Effect of Anti-Slip Flooring on Gait Biomechanics and Slip Risk in Elderly Women with Osteoporosis and Healthy Elderly

1 Effect of Anti-Slip Flooring on Gait Biomechanics and Slip Risk in Elderly Women with Osteoporosis and Healthy Elderly Sajad Azizi1 1 Department of Biomedical Engineering, Faculty of Medical Sciences and Technologies, Science and Research Branch, Islamic Azad University, Tehran, Iran Sajad[email protected] Abstract Osteoporosis significantly increases the risk of falls in elderly individuals, particularly women, due to compromised neuromuscular control and balance. This study explored the effects of anti-slip flooring on gait biomechanics, slip risk, and kinematic responses in elderly women with osteoporosis compared to healthy elderly controls. The experiment included 22 elderly women, with 11 participants suffering from severe osteoporosis and 11 healthy controls. Participants walked on anti-slip flooring surface (IR), while kinematic, slip-related and gait parameters were recorded using a VICON motion capture system and KISTLER force plates. The results showed that anti-slip flooring surface (IR) slightly increased walking speed and reduced slip distances, though these changes were not statistically significant. Significant differences were observed between the two groups in gait parameters. The osteoporosis group walked 131 slower than the healthy group (p = .0..0 ). Additionally, step time (STET) and stride time (STRT) were 121 and 131 longer, respectively, in the osteoporosis group compared to the healthy group (p = .0..0 and p = .0..0 ). Furthermore, double support time (DS) was significantly 201 higher in the osteoporosis group (p < .0..1). Regarding cadence (CDC), the osteoporosis group had 1.1 fewer steps than the healthy group (p = .0..4 ). Finally, kinematic analysis revealed that the time to peak (TTP) was significantly longer in the osteoporosis group compared to the healthy group, particularly for ankle dorsiflexion angle (p = .0.23 ), knee extension angle (p < .0..1 ), and hip flexion angle (p = .0..6 ). These results indicate delayed neuromuscular and kinematic responses in the osteoporosis group. In conclusion, while anti-slip flooring surfaces showed minor improvements in walking speed and slip risk reduction, the more profound effects of osteoporosis on gait biomechanics, including slower walking speeds, altered temporal parameters, and delayed neuromuscular responses, were evident. The study suggests that antislip flooring can provide some benefit in reducing slip risks but cannot compensate for the neuromuscular deficits in osteoporotic individuals. Combining anti-slip flooring with targeted neuromuscular training and balance exercises is essential for effective fall prevention in elderly populations with osteoporosis. Keywords: Osteoporosis, Gait biomechanics, Slip risk, Anti-slip flooring, Elderly fall prevention 1Introduction Osteoporosis, a condition characterized by reduced bone density and increased fragility, is particularly common among elderly individuals, especially women. This condition 2 significantly increases the risk of fractures, notably in the hip and spine (Laing & Robinovitch, 2..2; Huang et al., 2.24). Falls, a leading cause of fractures in this population, are influenced by various factors, including biomechanical, neuromuscular, and environmental elements. Environmental factors such as flooring type have a significant role in modulating balance, gait, and the risk of falls (Lockhart et al., 2..2; Sturnieks, 2.21). Elderly individuals with osteoporosis are at an even higher risk of falling due to impaired neuromuscular responses, reduced muscle strength, sensory degradation, and slower reflexes. These impairments compromise their balance and ability to adjust to postural disturbances (Hsu et al., 2.14; Alshahrani et al., 2.24). In addition, changes in gait biomechanics such as reduced stride length and slower walking speeds are commonly observed in this population, as they compensate for balance deficits when walking on various surfaces (Thies et al., 2..5; Marigold & Patla, 2..0). The impact of environmental conditions, particularly flooring type, on slip risk is well-established. Flooring conditions, including their texture and frictional properties, affect gait parameters such as walking speed, stride length, and double-support time, and significantly influence slip-related variables such as slip distance and the required coefficient of friction (Menant et al., 2..0; Lockhart & Kim, 2..6). Elderly individuals often alter their gait to mitigate the risk of slipping, such as walking at slower speeds and increasing double-support time (Williams & Martin, 2.21; Nascimento et al., 2.22). This study investigates the effect of anti-slip flooring on gait biomechanics, slip risk, and kinematic parameters in elderly women with osteoporosis compared to healthy elderly controls. A biomechanical analysis was conducted to evaluate key slip-related variables, including slip distance, coefficient of friction, and heel contact velocity, along with gait parameters such as walking speed, stride length, and double-support time. The study also examined kinematic factors such as joint angles and the trajectory of the center of pressure, which contribute to slip incidents. By comparing these parameters between the two groups, the study aims to shed light on how anti-slip flooring influence gait biomechanics and balance control in elderly women with osteoporosis. The findings aim to provide valuable insights into designing safer living environments for elderly individuals, ultimately reducing fall risks and improving overall stability, particularly for those with osteoporosis. 2Materials and Methods 2 - 1 -Participants This cross-sectional study received approval from the Clinical Research Ethics Committee of the Biomechanics Department at the Islamic Azad University, Science and Research branch. The study included 22 elderly women aged over 6., divided into two groups: one with severe osteoporosis (n=11) and a healthy control group (n=11). The osteoporosis group had an average age of 64040 ± 4025 years, weight of 60044 ± 12022 kg, and height of 155033 ± 5025 cm, while the control group had an average age of 640.. ± 3012 years, weight of 01002 ± 12034 kg, and height of 160003 ± 1.034 cm. The participants' mean Oswestry Disability Index (ODI) score was 402 ± 4034, and their average Abbreviated Mental Test Score (AMTS) was 200 ± .041. Prior to the study, all participants provided written informed consent and underwent a thorough medical evaluation by a rheumatologist to confirm their eligibility. Exclusion criteria included neurological conditions (e.g., multiple sclerosis, Parkinson's disease), neuromuscular disorders, stroke, peripheral neuropathies, inner ear diseases, genetic bone disorders (such as osteogenesis imperfecta, osteosclerosis), and cancers affecting Bone Mineral Density (BMD). Individuals with a BMI below 15 kg/m and those with severe 3 osteoporosis (defined by a T-score of less than -205 or greater than +205 standard deviations, potentially due to genetic factors or measurement errors) were also excluded. The ODI and AMTS questionnaires were used to evaluate pain levels and cognitive function, respectively. 2 - 2 -Anti-slip Flooring This study employed anti-slip flooring surfaces: (1) IR: a stiff non-slip PVC mat, 1. mm thick, with a patterned grid design (Klein Wolke Co., Germany). The surface fully covered the walking and standing path, with the force plates placed underneath. Figure 1. Utilizing anti-slip flooring surface: a patterned plastic surface (IR). 2 - 3 -Experimental Procedure and Data Acquisition Prior to the commencement of the experiment, the examiner provided each participant with thorough instructions regarding the procedures and execution of the tests. Before data collection, participants performed several practice trials to familiarize themselves with the walkway and ensure consistent foot placement on the force plates. They were instructed to walk barefoot, focus straight ahead, and maintain a natural walking pattern. No information about the purpose of the force plates embedded in the ground was given, to avoid influencing their behavior. During the steady-state walking phase, three successful trials were targeted, each involving three consecutive steps with correct heel strikes on the force plates and no double foot contact events. Participants were advised to wear form-fitting clothing to facilitate the attachment of markers. A specialized suit with the "Full body Plug-In-Gait VICON" marker pattern was fitted to each subject, who was also instructed to remove their shoes. A total of 54 retroreflective markers (14 mm, ©B&L Engineering, California, USA) were placed on bony landmarks according to the "Full body Plug-In-Gait VICON" protocol (Azizi et al., 2.21) to measure kinematics, spatiotemporal, and slip parameters. The experimental protocol involved walking at a comfortable self-selected pace on various surfaces. Each participant completed three successful trials on the surface, with the average values from these trials used to minimize inter-trial variation. A 3.-second rest interval was provided between trials to prevent fatigue effects. Participants underwent a full-body instrumented gait analysis at the Javad Movafakhian Neuroscience Rehabilitation Center (JMNRC) movement analysis laboratory. The setup included a synchronized three-dimensional passive motion capture system (0 Vicon T1. cameras, ©Vicon Motion Systems Ltd., Oxford, UK, 1.. frames per second, resolution 1 Megapixel 112. × 026) and three embedded KISTLER force plates (6-0, 1... Hz, 46 × 5. × 0 cm, ©KISTLER Instruments AG, Winterthur, Switzerland). Kinematic data were collected at 1.. Hz using the eight-camera VICON system, while force data were gathered at 1... Hz. All marker, kinematic, and kinetic data were filtered using a 4th-order reversed Butterworth filter with a low-pass frequency of 1. Hz (Criekinge et al., 2.23). 4 Marker trajectories were processed using Nexus 205 software. Gaps in the data were filled manually (using pattern or spline-based methods) with a maximum of 2. consecutive frames, ensuring the accuracy of the marker paths. Foot strike and toe-off events were determined in Nexus based on ankle and heel marker trajectories as well as force plate signals, with a force threshold of 2. N (Mei et al., 2.22). All events were visually verified for accuracy. The Plug-In-Gait Dynamic pipeline within Nexus was used for the processing of kinematic and kinetic data. This pipeline employs a fifth-order Woltring filter with an MSE smoothing value of 1. and integrates participant-specific anthropometric data (e.g., body mass, height, leg length) to enhance the model’s precision. The pipeline calculates joint angles, joint velocity, center of mass, joint moments, and joint power. To further refine the accuracy of joint center and axis calculations for internal markers, the Plug-in-Gait model was improved by incorporating the SARA and Score algorithms. These algorithms are designed specifically to optimize the positioning of joint centers and axes, ensuring more precise kinematic and kinetic results. Finally, the processed data were exported from Nexus in ASCII format for the extraction of research variables. 2 - 4 -Dependent Variable Analysis and Calculation 2 - 4 - 1 -Slip-Propensity Parameter The analyzed data from the motion analysis system and ground reaction forces during walking were utilized to provide a precise definition of individuals' slip status. The analysis of the heel contact phase offers detailed insights into the slip-stick condition and the ability to recover balance. Heel contact is defined as the moment when the vertical ground reaction force (GRF) exceeds 1.-2. Newtons (N), with slips typically occurring within the 5. to 1..-millisecond timeframe following heel contact (Lockhart et al., 2..3). Therefore, the analysis of spatiotemporal parameters within this interval is of critical importance. Subsequently, specific parameters are determined to evaluate the slip status and balance recovery ability of elderly individuals with severe osteoporosis: Initial Slip Distance (ISD) refers to the horizontal distance the slipping foot travels from the moment of first contact with a slippery surface to its maximum displacement relative to the body's center of mass. It reflects the extent of uncontrolled initial slipping and is mainly influenced by surface characteristics, frictional forces, and the individual’s reactive capacity. This phase begins with a sudden reduction in required coefficient of friction (RCOF) and ends before any corrective movement is initiated. In contrast, Second Slip Distance (SSD) represents the horizontal distance traveled from the end of ISD until the slipping foot regains stability. It reflects the body’s attempt to recover balance and is affected by neuromuscular control and postural reactions. This distinction between ISD and SSD is essential in biomechanical analyses of slips and fall risk (Liu & Lockhart, 2..2)0 2 - 4 - 2 -Minimum Required Coefficient of Friction at Heel Contact (MRCOF-HC) MRCOF-HC (Minimum Friction Coefficient at Heel Contact) represents the friction demand exerted on the floor by the walker at the moment of heel contact. If the tribological interaction between the shoe and the floor surface provides sufficient friction to meet the MFCOF-HC requirement, walking proceeds without interruption. However, if MFCOF-HC exceeds the available friction at the shoe-floor interface, a foot-slip may occur, particularly under slip perturbation conditions. MRCOF-HC is defined as the ratio of the resultant horizontal shear forces (Fx, Fy) to the vertical ground reaction force (Fz) at the moment of heel contact (Equation 1). ) Eq. 1 This measurement is valid only when heel contact occurs precisely on the force plate, ensuring that no external forces (e.g., partial foot contact from the contralateral foot) interfere 5 with the force profile. Kinetically, heel contact is identified when the vertical ground reaction force exceeds 2. N. To ensure accurate MFCOF-HC calculation, the moment of heel contact, determined via the vertical force threshold, was cross-verified with the minimum position of the heel marker. Figure 2. Diagram of the vertical component of the GRF at the moment of heel strike (red dashed vertical line) and the moment of minimum required coefficient of friction immediately after heel strike. MRCOF-HC was assessed over the duration of the footfall on the force plate. If a slip is to occur, it typically initiates within 5.–1.. ms following heel contact. Correspondingly, MRCOF-HC reaches its peak shortly after heel contact, serving as a critical determinant of slip occurrence. The absolute value of this peak represents the MRCOF-HC value of interest. 2 - 4 - 3 -Gait Parameters & Kinematic Variables To evaluate the effect of anti-slip flooring on the changes in the mechanoreceptor response of the feet in osteoporosis elderly, and to investigate the correlation between slip parameters and gait parameters, the following gait variables were selected: Cadence (CDC), Walking Speed (WS), Step Length (STEL) and Time (STET), Stride Length (STRL) and Time (STRT), Width Step Length (WSL), and changes in Single and Double Support (SS & DS) during the stance phase. To compare the effect of anti-slip flooring on gait biomechanics in elderly individuals with osteoporosis and healthy elderly, the kinetic parameters were analyzed, including Joint Angles (JA) and Angular Velocities (AV) of the lower extremities. These parameters were assessed at three key points in the gait cycle: Heel Contact (HC), Peak Value (PV), and Time to Peak (TTP) for each joint. Statistical comparisons across different flooring surfaces were made to evaluate how surface properties influence gait biomechanics in both groups. 3Results The results for slip and gait parameters, as well as each of the dependent variables of the study, are presented separately for anti-slip flooring surface (IR) and two groups of healthy elderly and those with severe osteoporosis. Specifically, the presentation sequence is as follows: first, the trends of changes in slip parameters; then, gait parameters; followed by each 6 kinematic variable, including sagittal joint angles (JA) and angular velocities (JV) for each lower limb joint (A: ankle, K: knee, H: hip); at each joint, at heel contact (HC), first peak (P), and time-to-peak (TTP). 3 - 1 -Slip Parameters The trend of changes between the two groups for ISD and SSD slip parameters was reversed, with results showing that the ISD value in osteoporosis elderly was 5.1 higher than in healthy elderly individuals, and the SSD value was 121 lower. In the osteoporosis group, a higher MRCOF value was observed at heel strike (251 increase). In other words, healthy elderly individuals exhibited less friction immediately after heel strike compared to elderly individuals with osteoporosis. Although the differences in slip parameters between the two groups were not reported as statistically significant, these differences are relatively substantial. Figure 4. The average values of the Initial Slip Distance (ISD), Second Slip Distance (SSD), and Minimum Coefficient of Friction (MRCOF) parameters at the moment of heel strike during walking were compared between two groups: elderly with severe osteoporosis and healthy elderly. Gait Parameters Figure 5 illustrates the significant differences between the elderly groups with osteoporosis and the healthy elderly group. The results revealed a significant 131 increase in WS in the healthy elderly compared to those with osteoporosis (p = .0..0 ). Additionally, although there was a decrease in STEL and STRL in the osteoporosis group compared to the healthy group, this difference was negligible and not statistically significant. However, STET and STRT were each significantly higher in the osteoporosis group than in the healthy group, by 121 (p = .0..0 ) and 131 (p = .0..0 ), respectively. While SS was higher in the osteoporosis group, this difference was not significant. In contrast, DS showed a significant 201 increase in the osteoporosis group compared to the healthy group (p < .0..1 ). 7 Figure 5. The average values of walking speed (WS), step length (STEL), step time (STEL), stride length (STRL), stride time (STRT), single support (SS), and double support (DS) across anti-slip flooring surface between two groups: healthy elderly individuals and elderly individuals with severe osteoporosis. Figure 6 illustrates the CDC variation trends between healthy elderly individuals and those with osteoporosis at different walking speeds. The various gait speeds did not result in any significant changes in CDC. However, a significant difference was observed between the two groups, healthy elderly and those with osteoporosis (p = .0..4 ). Specifically, the CDC value in the healthy elderly group was 1.1 higher than in the elderly group with osteoporosis. Figure 6. The average Cadence (CDC) between healthy elderly individuals versus those with severe osteoporosis 3 - 2 -Kinematics variables at Heel contact This section presents the results of changes in kinematic variables, including joint angles (JA) and angular velocities (JV) of the ankle, knee, and hip in the sagittal plane at the moment of heel strike during walking across anti-slip flooring surface between two groups: elderly individuals with severe osteoporosis and healthy elderly individuals. The results did not show significant changes in the mean angle and angular velocity of any lower limb joints between the healthy elderly and osteoporotic groups at the instant of heel strike (HC). However, the ankle dorsiflexion velocity in the osteoporotic elderly was 411 lower than in the healthy elderly. Additionally, the JV.K.HC and JV.H.HC values were also reduced in the osteoporotic elderly by 201 and 161, respectively, compared to the healthy elderly. 8 Figure 7. This figure illustrates the mean sagittal joint angle (JA) and angular velocity (JV) of the ankle (A), knee (K), and hip (H) joints at heel contact (HC) at anti-slip flooring surface for both healthy elderly individuals and elderly individuals with severe osteoporosis. 3 - 3 -Peak and TTP Kinematic Variables This section presents the peak changes in kinematic variables, including JA and JV of the ankle, knee, and hip in the sagittal plane, across anti-slip flooring surface (IR) between two groups: elderly individuals with severe osteoporosis and healthy elderly individuals. The results showed no significant effect on the initial peak following heel strike on the changes in JA and JV of the lower extremities joints between the two groups of healthy elderly and osteoporotic individuals. Additionally, no significant difference was observed between the surfaces in the JA and JV of the lower limb joints. Although the mean peak angular velocity of all three joints (ankle, knee, and hip) was higher at the IR surface compared to the others, this difference was not statistically significant. Furthermore, no notable differences were found in the peak joint angles across the different flooring surfaces. 9 Figure 9. The mean peak (P) values of joint angle (JA) and joint velocity (JV) for ankle (A), knee (K), and hip (H) joints on anti-slip flooring (IR) between two groups: healthy elderly and elderly with severe osteoporosis 3 - 4 -TTP of Kinematic variables 16 55. Shahriari, S., Azizi S, S., & Tabatabai Ghomsheh, F. (2.10). Kinematics analysis of ankle dorsiflexion when using the modified orthosis in order to increase stability in the moment of heel strike with the ground. Journal of Advanced Sport Technology, 1(1), 3.-30.