Center of Pressure Motion After Calf Vibration Is More Random in Fallers Than Non-fallers: Prospective Study of Older Individuals

Wolbert van den Hoorn, Graham K Kerr, Jaap H van Dieën, Paul W Hodges, Wolbert van den Hoorn, Graham K Kerr, Jaap H van Dieën, Paul W Hodges

Abstract

Aging is associated with changes in balance control and elderly take longer to adapt to changing sensory conditions, which may increase falls risk. Low amplitude calf muscle vibration stimulates local sensory afferents/receptors and affects sense of upright when applied in stance. It has been used to assess the extent the nervous system relies on calf muscle somatosensory information and to rapidly change/perturb part of the somatosensory information causing balance unsteadiness by addition and removal of the vibratory stimulus. This study assessed the effect of addition and removal of calf vibration on balance control (in the absence of vision) in elderly individuals (>65 years, n = 99) who did (n = 41) or did not prospectively report falls (n = 58), and in a group of young individuals (18-25 years, n = 23). Participants stood barefoot and blindfolded on a force plate for 135 s. Vibrators (60 Hz, 1 mm) attached bilaterally over the triceps surae muscles were activated twice for 15 s; after 15 and 75 s (45 s for recovery). Balance measures were applied in a windowed (15 s epoch) manner to compare center-of-pressure (CoP) motion before, during and after removal of calf vibration between groups. In each epoch, CoP motion was quantified using linear measures, and non-linear measures to assess temporal structure of CoP motion [using recurrence quantification analysis (RQA) and detrended fluctuation analysis]. Mean CoP displacement during and after vibration did not differ between groups, which suggests that calf proprioception and/or weighting assigned by the nervous system to calf proprioception was similar for the young and both groups of older individuals. Overall, compared to the elderly, CoP motion of young was more predictable and persistent. Balance measures were not different between fallers and non-fallers before and during vibration. However, non-linear aspects of CoP motion of fallers and non-fallers differed after removal of vibration, when dynamic re-weighting is required. During this period fallers exhibited more random CoP motion, which could result from a reduced ability to control balance and/or a reduced ability to dynamically reweight proprioceptive information. These results show that non-linear measures of balance provide evidence for deficits in balance control in people who go on to fall in the following 12 months.

Keywords: aging; balance; detrended fluctuation analysis; falls; muscle vibration; proprioception; recurrence quantification analysis; somatosensory.

Figures

Figure 1
Figure 1
Recurrence quantification analysis methods. (A) CoP motion in anterior-posterior example of a participant (faller) showing baseline, first and second vibrations (VIB) and 45 s after each vibration. Data were analyzed using 15-s epochs (ep). This includes the vibration epoch, and epochs 1–31 (post vibration epochs), which started after cessation of vibration and was shifted in time with 1-s intervals (93.33% overlap) until 45 s after vibration to assess balance after vibration. This resulted in two sets (two vibration repetitions) of 32 epochs (1 vibration + 31 post vibration) for each participant which were used for statistical analysis to assess group differences. Group differences at the baseline epoch were assessed separately as there was only 1 repetition available (see Statistics section for more details). (B) Example of a CoP epoch (blue) delayed with a tau of 180 ms. (C) A phase space was created by plotting the delayed CoP copies against each other. Note that the example is given in 3D, but, analysis was performed in 5D. (D) The recurrence plot represents the recurrences of CoP in the phase space depicted in (C); by creating a 2D recurrence plot by adapting the recurrence threshold distance to fix the recurrence rate to 5%. Temporally close recurrences were excluded (<1 s, Theiler window) which is represented by the grayed area along the line of identity (were CoP recurs with itself). Two examples are shown that represent a diagonal (in light and dark green) and vertical recurrence structures (in red). These examples are also shown in the phase space in (C). The light and dark green represents CoP motion running parallel in phase space and the red line represents CoP motion that revisits and remains in a region in phase space represented by the red dot in (C) and (D).
Figure 2
Figure 2
Detrended fluctuation analysis (DFA) methods. (A) Example of a 15-s CoP motion (see Figure 1A in blue). (B) CoP was integrated, then fluctuations of CoP around linear fits over windows ranging from 0.10 to 4.42 s were determined with 50% overlap. Example of 0.2 s is given. (C) Log-log plot of time windows vs. fluctuations. Two linear regions were fit by minimizing the squared errors between the combined linear fits and actual data. DFA1 and DFA2 reflect the general organization of fluctuations at shorter and longer time scales, respectively. DFAtau reflects the time scale between DFA1 and DFA2.
Figure 3
Figure 3
Results of linear measures during vibration (VIB) and post-vibration epochs. Top panel show mean for each group of (A) mean center of pressure (CoP) displacement and (B) sway path length (SP). Bottom panel in (A,B) show mean differences between groups (open dots), and the significant (sign) difference between groups (solid lines). Note that group differences are significant when the solid line matches the open dots. Group differences at baseline (BL) were assessed separately and are presented for visual reference. Error bars represent 95% confidence interval (1.96 × standard error of measurement).
Figure 4
Figure 4
Results of recurrence quantification analysis (RQA) of diagonal line features during vibration (VIB) and post-vibration epochs. Top panels show mean for each group of (A), mean percentage determinism (%DET) and (B) mean diagonal line lengths (Lmean). Bottom panels in (A,B) show mean differences between groups (open dots), and the significant (sign) difference between groups (solid lines). Note that group differences are significant when the solid line matches the open dots. Group differences at baseline (BL) were assessed separately and are presented for visual reference. Error bars represent 95% confidence interval (1.96 × standard error of measurement).
Figure 5
Figure 5
Results of recurrence quantification analysis (RQA) of vertical line features during vibration (VIB) and post-vibration epochs. Top panels show mean for each group of (A) mean percentage laminarity (%LAM) and (B) mean vertical line lengths (TT). Bottom panels in (A,B), mean differences between groups (open dots), and the significant (sign) difference between groups (solid lines). Note that group differences are significant when the solid line matches the open dots. Group differences at baseline (BL) were assessed separately and are presented for visual reference. Error bars represent 95% confidence interval (1.96 × standard error of measurement).
Figure 6
Figure 6
Results of detrended fluctuation analysis (DFA) during vibration (VIB) and post-vibration epochs. Top panels show mean for each group of (A) DFA1 (short term), (B) DFA2 (long term), and (C) DFAtau (time scale that separates DFA1 and DFA2). Bottom panels in (A–C) show mean differences between groups (open dots), and the significant (sign) difference between groups (solid lines). Note that group differences are significant when the solid line matches the open dots. Group differences at baseline (BL) were assessed separately and are presented for visual reference. Error bars represent 95% confidence interval (1.96 × standard error of measurement).

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Source: PubMed

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