A Lifespan Approach to Balance in Static and Dynamic Conditions: The Effect of Age on Balance Abilities

Abstract

Postural control is a complex sensorimotor skill that is fundamental to our daily life. The abilities to maintain and recover balance degrade with age. However, the time decay of balance performance with age is not well understood. In this study, we aim at quantifying the age-dependent changes in standing balance under static and dynamic conditions. We tested 272 healthy subjects with ages ranging from 20 to 90. Subjects maintained the upright posture while standing on the robotic platform hunova®. In the evaluation of static balance, subjects stood on the fixed platform both with eyes open (EO) and eyes closed (EC). In the dynamic condition, subjects stood with eyes open on the moving foot platform that provided three different perturbations: (i) an inclination proportional to the center of pressure displacements, (ii) a pre-defined predictable motion, and (iii) an unpredictable and unexpected tilt. During all these tests, hunova® measured the inclination of the platform and the displacement of the center of pressure, while the trunk movements were recorded with an accelerometer placed on the sternum. To quantify balance performance, we computed spatio-temporal parameters typically used in clinical environments from the acceleration measures: mean velocity, variability of trunk motion, and trunk sway area. All subjects successfully completed all the proposed exercises. Their motor performance in the dynamic balance tasks quadratically changed with age. Also, we found that the reliance on visual feedback is not age-dependent in static conditions. All subjects well-tolerated the proposed protocol independently of their age without experiencing fatigue as we chose the timing of the evaluations based on clinical needs and routines. Thus, this study is a starting point for the definition of robot-based assessment protocols aiming at detecting the onset of age-related standing balance deficits and allowing the planning of tailored rehabilitation protocols to prevent falls in older adults.

Keywords: age-dependent changes; aging; perturbations; postural control; standing balance; static and dynamic assessment.

Figure 1

Age distribution of subjects.

Figure 2

Proposed exercises: static exercises performed both with eyes open (test 1) and closed (test 2). The platform is kept fixed for the whole duration of the test; unstable exercise (test 3), the platform moves proportionally to the body's weight shift; adaptive exercise (test 4), the platform moves in a predictable and pre-programmed way on a circular trajectory; reactive exercise with different perturbation directions (test 5), the platform moves in a pre-programmed way, providing perturbations unpredictable for the users, tilting around the x-axis for the lateral perturbations (orange arrows, right-foot down and left-foot down) and around the z-axis, forward perturbation (gray arrow).

Figure 3

Experimental data from a representative subject to explain the parameters selected for the analysis of the proposed tasks. Parameters are based on readings of an Inertial Measurement Unit (IMU) placed on the sternum of the subject, i.e., parameters are extracted from the acceleration measures. (A) On the first column, the stabilograms (black line) and the variability (red shaded area, STD) of a 20-s exercise both in the ML (up) and AP (bottom) directions are shown. In the second column, the statokinesigram (gray line) together with the fitted confidence ellipse (red shaded area) representing the sway area are shown. Those parameters are computer for tests 1, 2, 3, and 4. (B) This panel shows the postural response after a perturbation of a representative subject for test 5: in red the perturbation trajectory, in blue the postural response along the perturbation's direction. Here, the peaks amplitudes are highlighted (light blue dashed line) together with the peak-to-peak time difference (black line).

Figure 4

Computed parameters for all the performed tests. Each graph represents how each single parameter changes with age [x-axis: age (years), y-axis: normalized performance indexes]. In each graph, dots represent single subjects' performance; colored line is the parabolic fitted curve; black line represents the age by age mean curve; dashed color line is the reference performance (y = 0). The colored shaded patch highlights the reference age windows used for normalization (age between 20 and 24). Each row is relative to a different test: namely (from top to bottom) static EO, static EC, unstable, adaptive, reactive exercise (forward and lateral perturbation). Each column is relative to a specific computed parameter, namely, (from left to right) mean velocity (MV), STD AP, STD ML, sway area (SA, for test 1–4), and P2P_time, P2P_amp, Peak₁, and Peak₂, (for test 5).

Figure 5

Motor performance of the subjects under 25 expressed as mean and standard deviation. This is the normalization factor we used before applying the fitting (see methods section for more details). (A) for test from 1 to 4, and (B) for test 5.