Motor Control, 2015, 19, 10-24 http://dx.doi.org/10.1123/mc.2013-0091 © 2015 Human Kinetics, Inc.
Unsupported Eyes Closed Sitting and Quiet Standing Share Postural Control Strategies in Healthy Individuals Murielle Grangeon, Cindy Gauthier, Cyril Duclos, JeanFrancois Lemay, and Dany Gagnon The study aimed to (1) compare postural stability between sitting and standing in healthy individuals and (2) define center-of-pressure (COP) measures during sitting that could also explain standing stability. Fourteen healthy individuals randomly maintained (1) two short-sitting positions with eyes open or closed, with or without hand support, and (2) one standing position with eyes open with both upper limbs resting alongside the body. Thirty-six COP measures based on time and frequency series were computed. Greater COP displacement and velocity along with lower frequency measures were found for almost all directional components during standing compared with both sitting positions. The velocity, 95% confidence ellipse area, and centroidal frequency were found to be correlated between unsupported sitting and standing. Despite evidenced differences between sitting and standing, similarities in postural control were highlighted when sitting stability was the most challenging. These findings support further investigation between dynamic sitting and standing balance. Keywords: postural control, sitting, standing, stability, center of pressure, centroidal frequency, rehabilitation
Postural control can be defined as the postural strategies used to maintain the vertical projection of the center of mass (COM) of the body within the base of support (BOS) to prevent falls (Winter, 2005). Recent evidence using mostly clinical impairment scales suggests that postural control during sitting upon admission to intensive functional rehabilitation may accurately predict the ambulatory capacity (i.e., standing, stepping, and walking) upon discharge among individuals with neurological impairments (Nayak et al., 2011; Schoch, Hogan, Gizewski, Timmann, & Konczak, 2010; Veerbeek, Van Wegen, Harmeling-Van der Wel, & Kwakkel, 2011; Verheyden et al., 2006). However, limited evidence using a biomechanical approach is available to support this relationship between postural control during quiet sitting and standing (Genthon & Rougier, 2007; Vette, Masani, Sin, & Popovic, The authors are with the School of Rehabilitation, Université de Montreal, Montreal, Canada, and the Pathokinesiology Laboratory, Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal—Institut de réadaptation Gingras-Lindsay-de-Montréal, Montreal, Canada. Address author correspondence to Murielle Grangeon at [email protected]. 10
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Quiet Sitting Compared With Standing 11
2010). Standing and sitting postural control share many features (e.g., fight against gravity) but freedom of movements, inertial properties, and motor control differ. Damage to the neurological system may thus affect sitting and standing postural control differently. Comparing the underlying control mechanisms during quiet sitting and standing may thus provide a benchmark for future postural stability investigations, especially in the context of balance rehabilitation programs for the development of novel assessment tools and exercise. The location of the center of pressure (COP), defined as the origin of the ground reaction force vector on the surface of a force plate on which the subject is positioned, provides consistent information on postural control (Winter, 1995). Indeed, with coordinated neuromuscular response, the COP is positioned in such a way that it continuously regulates the COM within the BOS to prevent instability (Caron, Faure, & Breniere, 1997). The quantification of the COP displacement over time using various time and frequency measures is a commonly applied and wellaccepted technique to measure quasi-static postural stability and to characterize the control mechanisms used to stabilize the body during quiet standing (Baratto, Morasso, Re, & Spada, 2002; Mancini et al., 2012; Maurer & Peterka, 2005; Prieto, Myklebust, Hoffmann, Lovett, & Myklebust, 1996) or sitting (Boswell-Ruys et al., 2009; Grangeon et al., 2013). Indeed, during quasi-static conditions, the COP displacement results from spontaneous body sway needed to control posture and balance when no external disturbances are applied (Rocchi, Chiari, & Horak, 2002; Seelen, Potten, Huson, Spaans, & Reulen, 1997). However few studies have investigated the relationship of COP measures between quiet standing and sitting. Vette et al. (2010) figure among the first to have investigated the relationship of COP measures between quiet standing and sitting. Among five COP measures calculated for 12 healthy individuals, Vette et al. (2010) showed that only mean velocity correlated fairly well (ρ = .70) between both positions. However, the participant’s feet did not touch the floor in the sitting position; therefore, the ground reaction forces under the feet did not account for the displacement of the COP. Secondly, only within-task comparisons were performed for the eye condition (i.e., eyes open or closed). Vette et al. did not compare sitting with eyes closed to standing with eyes open. It is possible that the authors would have found more relationships between the most challenging sitting position for postural control (i.e., sitting with arms crossed over the chest and eyes closed) and standing with eyes open than they did. Finally, investigating a larger set of COP measures is needed to further validate the five COP measures selected by Vette et al. (2010), and potentially adding a few additional relevant measures will allow for a straightforward interpretation of the relationship between standing and sitting positions. Therefore, the main objectives of the current study were to compare two sitting positions (with and without upper limb [U/L] support) with eyes open or closed to a standing position with eyes open among healthy individuals, and verify whether healthy individuals ranked similarly in terms of postural stability for both the standing and sitting position. The secondary objective was to identify COP measures in a sitting position that could also explain stability achieved while standing, which could be further investigated as predictive recovery measures for standing stability. The COP measures were expected to determine potential biomechanical and motor control differences between standing and sitting. Nevertheless, the COP measures computed in the most challenging sitting position (i.e., unsupported sitting with eyes
12 Grangeon et al.
closed) were hypothesized to be more associated with the standing position than with the other sitting positions, particularly mean velocity and centroidal frequency.
Methods
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Participants Fourteen healthy male individuals volunteered to participate in this study after signing the informed consent (Table 1). None of them reported having musculoskeletal or neurological impairments. Ethical approval was obtained from the Research Ethics Committee of the Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR-456–0809).
Experimental Tasks During the sitting trials, participants sat on a height-adjustable instrumented seat with their back unsupported and each foot resting on a separate force plate embedded in the floor. Their thighs and feet were parallel to each other. Approximately 75% of their thigh length was in contact with the seat, with their knees flexed at approximately 85°. Participants maintained a quiet sitting position with eyes open or closed, with both hands resting on their thighs (supported sitting) or with both shoulders flexed at 90° and horizontally abducted at 45° (unsupported sitting). These two different U/L positions aimed to isolate the compensatory role of the U/Ls when maintaining quiet sitting. Unsupported sitting is commonly used for functional U/L tasks. The unsupported sitting position has also been found to be the most difficult task among sitting positions in healthy individuals and neurological populations (Grangeon et al., 2012). During the standing trials, participants maintained a quiet stance with each foot resting on a separate force plate embedded in the floor, with their U/Ls hanging along both sides of their body. Their feet were placed at 30° with their heels separated by 9 cm. A total of two 60-s trials in each position were randomly performed.
Instrumentation and Data Processing Ground reaction forces were recorded (600 Hz) underneath the buttocks (sitting position only) and each foot (sitting and standing position) using the various force plates. The combined triaxial components (i.e., anteroposterior [AP; Fx], vertical [Fy], and mediolateral [ML; Fz]) of the reaction forces and moments at each force plate with their own referential were then combined to compute the global COP time series within the global laboratory referential. Data were then filtered with a fourthorder Butterworth zero-lag low-pass digital filter with a cutoff frequency of 5 Hz.
COP-Related Outcome Measures A total of 17 COP measures were computed based on the methodology of Prieto et al. (1996; Table 2). Eleven of the 17 COP measures were composed of AP and ML components from which the resultant (RD) component was calculated at each data point, whereas the remaining 6 COP measures were extracted from the RD time series in the horizontal plane only (e.g., the area covered by the COP).
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Age (Years) 23 67 60 53 33 38 50 35 37 30 43 33 24 54 41.43 13.46
Height (m) 1.74 1.74 1.66 1.7 1.74 1.81 1.67 1.78 1.78 1.79 1.65 1.89 1.73 1.68 1.74 0.07
Weight (kg) 76.9 70.2 80.9 73.7 78.6 83.6 65.8 86.3 87.5 94 78.6 74.3 91.1 80 80.11 7.90
BOS (Sitting) 0.31 0.31 0.26 0.31 0.30 0.33 0.28 0.37 0.39 0.38 0.33 0.35 0.28 0.32 0.32 0.04
(m2)
BOS (Standing) 0.15 0.11 0.09 0.10 0.10 0.13 0.11 0.14 0.15 0.16 0.12 0.11 0.09 0.12 0.12 0.02
(m2) Head 33 25 29.4 24 24 23 22.5 22.6 22.2 34 21.2 34 22.4 22 25.66 4.77
Segments Length (cm) Lower Trunk Thigh leg 56.4 39.5 39.8 52 43.7 44.4 54.2 36.2 39.3 56.2 37 42.2 54.2 42.2 40.5 55.9 43 42.8 55.6 36.5 41 53.5 27.2 43.6 51.2 44.6 42.3 54 40 43.5 46.2 40.5 40.6 57 60 49 56 43.8 39.8 51 40.2 40.3 53.81 41.03 42.08 2.93 7.06 2.56
Foot 26 25.5 24.8 25.5 25.5 27.4 25.7 40.1 26 24.5 25.9 28 27.3 28 27.16 3.89
Note. BOS = base of support. The contour of the BOS is continuously defined during the standing and sitting position by a convex area enclosing the contour of buttock and/or the feet segments (peripheral points) projected into the horizontal plane of the COP using an algorithm. The head segment was measured from chin to vertex, the trunk from trochanter to acromion, the thigh from trochanter to center of knee, the lower leg from the center of knee to center of malleolus, and the foot from the heel to the tip of the longest toe.
Participant 1 2 3 4 5 6 7 8 9 10 11 12 13 14 M SD
Table 1 Description of Participants
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14 Grangeon et al.
In the current study, postural stability was represented by three commonly reported dimensions: stability performance, control demand, and postural regulations (Grangeon et al., 2013). Stability performance and control demand (i.e., indicator of attentional resources required to maintain stability) were characterized by COP distance and velocity measures, respectively (Genthon, Vuillerme, Monnet, Petit, & Rougier, 2007; Hufschmidt, Dichgans, Mauritz, & Hufschmidt, 1980). A reduction in stability performance and an increase in control demand have often been associated with an increased risk of falling and reduced postural stability. Postural regulations are described by frequency measures, which could provide information on postural disturbances due to specific impairments or conditions (Demura, Kitabayashi, & Noda, 2008; Karlsson, Norrlin, Silander, Dahl, & Lanshammar, 2000). Despite a lack of consensus with regard to this interpretation, an increasing number of studies have revealed the capability of frequency measures to characterize postural control. More precisely, the FREQ-50% has been found to be sensitive to the contribution of various sensory information (i.e., integration of visual, vestibular, or somatosensory inputs; Bizid et al., 2009) and to change when a shift in preferential postural regulation occurs. The CFREQ, expressing the inertia of an inverted pendulum and the time for the COP to return to its initial position, is sensitive to the biomechanical properties of the studied system (Mancini et al., 2012; Vette et al., 2010). Finally, the FREQD, by describing the variability of the frequency content, may reveal the active–passive stiffness or rigidity of the system (Grangeon et al., 2013; Maurer & Peterka, 2005). Table 2 Summary of the COP-Related Outcome Measures Types of Measure Time-domain distance measures
Time-domain area measures Time-domain hybrid measures
Outcome Measure MDIST (mm)a RDIST (mm)a TOTEX (mm)a RANGE (mm)a MVELO (mm/s)a AREA-CC (mm2) AREA-CE (mm2) AREA-SW (mm2/s) MFREQ (Hz)a FD-RD FD-CC FD-CE
Frequency domain measures
a
T POWERa 50% (Hz)a 95% (Hz)a CFREQ (Hz)a FREQDa
Description average distance from the mean COP RMS distance total length of the COP path Maximum distance between any two points Average velocity of the COP 95% confidence circle area 95% confidence ellipse area sway area mean frequency fractal dimension fractal dimension based on the area-CC fractal dimension based on the area-CE total power frequency median power frequency 95% power frequency centroidal frequency frequency dispersion
Computed based on resultant (RD) time series as well as on the anteroposterior and mediolateral time series.
Quiet Sitting Compared With Standing 15
Statistical Analysis
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Once the normality of data were verified with the Shapiro–Wilk test, repeatedmeasures analyses of variance were computed for each COP measure using a significance level of .05. Bonferroni pairwise comparisons with an adjusted significance level (p = .05/4) were performed in case of significant results. Spearman rho correlation coefficients (ρ) were also computed to reveal potential relationships between the sitting and standing positions. Correlation coefficients were considered very strong above .90, strong between .70 and .89, and moderate between .50 and .69 (Demholdt, 2000). All statistical analyses were performed using SPSS version 20.0 software.
Results An example of a COP path during the three positions with eyes open is illustrated in Figure 1. All COP measures and statistical results are summarized in Table 3. Greater displacement, velocity, area, and lower frequency measures were confirmed for almost all the directional components in the standing position compared with both sitting positions. TPOWER for all directional components and the ML component of MVELO and TOTEX were similar for the three positions, irrespective of the vision condition. Significant differences were found for the AP and/or ML directional component of FREQD, despite similarity for the RD component between the standing position and both sitting positions, irrespective of the vision condition. Lastly, using Spearman’s rho correlation coefficients (Figure 2), only a few measures for the ML component were found to be correlated between standing with eyes open and unsupported sitting with eyes closed. RANGE-ML (ρ = .56, p = .04), MVELO-ML, and TOTEX-ML (ρ = .62, p = .01) were moderately correlated between these two positions, while CFREQ-ML (ρ = .73, p = .003) was strongly correlated. Other COP measures were weakly correlated or uncorrelated between standing and sitting (ρ = .09–.49), irrespective of the vision condition.
Discussion As expected, the differences in stability achieved while standing and sitting suggest that the mechanical demand governing balance in these positions is different as evidenced by the increased COP displacements, velocity, and lower frequency measures observed during standing compared with both sitting positions, particularly on the AP directional component. The present findings are thus in agreement with the previous related study of Vette et al. (2010) that revealed greater and faster body sway in standing, defined by a lower centroidal frequency and a reduced variability in frequency content (i.e., FREQD), compared with sitting position. Quiet standing is assumed to be more challenging than sitting. The inverted pendulum theory states that the stability of the rigid body is inversely related to the height of the COM above the BOS. Because the COM is farther from the BOS in a standing position than in a sitting position, postural sway increases to maintain the COM close to the initial position (i.e., larger COP amplitude, greater COP velocity, and lower COP frequency). Moreover, the BOS is larger when sitting than when standing (Kantor, Poupard, Le Bozec, & Bouisset, 2001), suggesting less postural demand to maintain stability.
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2,95 ± 1,10
20,57 ± 14,87
2,03 ± 0,97
17,41 ± 28,07
3,12 ± 1,21
6,08 ± 1,16
255,58 ± 174,38 16,03 ± 11,21 134,49 ± 64,85 2,23 ± 1,52 8,09 ± 3,78
3,95 ± 0,95
Task 2 Task 3 1,27 ± 0,45 4,23 ± 1,4 1 ± 0,39 3,71 ± 1,43 0,58 ± 0,24 1,36 ± 0,55 1,45 ± 0,51 4,95 ± 1,60 1,22 ± 0,47 4,57 ± 1,61 0,72 ± 0,30 1,70 ± 0,72 164,1 ± 45,03 224,3 ± 50,17 118,62 ± 28,39 182,36 ± 34,94 88,55 ± 32,99 93,5 ± 36,41 6,37 ± 2,06 21,83 ± 5,32 6,05 ± 1,95 21,27 ± 5,44 3,88 ± 1,38 9,02 ± 4,32 5,47 ± 1,50 7,48 ± 1,67
3,57 ± 1,64
Task 1 1,03 ± 0,80 0,86 ± 0,78 0,4 ± 0,21 1,16 ± 0,87 1,02 ± 0,85 0,51 ± 0,26 135,07 ± 62,55 106,95 ± 49,16 60,81 ± 29,04 5,28 ± 3,83 5,03 ± 3,80 3,10 ± 2,07 4,5 ± 2,08
10,86 ± 14,43 AREA-CE (mm2) AREA-SW(mm2/s) 1,55 ± 1,88
MDIST-RD (mm) MDIST-AP (mm) MDIST-ML (mm) RDIST-RD (mm) RDIST-AP (mm) RDIST-ML (mm) TOTEX-RD (mm) TOTEX-AP (mm) TOTEX-ML (mm) RANGE-RD (mm) RANGE-AP (mm) RANGE-ML (mm) MVELORD(mm/s) MVELOAP(mm/s) MVELOML(mm/s) AREA-CC (mm2)
Eyes Opened
3.00 ± 1,03
4,06 ± 1,34
8,84 ± 8,68 1,36 ± 1,23
23,85 ± 30,95 2,95 ± 3,4
15,06 ± 19,15 60,15 ± 152,69
2,12 ± 1,09
3,61 ± 1,43
*** ***
**
**
*** ***
**
**
*** ***
**
**
*** *
**
Task Comparisona T1 EO T2 EO T1 EC T2 EC Task 1 Task 2 vs. T3 EO vs. T3 EO vs. T3 EO vs. T3 EO 0,91 ± 0,38 1,59 ± 1,59 *** *** *** ** 0,74 ± 0,35 1,31 ± 1,62 *** *** *** * 0,39 ± 0,17 0,62 ± 0,22 *** *** *** ** 1,10 ± 0,57 1,78 ± 1,67 *** *** *** ** 0,96 ± 0,55 1,54 ± 1,70 *** *** *** ** 0,51 ± 0,24 0,76 ± 0,26 *** *** *** *** 137,49 ± 56,23 167,85 ± 52,17 ** * ** 108,25 ± 42,98 121,73 ± 40,29 ** ** ** ** 63,49 ± 32,67 90,08 ± 30,83 5,43 ± 3,24 7,35 ± 4,87 *** *** *** *** 5,11 ± 3,08 7,14 ± 4,87 *** *** *** *** 3,03 ± 1,92 4,16 ± 1,35 ** ** *** ** 4,58 ± 1,87 5,59 ± 1,74 ** * **
Eyes Closed
Table 3 Means ±SD of COP-Related Outcome Measures and Statistical Results
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Task 1 0,84 ± 0,31 0,95 ± 0,39 1,02 ± 0,3 1,49 ± 0,08 1,60 ± 0,09 1,64 ± 0,09 16,84 ± 5,09 49,3 ± 26,75 51,44 ± 13,4 0,83 ± 0,31 0,68 ± 0,30 0,80 ± 0,21 3,19 ± 0,39 2,75 ± 0,35 2,65 ± 0,41 1,52 ± 0,25 1,33 ± 0,27 1,35 ± 0,25 0,66 ± 0,05 0,67 ± 0,05 0,63 ± 0,04
Task 2 0,75 ± 0,21 0,80 ± 0,25 0,96 ± 0,26 1,47 ± 0,06 1,58 ± 0,07 1,60 ± 0,06 16,18 ± 4,33 43,11 ± 20,20 54,4 ± 17,24 0,67 ± 0,24 0,57 ± 0,23 0,70 ± 0,23 2,95 ± 0,37 2,71 ± 0,28 2,49 ± 0,37 1,37 ± 0,21 1,22 ± 0,19 1,25 ± 0,20 0,68 ± 0,05 0,68 ± 0,05 0,62 ± 0,05
Task 3 0,30 ± 0,08 0,33 ± 0,09 0,44 ± 0,15 1,29 ± 0,03 1,37 ± 0,05 1,42 ± 0,04 17,42 ± 4,18 39,16 ± 13,55 55,72 ± 15,02 0,35 ± 0,07 0,29 ± 0,07 0,39 ± 0,11 1,26 ± 0,26 1,03 ± 0,22 1,03 ± 0,32 0,64 ± 0,10 0,53 ± 0,08 0,58 ± 0,15 0,63 ± 0,05 0,61 ± 0,06 0,57 ± 0,05
Task 1 Task 2 0,85 ± 0,21 0,74 ± 0,18 0,95 ± 0,28 0,82 ± 0,24 1,01 ± 0,22 0,9 ± 0,18 1,48 ± 0,08 1,47 ± 0,05 1,60 ± 0,08 1,58 ± 0,07 1,64 ± 0,07 1,59 ± 0,04 19,20 ± 3,18 16,54 ± 3,64 52,26 ± 18,53 47,64 ± 19,08 55,76 ± 14,03 54,95 ± 15,47 0,82 ± 0,27 0,64 ± 0,18 0,69 ± 0,24 0,49 ± 0,18 0,79 ± 0,20 0,60 ± 0,13 3,01 ± 0,49 2,91 ± 0,18 2,63 ± 0,53 2,59 ± 0,33 2,63 ± 0,36 2,44 ± 0,28 1,48 ± 0,29 1,34 ± 0,14 1,31 ± 0,29 1,15 ± 0,15 1,29 ± 0,21 1,17 ± 0,12 0,65 ± 0,05 0,68 ± 0,04 0,65 ± 0,04 0,71 ± 0,05 0,63 ± 0,04 0,65 ± 0,04
Eyes Closed
*
*** ** *** *** *** *** *** *** ***
*
*** ** ** *** *** *** *** *** ***
*** ** *** *** *** *** *** *** ***
*** **
*** * ** *** *** *** *** *** ***
Task Comparisona T1 EO T2 EO T1 EC T2 EC vs. T3 EO vs. T3 EO vs. T3 EO vs. T3 EO *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** ***
Note. Task ¹ 1 or T1 = supported sitting position; task ¹ 2 or T2 = unsupported sitting position; task ¹ 3 or T3 = standing position. EO = eyes open; EC = eyes closed. aResults from t tests with Bonferroni adjustments when analysis of variance interaction was significant *p < .0125; **p ≤.01; ***p ≤ .001.
MFREQ-RD (Hz) MFREQ-AP (Hz) MFREQ-ML (Hz) FD-RD FD-CC FD-CE T POWER-RD T POWER–AP TPOWER-ML 50%-RD (Hz) 50%-AP (Hz) 50%-ML (Hz) 95%-RD (Hz) 95%-AP (Hz) 95%-ML (Hz) CFREQ-RD (Hz) CFREQ-AP (Hz) CFREQ-ML (Hz) FREQD-RD FREQD-AP FREQD-ML
Eyes Opened
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Figure 1 — Typical global COP path (m) observed over time during both supported and unsupported sitting with eyes opened as well as standing in one healthy individual.
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Quiet Sitting Compared With Standing 19
Figure 2 — Relationship found on the mediolateral (ML) component of MVELO and CFREQ between unsupported sitting with eyes closed (EC) and standing position with eyes opened (EO).
Using hand support or maintaining the U/Ls over the thighs and forward in combination with anterior foot support also helps to stabilize the sitting position, at least for the forward quadrants. This might reduce agonistic and antagonistic muscle cocontractions in a sitting position as reduced oscillations are observed. The increased variability in frequency content on AP or ML component observed while sitting versus standing supports this hypothesis and may reflect the reduced use of trunk muscular synergies to regulate stability (Maurer & Peterka, 2005).
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20 Grangeon et al.
Furthermore, the reduced moment of inertia of the moving body in both sitting positions compared with quiet standing increases frequency of body oscillations and explains the consistent large centroidal frequency during sitting (Winter, Patla, Prince, Ishac, & Gielo-Perczak, 1998). Therefore, in line with previous findings from other studies (Collins, De Luca, Burrows, & Lipsitz, 1995; Kang & Dingwell, 2006; Vette, Masani, Sin, & Popovic, 2010), the current study further confirms that sitting positions are more stable from a mechanical perspective and might require less neural feedback control than the standing position. Based on the two-part control behavior of Collins et al. (1995; i.e., a closed-loop control scheme implying the presence of neural feedback control over longer time intervals and an open-loop control scheme implying no neural control over short time intervals), the system during sitting might have less probability to drift away from a relative equilibrium point over short-term intervals compared with standing, suggesting fewer controlled adjustments in the longer term to bring the system back to equilibrium. However, further investigations using neural control indicators, such as the stabilogram diffusion function measures (Collins et al., 1995), are warranted to definitively confirm the neural aspect of postural control. These differences in the magnitude, velocity, and frequency of body sway between standing and sitting might also support the differences in postural strategy between these positions. Indeed, during quiet standing, the body is often assimilated to an inverted pendulum (Gage, Winter, Frank, & Adkin, 2004), described as a single body segment rotating around the ankle joints. In the AP direction, healthy individuals mainly use the ankle strategy to maintain stability in standing (Gatev, Thomas, Kepple, & Hallett, 1999) so that the upper and lower body move in the same direction, involving muscle activation (distal to proximal). When sitting with feet on the floor, the degree of freedom of the ankle and knee joints is greatly restricted so that only the upper body can be assimilated to an inverted pendulum model rotating around the hip joints (Granata & Wilson, 2001). In the AP direction in a sitting position, healthy individuals most likely use the hip strategy to maintain stability, involving muscle activation in the hip, pelvis, and trunk. Despite these differences between standing and sitting, hip, abdominal, and lower trunk muscles are essential for attaining postural control with both strategies because they provide the levels of stabilizing forces necessary for maintaining the rigidity of the trunk. Given this similarity, trunk sensorimotor impairments might alter the efficiency of both the ankle and hip strategy to maintain standing and sitting stability, respectively. In the AP directional component, the greater number of degrees of freedom used to maintain stability (i.e., muscular adjustments at the ankle, knee, and hip) provide individuals with an increased inventory of possible compensatory strategies to adjust AP stability and compensate for anticipated and nonanticipated external perturbations. However, in the ML direction, the primary response occurred at the hip both in standing and sitting conditions (Moore, Rushmer, Windus, & Nashner, 1988). The few correlations found between standing and sitting tend to reveal these similarities when sitting is the most challenging or when using one postural strategy is not enough to maintain postural control. The correlation of TOTEXML, MVELO-ML, and RANGE-ML between standing and unsupported sitting with eyes closed suggests similarities in postural control to maintain ML stability (i.e., sensorimotor information and integration; Jeka, Kiemel, Creath, Horak, & Peterka, 2004). These results differed from the study of Vette et al. (2010), who
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Quiet Sitting Compared With Standing 21
found that the MVELO was correlated between standing and sitting for the eyes open condition on all directional components. Differences in the protocol such as the computation of COP measures only from force plates underneath the buttocks, the position of the U/Ls (crossed on chest), and the smaller sample size (n = 12) in their study might explain these differences. Because correlations were also revealed on the ML component in the current study, it might be inferred that ML postural control may be a key to explaining similarities in standing and sitting stability. Furthermore, although dynamic properties using the moment inertia theory can explain differences between sitting and standing (as previously discussed), the strong correlation of CFREQ-ML between unsupported sitting with eyes closed and standing with eyes open strengthens these potential similarities in the applied control strategies. Interestingly, this measure was also found to be the most sensitive and reliable measure among the frequency COP measures in previous studies focusing on both standing and sitting stability (Grangeon et al., 2013; Mancini et al., 2012). Because CFREQ is an indirect measure of the moment of inertia, it reflects the time for the system to return to the equilibrium position. Thus, comparable ML control adjustments in unstable sitting and standing might be needed to bring the system back to the equilibrium position and to prevent falls. Studies among neurological populations have demonstrated that selective movements of the trunk help to maintain the COM within the BOS during static and dynamic postural adjustments during sitting, standing, and stepping (Davis, 1990; Edwards, 1996), particularly anticipatory postural trunk muscle activity (Dickstein, Shefi, Marcovitz, & Villa, 2004). Trunk control performance impairments were therefore found to be associated with impaired sitting and standing stability (Chern et al., 2010; van Nes, Nienhuis, Latour, & Geurts, 2008). Our conclusion that similarities in the postural control could be found between standing and the most challenging sitting position is thus supported by the correlations between MVELO and CFREQ between standing with eyes open and unsupported sitting with eyes closed. However, the small sample size (n = 14) of the current study needs to be considered since it may limit the power of these findings. Nevertheless, the present sample size does confirm a large to moderate similarity between standing and both sitting positions, since a statistical power of .77 and .49 was computed for the MVELO-ML and CFREQ-ML, respectively. Further investigations combining kinetic, kinematic, and muscular activity to compare sitting and standing are warranted to confirm the use of COP measures as an assessment tool for describing postural disorders during unsupported sitting and standing. In addition, because similar postural control seems to occur when a sitting position is the most challenging, future studies investigating the relationship between dynamic sitting and standing stability will also be relevant. If increased relationships between these positions are revealed, dynamic sitting upon admission to a rehabilitation program must also be investigated as a potential indicator of gait recovery at discharge. These results might be interesting for specificity of balance training in rehabilitation programs.
Conclusion This study aimed to highlight the relationship between standing and quiet sitting in healthy individuals. As expected, most COP measures differed during standing compared with both sitting positions and confirmed differences in mechanical and
22 Grangeon et al.
postural regulation. However, similarities existed between standing and sitting when sitting stability was reduced, suggesting similarity in postural control strategy. Additional prospective cohort studies on trunk involvement in postural control during quiet and dynamic sitting and standing among healthy and neurological populations is required to strengthen the level of current evidence.
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References Baratto, L., Morasso, P.G., Re, C., & Spada, G. (2002). A new look at posturographic analysis in the clinical context: Sway-density versus other parameterization techniques. Motor Control, 6(3), 246–270. PubMed Bizid, R., Jully, J.L., Gonzalez, G., Francois, Y., Dupui, P., & Paillard, T. (2009). Effects of fatigue induced by neuromuscular electrical stimulation on postural control. Journal of Science and Medicine in Sport, 12(1), 60–66. PubMed doi:10.1016/j.jsams.2007.10.006 Boswell-Ruys, C.L., Sturnieks, D.L., Harvey, L.A., Sherrington, C., Middleton, J.W., & Lord, S.R. (2009). Validity and reliability of assessment tools for measuring unsupported sitting in people with a spinal cord injury. Archives of Physical Medicine and Rehabilitation, 90(9), 1571–1577. PubMed doi:10.1016/j.apmr.2009.02.016 Caron, O., Faure, B., & Breniere, Y. (1997). Estimating the centre of gravity of the body on the basis of the centre of pressure in standing posture. Journal of Biomechanics, 30(11–12), 1169–1171. PubMed doi:10.1016/S0021-9290(97)00094-8 Chern, J.S., Lo, C.Y., Wu, C.Y., Chen, C.L., Yang, S., & Tang, F.T. (2010). Dynamic postural control during trunk bending and reaching in healthy adults and stroke patients. American Journal of Physical Medicine & Rehabilitation, 89(3), 186–197. PubMed doi:10.1097/ PHM.0b013e3181c56287 Collins, J.J., De Luca, C.J., Burrows, A., & Lipsitz, L.A. (1995). Age-related changes in open-loop and closed-loop postural control mechanisms. Experimental Brain Research, 104(3), 480–492. PubMed doi:10.1007/BF00231982 Davis, P. (1990). Problems associated with the loss of selective trunk activity in hemiplegia. In Right in the middle: Selective trunk activity in the treatment of adult hemiplegia (pp. 31–65). Demholdt, E. (2000). Statistical analysis of relationships: The basics. In Elseiver (Ed.), Research fundamentals (pp. 351–365). Demura, S., Kitabayashi, T., & Noda, M. (2008). Power spectrum characteristics of sway position and velocity of the center of pressure during static upright posture for healthy people. Perceptual and Motor Skills, 106(1), 307–316. PubMed doi:10.2466/pms.106.1.307-316 Dickstein, R., Shefi, S., Marcovitz, E., & Villa, Y. (2004). Anticipatory postural adjustment in selected trunk muscles in post stroke hemiparetic patients. Archives of Physical Medicine and Rehabilitation, 85(2), 261–267. PubMed doi:10.1016/j.apmr.2003.05.011 Edwards, S. (1996). An analysis of normal movement as the basis for the development of treatment techniques. In S. Edwards (Ed.), Neurological physiotherapy: A problem solving approach (pp. 5–40). Edinburgh, UK: Churchill Livingstone. Gage, W.H., Winter, D.A., Frank, J.S., & Adkin, A.L. (2004). Kinematic and kinetic validity of the inverted pendulum model in quiet standing. Gait & Posture, 19(2), 124–132. PubMed doi:10.1016/S0966-6362(03)00037-7 Gatev, P., Thomas, S., Kepple, T., & Hallett, M. (1999). Feedforward ankle strategy of balance during quiet stance in adults. The Journal of Physiology, 514(Pt 3), 915–928. PubMed doi:10.1111/j.1469-7793.1999.915ad.x Genthon, N., Vuillerme, N., Monnet, J.P., Petit, C., & Rougier, P. (2007). Biomechanical assessment of the sitting posture maintenance in patients with stroke. Clinical Biomechanics (Bristol, Avon), 22(9), 1024–1029. PubMed doi:10.1016/j.clinbiomech.2007.07.011
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Granata, K.P., & Wilson, S.E. (2001). Trunk posture and spinal stability. Clinical Biomechanics (Bristol, Avon), 16(8), 650–659. PubMed doi:10.1016/S0268-0033(01)00064X Grangeon, M., Gagnon, D., Duclos, C., Gauthier, C., Larivière, C., & Gourdou, P. (2013). Characterizing postural stability in a quasi-static sitting position among individuals with sensorimotor impairments following spinal cord injury. Journal of Bioengineering & Biomedical Sciences, 3, 124. Grangeon, M., Gagnon, D., Gauthier, C., Jacquemin, G., Masani, K., & Popovic, M.R. (2012). Effects of upper limb positions and weight support roles on quasi-static seated postural stability in individuals with spinal cord injury. Gait & Posture, 36(3), 572–579. PubMed doi:10.1016/j.gaitpost.2012.05.021 Hufschmidt, A., Dichgans, J., Mauritz, K.H., & Hufschmidt, M. (1980). Some methods and parameters of body sway quantification and their neurological applications. Archiv für Psychiatrie und Nervenkrankheiten, 228(2), 135–150. PubMed Jeka, J., Kiemel, T., Creath, R., Horak, F., & Peterka, R. (2004). Controlling human upright posture: Velocity information is more accurate than position or acceleration. Journal of Neurophysiology, 92(4), 2368–2379. PubMed doi:10.1152/jn.00983.2003 Kang, H.G., & Dingwell, J.B. (2006). A direct comparison of local dynamic stability during unperturbed standing and walking. Experimental Brain Research, 172(1), 35–48. PubMed doi:10.1007/s00221-005-0224-6 Kantor, E., Poupard, L., Le Bozec, S., & Bouisset, S. (2001). Does body stability depend on postural chain mobility or stability area? Neuroscience Letters, 308(2), 128–132. PubMed doi:10.1016/S0304-3940(01)01986-3 Karlsson, A., Norrlin, S., Silander, H.C., Dahl, M., & Lanshammar, H. (2000). Amplitude and frequency analysis of force plate data in sitting children with and without MMC. Clinical Biomechanics (Bristol, Avon), 15(7), 541–545. PubMed doi:10.1016/ S0268-0033(00)00010-3 Mancini, M., Salarian, A., Carlson-Kuhta, P., Zampieri, C., King, L., Chiari, L., & Horak, F.B. (2012). ISway: A sensitive, valid and reliable measure of postural control. Journal of Neuroengineering and Rehabilitation, 9, 59. PubMed doi:10.1186/1743-0003-9-59 Maurer, C., & Peterka, R.J. (2005). A new interpretation of spontaneous sway measures based on a simple model of human postural control. Journal of Neurophysiology, 93(1), 189–200. PubMed doi:10.1152/jn.00221.2004 Moore, S.P., Rushmer, D.S., Windus, S.L., & Nashner, L.M. (1988). Human automatic postural responses: Responses to horizontal perturbations of stance in multiple directions. Experimental Brain Research, 73(3), 648–658. PubMed doi:10.1007/BF00406624 Nayak, A., Karthikbabu, S., Vijayakumar, K., Ganesan, S., Chakrapani, M., & Prem, V. (2011). Sitting postural control is prerequisite for standing and stepping after stroke: A cross-sectional study. Physiotherapy and Occupational Therapy Journal, 4(1). Prieto, T.E., Myklebust, J.B., Hoffmann, R.G., Lovett, E.G., & Myklebust, B.M. (1996). Measures of postural steadiness: Differences between healthy young and elderly adults. IEEE Transactions on Bio-Medical Engineering, 43(9), 956–966. PubMed doi:10.1109/10.532130 Rocchi, L., Chiari, L., & Horak, F.B. (2002). Effects of deep brain stimulation and levodopa on postural sway in Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 73(3), 267–274. PubMed doi:10.1136/jnnp.73.3.267 Schoch, B., Hogan, A., Gizewski, E.R., Timmann, D., & Konczak, J. (2010). Balance control in sitting and standing in children and young adults with benign cerebellar tumors. Cerebellum (London, England), 9(3), 324–335. PubMed doi:10.1007/ s12311-010-0165-x Seelen, H.A., Potten, Y.J., Huson, A., Spaans, F., & Reulen, J.P. (1997). Impaired balance control in paraplegic subjects. Journal of Electromyography and Kinesiology, 7(2), 149–160. PubMed doi:10.1016/S1050-6411(97)88884-0
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van Nes, I.J., Nienhuis, B., Latour, H., & Geurts, A.C. (2008). Posturographic assessment of sitting balance recovery in the subacute phase of stroke. Gait & Posture, 28(3), 507–512. PubMed doi:10.1016/j.gaitpost.2008.03.004 Veerbeek, J.M., Van Wegen, E.E., Harmeling-Van der Wel, B.C., & Kwakkel, G. (2011). Is accurate prediction of gait in nonambulatory stroke patients possible within 72 hours poststroke? The EPOS study. [Research Support, Non-U.S. Government]. Neurorehabilitation and Neural Repair, 25(3), 268–274. PubMed doi:10.1177/1545968310384271 Verheyden, G., Vereeck, L., Truijen, S., Troch, M., Herregodts, I., Lafosse, C., . . .. De Weerdt, W. (2006). Trunk performance after stroke and the relationship with balance, gait and functional ability. Clinical Rehabilitation, 20(5), 451–458. PubMed doi:10.1191/0269215505cr955oa Vette, A.H., Masani, K., Sin, V., & Popovic, M.R. (2010). Posturographic measures in healthy young adults during quiet sitting in comparison with quiet standing. Medical Engineering & Physics, 32(1), 32–38. PubMed doi:10.1016/j.medengphy.2009.10.005 Winter, D.A. (1995). Human balance and posture during standing and walking. Gait & Posture, 3(4), 193–214. doi:10.1016/0966-6362(96)82849-9 Winter, D.A. (Ed.). (2005). Biomechanics and motor control of human movement. Hoboken, NJ: John Wiley and Sons. Winter, D.A., Patla, A.E., Prince, F., Ishac, M., & Gielo-Perczak, K. (1998). Stiffness control of balance in quiet standing. Journal of Neurophysiology, 80(3), 1211–1221. PubMed
Unsupported Eyes Closed Sitting and Quiet Standing Share Postural Control Strategies in Healthy Individuals Murielle Grangeon, Cindy Gauthier, Cyril Duclos, JeanFrancois Lemay, and Dany Gagnon The study aimed to (1) compare postural stability between sitting and standing in healthy individuals and (2) define center-of-pressure (COP) measures during sitting that could also explain standing stability. Fourteen healthy individuals randomly maintained (1) two short-sitting positions with eyes open or closed, with or without hand support, and (2) one standing position with eyes open with both upper limbs resting alongside the body. Thirty-six COP measures based on time and frequency series were computed. Greater COP displacement and velocity along with lower frequency measures were found for almost all directional components during standing compared with both sitting positions. The velocity, 95% confidence ellipse area, and centroidal frequency were found to be correlated between unsupported sitting and standing. Despite evidenced differences between sitting and standing, similarities in postural control were highlighted when sitting stability was the most challenging. These findings support further investigation between dynamic sitting and standing balance. Keywords: postural control, sitting, standing, stability, center of pressure, centroidal frequency, rehabilitation
Postural control can be defined as the postural strategies used to maintain the vertical projection of the center of mass (COM) of the body within the base of support (BOS) to prevent falls (Winter, 2005). Recent evidence using mostly clinical impairment scales suggests that postural control during sitting upon admission to intensive functional rehabilitation may accurately predict the ambulatory capacity (i.e., standing, stepping, and walking) upon discharge among individuals with neurological impairments (Nayak et al., 2011; Schoch, Hogan, Gizewski, Timmann, & Konczak, 2010; Veerbeek, Van Wegen, Harmeling-Van der Wel, & Kwakkel, 2011; Verheyden et al., 2006). However, limited evidence using a biomechanical approach is available to support this relationship between postural control during quiet sitting and standing (Genthon & Rougier, 2007; Vette, Masani, Sin, & Popovic, The authors are with the School of Rehabilitation, Université de Montreal, Montreal, Canada, and the Pathokinesiology Laboratory, Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal—Institut de réadaptation Gingras-Lindsay-de-Montréal, Montreal, Canada. Address author correspondence to Murielle Grangeon at [email protected]. 10
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Quiet Sitting Compared With Standing 11
2010). Standing and sitting postural control share many features (e.g., fight against gravity) but freedom of movements, inertial properties, and motor control differ. Damage to the neurological system may thus affect sitting and standing postural control differently. Comparing the underlying control mechanisms during quiet sitting and standing may thus provide a benchmark for future postural stability investigations, especially in the context of balance rehabilitation programs for the development of novel assessment tools and exercise. The location of the center of pressure (COP), defined as the origin of the ground reaction force vector on the surface of a force plate on which the subject is positioned, provides consistent information on postural control (Winter, 1995). Indeed, with coordinated neuromuscular response, the COP is positioned in such a way that it continuously regulates the COM within the BOS to prevent instability (Caron, Faure, & Breniere, 1997). The quantification of the COP displacement over time using various time and frequency measures is a commonly applied and wellaccepted technique to measure quasi-static postural stability and to characterize the control mechanisms used to stabilize the body during quiet standing (Baratto, Morasso, Re, & Spada, 2002; Mancini et al., 2012; Maurer & Peterka, 2005; Prieto, Myklebust, Hoffmann, Lovett, & Myklebust, 1996) or sitting (Boswell-Ruys et al., 2009; Grangeon et al., 2013). Indeed, during quasi-static conditions, the COP displacement results from spontaneous body sway needed to control posture and balance when no external disturbances are applied (Rocchi, Chiari, & Horak, 2002; Seelen, Potten, Huson, Spaans, & Reulen, 1997). However few studies have investigated the relationship of COP measures between quiet standing and sitting. Vette et al. (2010) figure among the first to have investigated the relationship of COP measures between quiet standing and sitting. Among five COP measures calculated for 12 healthy individuals, Vette et al. (2010) showed that only mean velocity correlated fairly well (ρ = .70) between both positions. However, the participant’s feet did not touch the floor in the sitting position; therefore, the ground reaction forces under the feet did not account for the displacement of the COP. Secondly, only within-task comparisons were performed for the eye condition (i.e., eyes open or closed). Vette et al. did not compare sitting with eyes closed to standing with eyes open. It is possible that the authors would have found more relationships between the most challenging sitting position for postural control (i.e., sitting with arms crossed over the chest and eyes closed) and standing with eyes open than they did. Finally, investigating a larger set of COP measures is needed to further validate the five COP measures selected by Vette et al. (2010), and potentially adding a few additional relevant measures will allow for a straightforward interpretation of the relationship between standing and sitting positions. Therefore, the main objectives of the current study were to compare two sitting positions (with and without upper limb [U/L] support) with eyes open or closed to a standing position with eyes open among healthy individuals, and verify whether healthy individuals ranked similarly in terms of postural stability for both the standing and sitting position. The secondary objective was to identify COP measures in a sitting position that could also explain stability achieved while standing, which could be further investigated as predictive recovery measures for standing stability. The COP measures were expected to determine potential biomechanical and motor control differences between standing and sitting. Nevertheless, the COP measures computed in the most challenging sitting position (i.e., unsupported sitting with eyes
12 Grangeon et al.
closed) were hypothesized to be more associated with the standing position than with the other sitting positions, particularly mean velocity and centroidal frequency.
Methods
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Participants Fourteen healthy male individuals volunteered to participate in this study after signing the informed consent (Table 1). None of them reported having musculoskeletal or neurological impairments. Ethical approval was obtained from the Research Ethics Committee of the Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR-456–0809).
Experimental Tasks During the sitting trials, participants sat on a height-adjustable instrumented seat with their back unsupported and each foot resting on a separate force plate embedded in the floor. Their thighs and feet were parallel to each other. Approximately 75% of their thigh length was in contact with the seat, with their knees flexed at approximately 85°. Participants maintained a quiet sitting position with eyes open or closed, with both hands resting on their thighs (supported sitting) or with both shoulders flexed at 90° and horizontally abducted at 45° (unsupported sitting). These two different U/L positions aimed to isolate the compensatory role of the U/Ls when maintaining quiet sitting. Unsupported sitting is commonly used for functional U/L tasks. The unsupported sitting position has also been found to be the most difficult task among sitting positions in healthy individuals and neurological populations (Grangeon et al., 2012). During the standing trials, participants maintained a quiet stance with each foot resting on a separate force plate embedded in the floor, with their U/Ls hanging along both sides of their body. Their feet were placed at 30° with their heels separated by 9 cm. A total of two 60-s trials in each position were randomly performed.
Instrumentation and Data Processing Ground reaction forces were recorded (600 Hz) underneath the buttocks (sitting position only) and each foot (sitting and standing position) using the various force plates. The combined triaxial components (i.e., anteroposterior [AP; Fx], vertical [Fy], and mediolateral [ML; Fz]) of the reaction forces and moments at each force plate with their own referential were then combined to compute the global COP time series within the global laboratory referential. Data were then filtered with a fourthorder Butterworth zero-lag low-pass digital filter with a cutoff frequency of 5 Hz.
COP-Related Outcome Measures A total of 17 COP measures were computed based on the methodology of Prieto et al. (1996; Table 2). Eleven of the 17 COP measures were composed of AP and ML components from which the resultant (RD) component was calculated at each data point, whereas the remaining 6 COP measures were extracted from the RD time series in the horizontal plane only (e.g., the area covered by the COP).
13
Age (Years) 23 67 60 53 33 38 50 35 37 30 43 33 24 54 41.43 13.46
Height (m) 1.74 1.74 1.66 1.7 1.74 1.81 1.67 1.78 1.78 1.79 1.65 1.89 1.73 1.68 1.74 0.07
Weight (kg) 76.9 70.2 80.9 73.7 78.6 83.6 65.8 86.3 87.5 94 78.6 74.3 91.1 80 80.11 7.90
BOS (Sitting) 0.31 0.31 0.26 0.31 0.30 0.33 0.28 0.37 0.39 0.38 0.33 0.35 0.28 0.32 0.32 0.04
(m2)
BOS (Standing) 0.15 0.11 0.09 0.10 0.10 0.13 0.11 0.14 0.15 0.16 0.12 0.11 0.09 0.12 0.12 0.02
(m2) Head 33 25 29.4 24 24 23 22.5 22.6 22.2 34 21.2 34 22.4 22 25.66 4.77
Segments Length (cm) Lower Trunk Thigh leg 56.4 39.5 39.8 52 43.7 44.4 54.2 36.2 39.3 56.2 37 42.2 54.2 42.2 40.5 55.9 43 42.8 55.6 36.5 41 53.5 27.2 43.6 51.2 44.6 42.3 54 40 43.5 46.2 40.5 40.6 57 60 49 56 43.8 39.8 51 40.2 40.3 53.81 41.03 42.08 2.93 7.06 2.56
Foot 26 25.5 24.8 25.5 25.5 27.4 25.7 40.1 26 24.5 25.9 28 27.3 28 27.16 3.89
Note. BOS = base of support. The contour of the BOS is continuously defined during the standing and sitting position by a convex area enclosing the contour of buttock and/or the feet segments (peripheral points) projected into the horizontal plane of the COP using an algorithm. The head segment was measured from chin to vertex, the trunk from trochanter to acromion, the thigh from trochanter to center of knee, the lower leg from the center of knee to center of malleolus, and the foot from the heel to the tip of the longest toe.
Participant 1 2 3 4 5 6 7 8 9 10 11 12 13 14 M SD
Table 1 Description of Participants
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14 Grangeon et al.
In the current study, postural stability was represented by three commonly reported dimensions: stability performance, control demand, and postural regulations (Grangeon et al., 2013). Stability performance and control demand (i.e., indicator of attentional resources required to maintain stability) were characterized by COP distance and velocity measures, respectively (Genthon, Vuillerme, Monnet, Petit, & Rougier, 2007; Hufschmidt, Dichgans, Mauritz, & Hufschmidt, 1980). A reduction in stability performance and an increase in control demand have often been associated with an increased risk of falling and reduced postural stability. Postural regulations are described by frequency measures, which could provide information on postural disturbances due to specific impairments or conditions (Demura, Kitabayashi, & Noda, 2008; Karlsson, Norrlin, Silander, Dahl, & Lanshammar, 2000). Despite a lack of consensus with regard to this interpretation, an increasing number of studies have revealed the capability of frequency measures to characterize postural control. More precisely, the FREQ-50% has been found to be sensitive to the contribution of various sensory information (i.e., integration of visual, vestibular, or somatosensory inputs; Bizid et al., 2009) and to change when a shift in preferential postural regulation occurs. The CFREQ, expressing the inertia of an inverted pendulum and the time for the COP to return to its initial position, is sensitive to the biomechanical properties of the studied system (Mancini et al., 2012; Vette et al., 2010). Finally, the FREQD, by describing the variability of the frequency content, may reveal the active–passive stiffness or rigidity of the system (Grangeon et al., 2013; Maurer & Peterka, 2005). Table 2 Summary of the COP-Related Outcome Measures Types of Measure Time-domain distance measures
Time-domain area measures Time-domain hybrid measures
Outcome Measure MDIST (mm)a RDIST (mm)a TOTEX (mm)a RANGE (mm)a MVELO (mm/s)a AREA-CC (mm2) AREA-CE (mm2) AREA-SW (mm2/s) MFREQ (Hz)a FD-RD FD-CC FD-CE
Frequency domain measures
a
T POWERa 50% (Hz)a 95% (Hz)a CFREQ (Hz)a FREQDa
Description average distance from the mean COP RMS distance total length of the COP path Maximum distance between any two points Average velocity of the COP 95% confidence circle area 95% confidence ellipse area sway area mean frequency fractal dimension fractal dimension based on the area-CC fractal dimension based on the area-CE total power frequency median power frequency 95% power frequency centroidal frequency frequency dispersion
Computed based on resultant (RD) time series as well as on the anteroposterior and mediolateral time series.
Quiet Sitting Compared With Standing 15
Statistical Analysis
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Once the normality of data were verified with the Shapiro–Wilk test, repeatedmeasures analyses of variance were computed for each COP measure using a significance level of .05. Bonferroni pairwise comparisons with an adjusted significance level (p = .05/4) were performed in case of significant results. Spearman rho correlation coefficients (ρ) were also computed to reveal potential relationships between the sitting and standing positions. Correlation coefficients were considered very strong above .90, strong between .70 and .89, and moderate between .50 and .69 (Demholdt, 2000). All statistical analyses were performed using SPSS version 20.0 software.
Results An example of a COP path during the three positions with eyes open is illustrated in Figure 1. All COP measures and statistical results are summarized in Table 3. Greater displacement, velocity, area, and lower frequency measures were confirmed for almost all the directional components in the standing position compared with both sitting positions. TPOWER for all directional components and the ML component of MVELO and TOTEX were similar for the three positions, irrespective of the vision condition. Significant differences were found for the AP and/or ML directional component of FREQD, despite similarity for the RD component between the standing position and both sitting positions, irrespective of the vision condition. Lastly, using Spearman’s rho correlation coefficients (Figure 2), only a few measures for the ML component were found to be correlated between standing with eyes open and unsupported sitting with eyes closed. RANGE-ML (ρ = .56, p = .04), MVELO-ML, and TOTEX-ML (ρ = .62, p = .01) were moderately correlated between these two positions, while CFREQ-ML (ρ = .73, p = .003) was strongly correlated. Other COP measures were weakly correlated or uncorrelated between standing and sitting (ρ = .09–.49), irrespective of the vision condition.
Discussion As expected, the differences in stability achieved while standing and sitting suggest that the mechanical demand governing balance in these positions is different as evidenced by the increased COP displacements, velocity, and lower frequency measures observed during standing compared with both sitting positions, particularly on the AP directional component. The present findings are thus in agreement with the previous related study of Vette et al. (2010) that revealed greater and faster body sway in standing, defined by a lower centroidal frequency and a reduced variability in frequency content (i.e., FREQD), compared with sitting position. Quiet standing is assumed to be more challenging than sitting. The inverted pendulum theory states that the stability of the rigid body is inversely related to the height of the COM above the BOS. Because the COM is farther from the BOS in a standing position than in a sitting position, postural sway increases to maintain the COM close to the initial position (i.e., larger COP amplitude, greater COP velocity, and lower COP frequency). Moreover, the BOS is larger when sitting than when standing (Kantor, Poupard, Le Bozec, & Bouisset, 2001), suggesting less postural demand to maintain stability.
16
2,95 ± 1,10
20,57 ± 14,87
2,03 ± 0,97
17,41 ± 28,07
3,12 ± 1,21
6,08 ± 1,16
255,58 ± 174,38 16,03 ± 11,21 134,49 ± 64,85 2,23 ± 1,52 8,09 ± 3,78
3,95 ± 0,95
Task 2 Task 3 1,27 ± 0,45 4,23 ± 1,4 1 ± 0,39 3,71 ± 1,43 0,58 ± 0,24 1,36 ± 0,55 1,45 ± 0,51 4,95 ± 1,60 1,22 ± 0,47 4,57 ± 1,61 0,72 ± 0,30 1,70 ± 0,72 164,1 ± 45,03 224,3 ± 50,17 118,62 ± 28,39 182,36 ± 34,94 88,55 ± 32,99 93,5 ± 36,41 6,37 ± 2,06 21,83 ± 5,32 6,05 ± 1,95 21,27 ± 5,44 3,88 ± 1,38 9,02 ± 4,32 5,47 ± 1,50 7,48 ± 1,67
3,57 ± 1,64
Task 1 1,03 ± 0,80 0,86 ± 0,78 0,4 ± 0,21 1,16 ± 0,87 1,02 ± 0,85 0,51 ± 0,26 135,07 ± 62,55 106,95 ± 49,16 60,81 ± 29,04 5,28 ± 3,83 5,03 ± 3,80 3,10 ± 2,07 4,5 ± 2,08
10,86 ± 14,43 AREA-CE (mm2) AREA-SW(mm2/s) 1,55 ± 1,88
MDIST-RD (mm) MDIST-AP (mm) MDIST-ML (mm) RDIST-RD (mm) RDIST-AP (mm) RDIST-ML (mm) TOTEX-RD (mm) TOTEX-AP (mm) TOTEX-ML (mm) RANGE-RD (mm) RANGE-AP (mm) RANGE-ML (mm) MVELORD(mm/s) MVELOAP(mm/s) MVELOML(mm/s) AREA-CC (mm2)
Eyes Opened
3.00 ± 1,03
4,06 ± 1,34
8,84 ± 8,68 1,36 ± 1,23
23,85 ± 30,95 2,95 ± 3,4
15,06 ± 19,15 60,15 ± 152,69
2,12 ± 1,09
3,61 ± 1,43
*** ***
**
**
*** ***
**
**
*** ***
**
**
*** *
**
Task Comparisona T1 EO T2 EO T1 EC T2 EC Task 1 Task 2 vs. T3 EO vs. T3 EO vs. T3 EO vs. T3 EO 0,91 ± 0,38 1,59 ± 1,59 *** *** *** ** 0,74 ± 0,35 1,31 ± 1,62 *** *** *** * 0,39 ± 0,17 0,62 ± 0,22 *** *** *** ** 1,10 ± 0,57 1,78 ± 1,67 *** *** *** ** 0,96 ± 0,55 1,54 ± 1,70 *** *** *** ** 0,51 ± 0,24 0,76 ± 0,26 *** *** *** *** 137,49 ± 56,23 167,85 ± 52,17 ** * ** 108,25 ± 42,98 121,73 ± 40,29 ** ** ** ** 63,49 ± 32,67 90,08 ± 30,83 5,43 ± 3,24 7,35 ± 4,87 *** *** *** *** 5,11 ± 3,08 7,14 ± 4,87 *** *** *** *** 3,03 ± 1,92 4,16 ± 1,35 ** ** *** ** 4,58 ± 1,87 5,59 ± 1,74 ** * **
Eyes Closed
Table 3 Means ±SD of COP-Related Outcome Measures and Statistical Results
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Task 1 0,84 ± 0,31 0,95 ± 0,39 1,02 ± 0,3 1,49 ± 0,08 1,60 ± 0,09 1,64 ± 0,09 16,84 ± 5,09 49,3 ± 26,75 51,44 ± 13,4 0,83 ± 0,31 0,68 ± 0,30 0,80 ± 0,21 3,19 ± 0,39 2,75 ± 0,35 2,65 ± 0,41 1,52 ± 0,25 1,33 ± 0,27 1,35 ± 0,25 0,66 ± 0,05 0,67 ± 0,05 0,63 ± 0,04
Task 2 0,75 ± 0,21 0,80 ± 0,25 0,96 ± 0,26 1,47 ± 0,06 1,58 ± 0,07 1,60 ± 0,06 16,18 ± 4,33 43,11 ± 20,20 54,4 ± 17,24 0,67 ± 0,24 0,57 ± 0,23 0,70 ± 0,23 2,95 ± 0,37 2,71 ± 0,28 2,49 ± 0,37 1,37 ± 0,21 1,22 ± 0,19 1,25 ± 0,20 0,68 ± 0,05 0,68 ± 0,05 0,62 ± 0,05
Task 3 0,30 ± 0,08 0,33 ± 0,09 0,44 ± 0,15 1,29 ± 0,03 1,37 ± 0,05 1,42 ± 0,04 17,42 ± 4,18 39,16 ± 13,55 55,72 ± 15,02 0,35 ± 0,07 0,29 ± 0,07 0,39 ± 0,11 1,26 ± 0,26 1,03 ± 0,22 1,03 ± 0,32 0,64 ± 0,10 0,53 ± 0,08 0,58 ± 0,15 0,63 ± 0,05 0,61 ± 0,06 0,57 ± 0,05
Task 1 Task 2 0,85 ± 0,21 0,74 ± 0,18 0,95 ± 0,28 0,82 ± 0,24 1,01 ± 0,22 0,9 ± 0,18 1,48 ± 0,08 1,47 ± 0,05 1,60 ± 0,08 1,58 ± 0,07 1,64 ± 0,07 1,59 ± 0,04 19,20 ± 3,18 16,54 ± 3,64 52,26 ± 18,53 47,64 ± 19,08 55,76 ± 14,03 54,95 ± 15,47 0,82 ± 0,27 0,64 ± 0,18 0,69 ± 0,24 0,49 ± 0,18 0,79 ± 0,20 0,60 ± 0,13 3,01 ± 0,49 2,91 ± 0,18 2,63 ± 0,53 2,59 ± 0,33 2,63 ± 0,36 2,44 ± 0,28 1,48 ± 0,29 1,34 ± 0,14 1,31 ± 0,29 1,15 ± 0,15 1,29 ± 0,21 1,17 ± 0,12 0,65 ± 0,05 0,68 ± 0,04 0,65 ± 0,04 0,71 ± 0,05 0,63 ± 0,04 0,65 ± 0,04
Eyes Closed
*
*** ** *** *** *** *** *** *** ***
*
*** ** ** *** *** *** *** *** ***
*** ** *** *** *** *** *** *** ***
*** **
*** * ** *** *** *** *** *** ***
Task Comparisona T1 EO T2 EO T1 EC T2 EC vs. T3 EO vs. T3 EO vs. T3 EO vs. T3 EO *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** ***
Note. Task ¹ 1 or T1 = supported sitting position; task ¹ 2 or T2 = unsupported sitting position; task ¹ 3 or T3 = standing position. EO = eyes open; EC = eyes closed. aResults from t tests with Bonferroni adjustments when analysis of variance interaction was significant *p < .0125; **p ≤.01; ***p ≤ .001.
MFREQ-RD (Hz) MFREQ-AP (Hz) MFREQ-ML (Hz) FD-RD FD-CC FD-CE T POWER-RD T POWER–AP TPOWER-ML 50%-RD (Hz) 50%-AP (Hz) 50%-ML (Hz) 95%-RD (Hz) 95%-AP (Hz) 95%-ML (Hz) CFREQ-RD (Hz) CFREQ-AP (Hz) CFREQ-ML (Hz) FREQD-RD FREQD-AP FREQD-ML
Eyes Opened
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Figure 1 — Typical global COP path (m) observed over time during both supported and unsupported sitting with eyes opened as well as standing in one healthy individual.
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Quiet Sitting Compared With Standing 19
Figure 2 — Relationship found on the mediolateral (ML) component of MVELO and CFREQ between unsupported sitting with eyes closed (EC) and standing position with eyes opened (EO).
Using hand support or maintaining the U/Ls over the thighs and forward in combination with anterior foot support also helps to stabilize the sitting position, at least for the forward quadrants. This might reduce agonistic and antagonistic muscle cocontractions in a sitting position as reduced oscillations are observed. The increased variability in frequency content on AP or ML component observed while sitting versus standing supports this hypothesis and may reflect the reduced use of trunk muscular synergies to regulate stability (Maurer & Peterka, 2005).
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Furthermore, the reduced moment of inertia of the moving body in both sitting positions compared with quiet standing increases frequency of body oscillations and explains the consistent large centroidal frequency during sitting (Winter, Patla, Prince, Ishac, & Gielo-Perczak, 1998). Therefore, in line with previous findings from other studies (Collins, De Luca, Burrows, & Lipsitz, 1995; Kang & Dingwell, 2006; Vette, Masani, Sin, & Popovic, 2010), the current study further confirms that sitting positions are more stable from a mechanical perspective and might require less neural feedback control than the standing position. Based on the two-part control behavior of Collins et al. (1995; i.e., a closed-loop control scheme implying the presence of neural feedback control over longer time intervals and an open-loop control scheme implying no neural control over short time intervals), the system during sitting might have less probability to drift away from a relative equilibrium point over short-term intervals compared with standing, suggesting fewer controlled adjustments in the longer term to bring the system back to equilibrium. However, further investigations using neural control indicators, such as the stabilogram diffusion function measures (Collins et al., 1995), are warranted to definitively confirm the neural aspect of postural control. These differences in the magnitude, velocity, and frequency of body sway between standing and sitting might also support the differences in postural strategy between these positions. Indeed, during quiet standing, the body is often assimilated to an inverted pendulum (Gage, Winter, Frank, & Adkin, 2004), described as a single body segment rotating around the ankle joints. In the AP direction, healthy individuals mainly use the ankle strategy to maintain stability in standing (Gatev, Thomas, Kepple, & Hallett, 1999) so that the upper and lower body move in the same direction, involving muscle activation (distal to proximal). When sitting with feet on the floor, the degree of freedom of the ankle and knee joints is greatly restricted so that only the upper body can be assimilated to an inverted pendulum model rotating around the hip joints (Granata & Wilson, 2001). In the AP direction in a sitting position, healthy individuals most likely use the hip strategy to maintain stability, involving muscle activation in the hip, pelvis, and trunk. Despite these differences between standing and sitting, hip, abdominal, and lower trunk muscles are essential for attaining postural control with both strategies because they provide the levels of stabilizing forces necessary for maintaining the rigidity of the trunk. Given this similarity, trunk sensorimotor impairments might alter the efficiency of both the ankle and hip strategy to maintain standing and sitting stability, respectively. In the AP directional component, the greater number of degrees of freedom used to maintain stability (i.e., muscular adjustments at the ankle, knee, and hip) provide individuals with an increased inventory of possible compensatory strategies to adjust AP stability and compensate for anticipated and nonanticipated external perturbations. However, in the ML direction, the primary response occurred at the hip both in standing and sitting conditions (Moore, Rushmer, Windus, & Nashner, 1988). The few correlations found between standing and sitting tend to reveal these similarities when sitting is the most challenging or when using one postural strategy is not enough to maintain postural control. The correlation of TOTEXML, MVELO-ML, and RANGE-ML between standing and unsupported sitting with eyes closed suggests similarities in postural control to maintain ML stability (i.e., sensorimotor information and integration; Jeka, Kiemel, Creath, Horak, & Peterka, 2004). These results differed from the study of Vette et al. (2010), who
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Quiet Sitting Compared With Standing 21
found that the MVELO was correlated between standing and sitting for the eyes open condition on all directional components. Differences in the protocol such as the computation of COP measures only from force plates underneath the buttocks, the position of the U/Ls (crossed on chest), and the smaller sample size (n = 12) in their study might explain these differences. Because correlations were also revealed on the ML component in the current study, it might be inferred that ML postural control may be a key to explaining similarities in standing and sitting stability. Furthermore, although dynamic properties using the moment inertia theory can explain differences between sitting and standing (as previously discussed), the strong correlation of CFREQ-ML between unsupported sitting with eyes closed and standing with eyes open strengthens these potential similarities in the applied control strategies. Interestingly, this measure was also found to be the most sensitive and reliable measure among the frequency COP measures in previous studies focusing on both standing and sitting stability (Grangeon et al., 2013; Mancini et al., 2012). Because CFREQ is an indirect measure of the moment of inertia, it reflects the time for the system to return to the equilibrium position. Thus, comparable ML control adjustments in unstable sitting and standing might be needed to bring the system back to the equilibrium position and to prevent falls. Studies among neurological populations have demonstrated that selective movements of the trunk help to maintain the COM within the BOS during static and dynamic postural adjustments during sitting, standing, and stepping (Davis, 1990; Edwards, 1996), particularly anticipatory postural trunk muscle activity (Dickstein, Shefi, Marcovitz, & Villa, 2004). Trunk control performance impairments were therefore found to be associated with impaired sitting and standing stability (Chern et al., 2010; van Nes, Nienhuis, Latour, & Geurts, 2008). Our conclusion that similarities in the postural control could be found between standing and the most challenging sitting position is thus supported by the correlations between MVELO and CFREQ between standing with eyes open and unsupported sitting with eyes closed. However, the small sample size (n = 14) of the current study needs to be considered since it may limit the power of these findings. Nevertheless, the present sample size does confirm a large to moderate similarity between standing and both sitting positions, since a statistical power of .77 and .49 was computed for the MVELO-ML and CFREQ-ML, respectively. Further investigations combining kinetic, kinematic, and muscular activity to compare sitting and standing are warranted to confirm the use of COP measures as an assessment tool for describing postural disorders during unsupported sitting and standing. In addition, because similar postural control seems to occur when a sitting position is the most challenging, future studies investigating the relationship between dynamic sitting and standing stability will also be relevant. If increased relationships between these positions are revealed, dynamic sitting upon admission to a rehabilitation program must also be investigated as a potential indicator of gait recovery at discharge. These results might be interesting for specificity of balance training in rehabilitation programs.
Conclusion This study aimed to highlight the relationship between standing and quiet sitting in healthy individuals. As expected, most COP measures differed during standing compared with both sitting positions and confirmed differences in mechanical and
22 Grangeon et al.
postural regulation. However, similarities existed between standing and sitting when sitting stability was reduced, suggesting similarity in postural control strategy. Additional prospective cohort studies on trunk involvement in postural control during quiet and dynamic sitting and standing among healthy and neurological populations is required to strengthen the level of current evidence.
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