discomfort. Finally, the present study underlined

the importance of quantifying motor variability for understanding the biomechanics of seated posture.

& 2010 Elsevier Ltd. All rights reserved.1. Introduction

Musculoskeletal discomfort is expressing manifestations likeperceived tension, muscle fatigue or soreness, numbness andfeeling of pain (de Looze et al., 2003). Discomfort from the lumbarregion is reported to be the main cause for an increase in generaldiscomfort in the seated position (Vergara and Page, 2002).Moreover, discomfort may reflect an early perception of painrelated to the biomechanical load applied to the musculoskeletalsystem (Madeleine et al., 1998). However, the underlyingmechanisms of back pain are not clearly understood (Battieet al., 2009; Videman et al., 2003). A number of studies havesuggested that prolonged sitting could be a risk factor for thedevelopment of low-back pain (Corlett, 2006; Pope et al., 2002).Thus, the study of discomfort in relation to prolonged sitting mayreveal important aspects of the transition between discomfortand pain.

Interestingly, discomfort is considered to be related withsitting postural changes (Fenety and Walker, 2002; Vergara andPage, 2002; Liao and Drury, 2000). Liao and Drury (2000) havell rights reserved.

+45 98154008.reported a positive relationship between discomfort and thefrequency of postural changes during computer work. This hasbeen further substantiated by an increase in the frequency ofpostural shifts over time also reported during computer work(Fenety and Walker, 2002). Vergara and Page (2002) proposedthat postures sustained for a long period may be harmful andunderlined the necessity of varying posture. Previous studies havemainly focused on specific postures and postural changes, and assuch, did not take into account the fact that seating is a dynamictask (Dempster, 1955; Branton and Grayson, 1967). This calls forfurther studies aiming at quantifying the variability of posturalcontrol strategies in seated posture.

Standard deviation and/or coefficient of variation are the mostcommon linear descriptors used to characterize the amount ofmotor variability (Stergiou, 2004). Such analysis is oftencomplemented with nonlinear analysis, as it provides measuresof the pattern of postural movement. These analysis techniquesenable the quantification of subtle changes in the dynamics ofbiological systems (Lipsitz and Goldberger, 1992). In the biome-chanics of sitting, nonlinear analysis so far has been mostlyapplied to delineate the dynamics of sitting in relation todevelopment and disorders in infants (Deffeyes et al., 2009;Harbourne and Stergiou, 2003; Harbourne et al., 2004). Changesin the pattern of sitting postural control can be assessed by

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K.H.E. Sndergaard et al. / Journal of Biomechanics 43 (2010) 199720011998e.g. entropy measures derived from information theory. Entropy isthe natural logarithm of a conditional probability, interpreted asthe rate of information generation and provides an estimate of thecomplexity of the underlying system producing the dynamics inquestion (Lipsitz and Goldberger, 1992; Richman and Moorman,2000). Surprisingly, sitting postural control has only sparsely beeninvestigated in adults, despite the aforementioned importance ofunderstanding seated postures. The relationship between seatedcenter of pressure (COP) dynamics and driver macro movementshas been investigated by simultaneously assessing driver macromovements and complexity of the COP displacements during longterm driving (Hermann, 2005). However, no studies have, to ourknowledge, measured the development of sitting discomfort andrelated this to the dynamics of sitting postural control.

In the present study, we investigated the development ofdiscomfort during prolonged sitting and the basic relationshipsbetween perceived seated discomfort and sitting postural move-ment in terms of variations in COP and lumbar curvature. Thevariability of these seated postural variables was evaluated bymeans of linear and nonlinear analysis techniques in relation toperceived discomfort during prolonged sitting.Fig. 1. Experimental setup: Subject was seated on a force platform with nosupport for the back, feet or arms. The arrows in the coordinate system indicate

the positive axes for the x, y and z force components. Reflective markers

were placed at the spinous processes of L1 and S2. A third marker was placed at

the farthest perpendicular distance to a line between L1 and S2 markers. a denotesthe angle of lumbar curvature. A fourth marker was placed at the sternum as a

reference point to discern lordotic and kyphotic lumbar curvatures. Negative

values denoted kyphotic curvatures and positive lordotic curvatures.2. Methods and materials

2.1. Subjects

Nine male volunteers participated in the study (mean7SD age 25.271.6years, height 186.975.8 cm, body mass 81.676.5 kg and BMI 23.371.1). None ofthe subjects had any known spinal deformities or history of back pain. All subjects

gave written, informed consent to participate in this study. The study was

approved by the local ethics committee (N-20070004) and conducted in

conformity with the Declaration of Helsinki.

2.2. Experimental procedure

The method for assessing lumbar curvature was modified from the tangential

radiologic assessment of lumbar lordosis technique (Chernukha et al., 1998) to

allow for non-invasive assessment of lumbar curvature (see Fig. 1 for a schematic

illustration of the modified method). The spinous processes of the L1 and S2

vertebrae were palpated during relaxed standing, and each marked with a

reflective marker. The point on the lumbar spine with the furthest perpendicular

distance to an imaginary line between L1 and S2, corresponding to point C in Fig. 1,

was found by sliding a ruler along the lumbar spine between L1 and S2, and

marked with a reflective marker. A fourth marker was placed on the sternum as a

reference for discerning kyphotic and lordotic lumbar curvature. Lumbar curvature

was measured to assess the local postural movement in the lumbar region.

Once the markers are attached, the subjects were seated on a force platform

(AMTI OR6-7 1000, Watertown, MA, USA) with no back-, foot support or armrest

and without cushioning. As such, the only contact surface was the force platform.

The subjects were allowed to move their upper bodies in response to discomfort,

but were given restrictions with respect to movement of arms and feet, i.e. they

were instructed to leave their hands at rest on their thighs, and not to move their

legs and feet during the recording sessions. The edge of the force platform was

padded with foam to avoid discomfort at the popliteal area from resting the thighs.

The subjects watched a movie during the recording session to minimize the

influence of the Hawthorne effect due to subject awareness. Pilot studies revealed

90 min of sitting to be sufficient to provoke a moderate level of discomfort. Each

recording session consisted of 18 intervals of 5 min data recording with a break of

20 s between each interval, resulting in a total of 96 min for each session. The

breaks were inserted for discomfort assessment and to allow the subjects to move

their lower legs and feet to ensure blood circulation in the legs.

2.3. Data recordings and analysis

Every 5 min, body part discomfort (BPD) ratings were collected during the 20 s

break using a 6 level scale from 0 to 5. Zero representing no discomfort and 5

worst imaginable discomfort (Corlett and Bishop, 1976). Reaction forces were

sampled at 100 Hz after amplification (gain of 4000) and analogue low pass

filtering (Fcut-off: 10.5 Hz). Similarly, kinematics data were sampled at 100 Hz using

eight Qualisys Pro-Reflex 240 cameras (Qualisys, Gothenburg, Sweden).

BPD scores for each subject were summed for each time-interval, providing a

BPD index (Helander and Zhang, 1997). COP displacement over time wascomputed in the anteriorposterior (AP) and mediallateral (ML) directions

(Winter, 1990) in Matlab (Mathworks, Natick, MA). Kinematics data were

processed using Qualisys track manager software, exported to Matlab and

transformed to lumbar curvature angle. Negative values denoted kyphotic

curvatures and positive lordotic curvatures. The mean, standard deviation (SD)

and sample entropy (SaEn) of the COP displacement in AP and ML directions and

of the lumbar curvature were computed. SD and SaEn were used to characterize

respectively the amount of motor variability and the complexity of the sitting

postural control. SaEn quantifies regularity in a data series by assessing

the probability that sequences of length m that are similar will remain similar

when incrementing the length of the sequences tom+1. The similarity condition is

determined by the tolerance, r. Output is a unit-less, non-negative number, where

higher values indicate more complex data series. For more details, see Richman

and Moorman (2000). The embedding dimension, m, was chosen as 2, and the

tolerance, r, was chosen to 0.1 SD of the time series (Pincus, 1991).2.4. Statistical analysis

Pearson correlation coefficients were calculated using SPSS version 16.0

(Chicago, IL, USA) to assess the relationship between perceived discomfort and

dynamics of sitting postural control, using BPD sum as the dependent variable and

mean/SD/SaEn of COP displacement in AP and ML directions and of lumbar

curvature as predictor variables. po0.05 Was considered as significant.3. Results

Figs. 2 and 3 illustrate changes in BPD and in mean/SD/SaEn ofCOP displacement in AP and ML directions and of lumbarcurvature over time. BPD increased significantly over time (Fig. 2).The mean COP displacement in AP direction (Fig. 3a) and meanlumbar curvature (Fig. 3c) increased significantly over time,revealing a shift towards more lordotic curvatures. Meanwhile,mean COP displacement in ML direction did not show anysignificant changes over time (Fig. 3b). The SD of the COPdisplacement in both AP and ML directions (Fig. 3d and e)and of lumbar curvature (Fig. 3f) significantly increased over time,while SaEn significantly decreased over time (Fig. 3gi).

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Upp

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Fig. 2. Mean+SD of the sum of body part discomfort, neck, shoulders, upper back,lower back, buttocks, thighs, popliteal region and legs over 90 min seating.

K.H.E. Sndergaard et al. / Journal of Biomechanics 43 (2010) 19972001 1999Table 1 lists the results of the statistical analysis. There werestatistically significant correlations between BPD and all predictorvariables, except mean COP displacement in AP and MLdirections and lumbar curvature. The SDs of the COPdisplacement and lumbar curvature were positively correlatedwith BPD, while SaEn were negatively correlated.4. Discussion

In the present study, we investigated the correlations betweenperceived discomfort and sitting postural control duringprolonged sitting by means of linear and non-linear analysis ofcenter of pressure displacement and variations in lumbarcurvature.

4.1. Methodological considerations

In previous studies on seated discomfort, experimental setupshave typically been directed towards specific applications, e.g.discomfort during driving (Hermann, 2005), chair design/assess-ment (Vergara and Page, 2002; Kingma and van Dieen, 2009) orwork tasks (Starr et al., 1985; Fenety and Walker, 2002; Ziefle,2003). The main drawback of such approach is the difficulty todiscern between factors (e.g. work task, sitting task) interactingwith the perception of discomfort. Furthermore, the presence orabsence of backrest or armrests complicates comparison betweenstudies. In the present study, we omitted backrest, armrests andcushion. The sitting constraints (no arms/legs movement) duringthe recording sessions may explain the lack of changes in thedisplacement of the COP in the ML direction over time. The frontedge of the force platform was padded to minimize discomfort inthe popliteal area. This resulted in perceived discomfort mainlyoriginating from the buttocks and the low back regions. Theexperimental setup did not reflect realistic seating, but it enabledto assess changes over time in sitting postural dynamics inrelation to perceived seated discomfort. Thus, the present studycould be used as a baseline for future studies investigating morerealistic setup, including for instance armrests, footrests or seats.

4.2. Postural variability measures as indicators of seated discomfort

The present study depicted correlations between perceivedseated discomfort and mean, amount of variability and complex-ity of the COP trajectories as well as lumbar curvature. Thepredominance of discomfort reported from the low back andthe buttocks confirmed that the variables under investigation canbe considered as indicators of seated discomfort. Regarding meanposture, we computed the mean curvatures of the 18 intervalsconstituting the recording session. This procedure was repeatedfor the displacement of the COP in AP and ML directions tofurther explore relationships between seated discomfort andsitting postural changes. There were no correlations betweendiscomfort and mean values of postural movement and meanlumbar curvature, suggesting that mean sitting posture variablesdo not seem to provide an objective way to assess thedevelopment of seated discomfort at a group level in the presentexperimental setup.

On the other hand, the present analysis confirmed theimportance of variability in relation to sitting posture anddiscomfort (Vergara and Page, 2002). The amount of variabilityfor both lumbar curvature and COP displacement increased overtime as well as the discomfort, indicating a relationship. Grossmediallateral displacements of the COP can be interpreted as ameans of pressure relief of the gluteal region, as the peak pressureis lifted from either side. The increase in SD with increaseddiscomfort probably indicates a progressively larger need forgreater or more effective pressure relief of the soft tissue underthe buttocks and suggests an association between prolongedtissue pressure under the buttocks and seated discomfort. Giventhe lumbar-pelvic anatomy, with the shape of the spine closelyintertwining with the tilt of the pelvis, the COP displacements inAP direction are closely related to the variations in lumbarcurvature. This is substantiated by the positive correlationbetween standard deviation of the lumbar curvature and standarddeviation of COP displacement in AP direction. Gross displace-ments of the lumbar curvature are likewise interpreted as a

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Fig. 3. Mean+SD of the mean (top row), standard deviation (middle row) and sample entropy (bottom row) of the center of pressure (CoP) displacement (m) in theanteriorposterior (AP, left column) and mediallateral (ML, middle column) and lumbar curvature (deg., right column) over 90 min seating. Negative values denoted

kyphotic curvatures and positive lordotic curvatures.

Table 1Pearson correlation coefficients between sum of body part discomfort (BPD) and mean, standard deviation (SD) and sample entropy (SaEn) of the center of pressure

displacement in anteriorposterior and mediallateral directions (COPAP and COPML) as well as lumbar curvature (LC).

BPD Mean COPAP Mean COPML Mean LC SD COPAP SD COPML SD LC SaEn COPAP SaEn COPML SaEn LC

BPD 1

Mean COPAP 0.125 1 Mean COPML 0.029 0.541

nn 1

Mean LC 0.002 0.065 0.091 1 SD COPAP 0.273

nn 0.158n 0.003 0.171n 1 SD COPML 0.329

nn 0.052 0.313nn 0.361n 0.163n 1 SD LC 0.140n 0.139n 0.139n 0.480nn 0.675nn 0.357nn 1 SaEn COPAP 0.271nn 0.235nn 0.070 0.128 0.097 0.134n 0.033 1 SaEn COPML 0.278

nn 0.120 0.091 0.200nn 0.151n 0.696nn 0.162n 0.098 1 SaEn LC 0.193nn 0.252nn 0.113 0.392nn 0.565nn 0.368nn 0.823nn 0.116 0.166n 1

n po0.05.nn po0.01.

K.H.E. Sndergaard et al. / Journal of Biomechanics 43 (2010) 199720012000means of pressure relief, as changes in lumbar curvature rotatethe pelvis, and thus shift the location of the ischial tuberositiesunder the buttocks. Moreover, it may provide muscle- andligament tension relief of the lumbar, sacral and gluteal bodyregions.

In parallel to the observed changes in the amount ofvariability, sample entropy as a measure of complexity decreasedover time for COP postural movement in AP and ML directionand lumbar curvature, along with significant negative correlationsof sample entropy to discomfort. The changes in sample entropyvalues suggest that the intrinsic dynamics of seated posturalcontrol are similar to those of standing postural control andgenerally perceived as fluctuating around an equilibrium point(Collins and DeLuca, 1993). Finally, the present study showed that

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K.H.E. Sndergaard et al. / Journal of Biomechanics 43 (2010) 19972001 2001the complexity of sitting postural control is affected by increasingdiscomfort due to prolonged sitting.

In conclusion, the present study revealed for the first time thatthe degree of variability of COP displacements and lumbarcurvature increased, while its complexity decreased in relationto increased perceived discomfort. Quantitative measurement ofspinal posture behavior over an extended period of timecontributed to a better understanding of the biomechanics ofseating. As discomfort increased, sitting movement patternsbecame larger and more regular. Further studies investigatingsitting postural in working conditions are warranted.Conflict of interest statement

All authors hereby declare that there are no conflicts of interest.Acknowledgements

The authors are grateful to Rene Lindstrm (Center forSensory-Motor Interaction (SMI), Aalborg University) for identify-ing anatomical landmarks. This study was financially supportedby the European Regional Development Fund (Project SeatingPosition and Functional Ability).

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The variability and complexity of sitting postural control are associated with discomfortIntroductionMethods and materialsSubjectsExperimental procedureData recordings and analysisStatistical analysis

ResultsDiscussionMethodological considerationsPostural variability measures as indicators of seated discomfort

Conflict of interest statementAcknowledgementsReferences