Subjects were recruited from the University community through targeted advertising. Those who met the inclusion criteria were thoroughly informed about the research’s aims and procedures, and informed consent was obtained. The study was conducted in accordance with Institutional Review Board guidelines (IRB #1653.21).

Inclusion criteria for the LBP group included being between 50 and 75 years of age, right limb dominant, experiencing persistent LBP for at least three months prior to data collection, and having no severe pathologies or conditions preventing unilateral standing. The criteria for the control subjects were the same as the LBP group, except they did not have a history of chronic LBP or recurrent musculoskeletal disorders and no severe musculoskeletal, neurological, or vestibular conditions affecting balance. Exclusion criteria included any diagnosed psychological disorders that could disrupt the protocol, neurological symptoms (e.g., sensory deficits or motor paralysis), or pregnancy.

Recruitment of the control group accounted for age and body mass index (BMI) to match subjects and to control for potential confounding variables. The study focused on the dominant limbs of both the upper and lower extremities, given that prior research has identified limb dominance as a potential confounding factor [16, 17].

Upon arrival at the laboratory, subjects completed health status questionnaires, which included demographic and medical history information. The level of disability was measured using the Oswestry Disability Index (ODI), which is a 10-item questionnaire that evaluates the impact of low back (or leg) pain on daily activities [18]. In addition, pain intensity was assessed using a visual analogue scale (VAS), which allows subjects to mark their pain level on a continuous line, providing both continuous and interval-level measurement data.

Subjects were instructed to remove their shoes and stand barefoot on the platform, aligning the medial malleolus with the horizontal guideline and the calcaneus with the anteroposterior (AP) guideline to ensure consistent COP positioning. Standardized protocols for single-leg stance tasks were followed, as depicted in Fig. 1. The eyes-open condition was always performed first to allow participants to familiarize themselves with the testing environment and task demands. This was followed by the eyes-closed condition to assess postural control without visual input. The order of visual conditions was predetermined, with all participants completing the eyes-open condition first, followed by the eyes-closed condition. This was done to minimize variability due to adaptation effects.

A 10-second rest period was provided between trials to minimize fatigue and maintain performance consistency. In addition, all assessments were conducted by the same trained personnel. The ankle joint was aligned with the transverse rotational axis, and the lateral aspect of the calcaneus was positioned accurately. The y-axis represented AP movements on the platform, while mediolateral (ML) shifts on the support surface were tracked along the x-axis (side-to-side motion). Dual force plates were used, allowing rotation about the x-axis, which served as the transverse axis of the ankle joint, providing a reference for calculating sway angles.

A full-body safety harness system, secured to an overhead bar, was worn by subjects to prevent fall injuries. Subjects stood on the Bertec Balance Advantage® system for Computerized Dynamic Posturography with Immersion Virtual Reality (CDP-IVR) with their feet positioned comfortably apart (Fig. 1). The CDP-IVR allowed for the measurement of balance performance and the monitoring of postural stability improvements.

The unilateral standing test was conducted for postural stability and included two different conditions, which were eyes-open and eyes-closed conditions in dominant limb standing. Each condition of the standardized procedure was demonstrated for the subjects. For example, a subject was asked to stand steady on the dominant foot for 10 s on the balance plate with his/her eyes open. The initial position included standing relaxed with eyes open. Upon request, the subject stood upright on the force plate with the contralateral hip and knee flexed to approximately 30 degrees. Participants were instructed to keep their arms at their sides during the initial stance; however, compensatory arm movements were permitted to maintain balance. For the eyes-closed condition, participants followed the same stance procedure but closed their eyes after assuming the correct position. Each trial lasted 10 s, followed by a 10-second rest interval before the next repetition.

The ground reaction force (GRF) was recorded using a force plate at a sampling frequency of 1,000 Hz. The force plate was pre-calibrated by the manufacturer, and a sensitivity matrix was applied to convert voltage readings into forces and torques. In addition, baseline data were collected from the unloaded platform to establish the zero offset, ensuring precise measurement of postural stability during unilateral stance tasks. All kinetic data were processed with a fourth-order low-pass Butterworth filter, using a 20 Hz cutoff frequency, and normalized by body weight. The COP metrics provided insight into postural organization and dynamic stability. Subjects completed three 10-second trials of unilateral standing on the force platform, with COP and COG data captured to measure sway excursions in the AP and ML directions. Only trials in which participants successfully maintained the full standing duration were included in the final analysis, with total standing time recorded until the non-weight bearing leg contacted the force plate.

In our study, the mean and standard deviation of COP and COG sway ranges (max - min) were analyzed for the AP and ML directions [19, 20]. The formula was utilized for COP AP (Mx/Fz) and COP ML (-My/Fz), where: Fz represents the vertical GRF recorded by the force plate, Mx is the moment of the ML axis used to calculate COP displacement in the AP direction, and My is the moment of the AP axis used to calculate COP displacement in the ML direction.

The COG position, which accounts for body dynamics, was estimated using the inverted pendulum model, which conceptualizes balance control as a function of mass distribution. COG was derived by adjusting COP based on body acceleration and estimated height, allowing for precise assessment of neuromuscular control strategies in maintaining equilibrium. By analyzing COG displacement relative to COP, neuromuscular control strategies were inferred in stabilizing posture [21].

To ensure comparability across participants and to account for variability in height, leg length, and body weight, COP and COG displacement values were normalized. This approach allows for a standardized evaluation of postural sway metrics, minimizing the influence of anthropometric differences. This estimation accounts for postural adjustments by incorporating the acceleration of the COP in both the AP and ML directions. In addition, the height of the body’s COG is determined using anthropometric data, while gravitational acceleration is used as a reference parameter. The COG position was calculated based on force plate data, incorporating COP) and body acceleration using the following equations:\(\:COGx=COPx-\ddot X\)ḥ/ġ, \(\:COGy=COPy-\ddot Y\)ḥ/ġ, where: \(\:COPx,COPy=\) COP in the ML and AP directions respectively, Ẍ, Ÿ = acceleration of COP in ML and AP directions, ḥ = estimated height of the COG, ġ = acceleration due to gravity (9.81 m/s2).

Neuromuscular responses were analyzed by quantifying COP-COG displacement, which represents the instantaneous distance between COP and COG. This measure is independent of body weight and is used to assess balance regulation. During unilateral standing, the body is vertically aligned over the mathematical COG of the weightbearing foot. The COP - COG displacement was calculated as:

$$\:_-_=\left|_-_\right|$$

$$\:_-_=\left|_-_\right|$$

This metric quantifies the deviation between actual pressure distribution and the center of body mass movement. The COP-COG displacement serves as an indicator of neuromuscular control efficiency, measuring the spatial difference between postural control (COP) adjustments and body mass center (COG) shifts [7, 22]. Furthermore, the neuromuscular responses reflected by COP-COG distance represent the instantaneous separation between COP and COG, independent of body weight effects. The difference between COP and COG serves as a key measure of neuromuscular control strategies, highlighting an individual’s ability to maintain balance by adjusting for postural sway during stance tasks. Figure 2 is an example of the neuromuscular control of sway distance (COP-COG), which was analyzed during 10 s of unilateral standing. The three repeated trials were plotted as different lines for each x (ML direction) and y (AP direction).

Preliminary power analyses were conducted based on the pilot data comparing groups, under the assumption of setting the type I error rate at 0.05. In our study, the sample size calculation determined that a minimum of 28 subjects per group would provide 80% power to detect an effect size of 0.4. The effect sizes were analyzed by partial Eta-squared values (η2p) within repeated measures analysis of variance (ANOVA) (small ≥ 0.01, medium ≥ 0.06, large ≥ 0.14), which was used to indicate the mean difference between groups. The independent variables included groups (with and without LBP).

To investigate differences in individual characteristics between the groups, an independent sample t-test was utilized. Mixed repeated measures ANOVA were employed to examine main and interaction effects on sway distance (COP-COG) while considering visual condition. The general linear model was applied to assess all continuous dependent variables based on a by-group factorial experimental design. For multiple comparisons, post-hoc analysis was conducted using the Bonferroni test. Accounting for these individual characteristics is essential for interpreting dynamic standing balance strategies. Failure to control such confounding variables could compromise the generalizability of the findings. All statistical analyses were performed using SPSS version 28.0 (IBM Corp, Armonk, NY, USA) with a significance level set at 0.05 for all tests.