Training and testing of balance have potential applications in sports and medicine. Laboratory grade force plates (FP) are considered the gold standard for the measurement of balance performance. Measurements in these systems are based on the parameterization of center of pressure (CoP) trajectories. Previous research validated the inexpensive, widely available and portable Nintendo Wii Balance Board (WBB). The novelty of the present study is that FP and WBB are compared on CoP data that was collected simultaneously, by placing the WBB on the FP. Fourteen healthy participants performed ten sequences of single-leg stance tasks with eyes open (EO), eyes closed (EC) and after a sideways hop (HOP). Within trial comparison of the two systems showed small root-mean-square differences for the CoP trajectories in the x and y direction during the three tasks (mean±SD; EO: 0.33±0.10 and 0.31±0.16 mm; EC: 0.58±0.17 and 0.63±0.19 mm; HOP: 0.74±0.34 and 0.74±0.27 mm, respectively). Additionally, during all 420 trials, comparison of FP and WBB revealed very high Pearson's correlation coefficients (r) of the CoP trajectories (x: 0.999±0.002; y: 0.998±0.003). A general overestimation was found on the WBB compared to the FP for 'CoP path velocity' (EO: 5.3±1.9%; EC: 4.0±1.4%; HOP: 4.6±1.6%) and 'mean absolute CoP sway' (EO: 3.5±0.7%; EC: 3.7±0.5%; HOP: 3.6±1.0%). This overestimation was highly consistent over the 140 trials per task (r>0.996). The present findings demonstrate that WBB is sufficiently accurate in quantifying CoP trajectory, and overall amplitude and velocity during single-leg stance balance tasks.

Time to stabilization (TTS) is the time it takes for an individual to return to a baseline or stable state following a jump or hop landing. A large variety exists in methods to calculate the TTS. These methods can be described based on four aspects: (1) the input signal used (vertical, anteroposterior, or mediolateral ground reaction force) (2) signal processing (smoothed by sequential averaging, a moving root-mean-square window, or fitting an unbounded third order polynomial), (3) the stable state (threshold), and (4) the definition of when the (processed) signal is considered stable. Furthermore, differences exist with regard to the sample rate, filter settings and trial length. Twenty-five healthy volunteers performed ten 'single leg drop jump landing' trials. For each trial, TTS was calculated according to 18 previously reported methods. Additionally, the effects of sample rate (1000, 500, 200 and 100 samples/s), filter settings (no filter, 40, 15 and 10 Hz), and trial length (20, 14, 10, 7, 5 and 3s) were assessed. The TTS values varied considerably across the calculation methods. The maximum effect of alterations in the processing settings, averaged over calculation methods, were 2.8% (SD 3.3%) for sample rate, 8.8% (SD 7.7%) for filter settings, and 100.5% (SD 100.9%) for trial length. Differences in TTS calculation methods are affected differently by sample rate, filter settings and trial length. The effects of differences in sample rate and filter settings are generally small, while trial length has a large effect on TTS values.

Background:Soccer has a high injury rate, with lateral ankle sprains being a common injury. Therefore, an approach to prevent or at least reduce the occurrence is warranted. Injury prevention can be improved by identifying specific risk factors and individuals at risk.Purpose:To assess drop-jump landing performance as a potential predictor of lateral ankle sprain within 3-year follow-up.Study Design:Case-control study; Level of evidence, 3.Methods:Single-legged drop-jump landing tests were performed by 190 elite soccer players. Based on ground-reaction forces, 6 outcome measures were calculated that aim to reflect the impact and stabilization phase. Lateral ankle sprains were registered during up to 3 years of follow-up. Following a z score correction for age, a multivariate regression analysis was performed.Results:During follow-up, 45 players (23.7%) suffered a primary lateral ankle sprain. Of those, 34 were regarded as severe (absence >7 days). Performance was related to increased risk of ankle sprain (P = .005 for all sprains and P = .001 for severe sprains). Low mediolateral stability for the first 0.4 seconds after landing (a larger value indicates more force exerted in the mediolateral direction, resulting in rapid lateral stabilization) and high horizontal ground-reaction force between 3.0 and 5.0 seconds (a smaller value indicates less sway in the stabilization phase) were identified as risk factors. A player that scored 2 SD below average for both risk factors had a 4.4-times-higher chance of sustaining an ankle sprain than a player who scored average.Conclusion:The current study showed that following a single-legged drop-jump landing, mediolateral force over 0 to 0.4 seconds and/or mean resultant horizontal ground-reaction force over 3 to 5 seconds has predictive value with regard to the occurrence of an ankle sprain among male elite soccer players within 3 years.

The present findings support our hypothesis that the VM contributes similarly to total knee extension torque at different knee angles.

We aimed to verify whether the static phase after a single leg drop jump (DJ) landing on a force plate may serve as a proxy for a single leg stance (SLS) balance task, as this would increase the application possibilities of landing tasks in the evaluation of sensorimotor function in relation to injury rehabilitation or performance assessment. Twenty-five healthy participants performed two sessions of five valid trials for both tasks in a reproducibility-agreement design. Three postural stability outcome measures ('COP speed', 'COP sway' and 'Horizontal GRF') were calculated for DJ (5-20s after landing) and for SLS (15s), and were averaged per session. Paired T-tests revealed a learning effect of SLS for postural stability (4.6-6.1%; P-values <0.03), in contrast to DJ (P-values >0.27). Only session 2 resulted in superior postural stability for SLS compared to DJ for 'COP speed' (5.0%; P=0.017) and 'Horizontal GRF' (8.2%; P=0.001). Bland and Altman methods demonstrated inter-session SD's of difference for DJ of 11-12% and for SLS of 10-12%, while inter-task SD's of difference ranged 10-17%. Precision ('SD within') was better for SLS concerning 'COP speed' (14-15% vs 13%) and 'Horizontal GRF' (18-20% vs 14-15%). In conclusion, postural stability during DJ and SLS cannot be considered interchangeable, due to a learning effect for SLS and inferior precision for DJ. However, a DJ task may be used as a proxy for static postural stability, although more than three trials are needed to achieve individual errors similar to SLS for 'COP speed' (4) and 'Horizontal GRF' (5).

In research regarding postural stability, leg preference is often tested and controlled for. However, leg preference may vary between tasks. As athletes are a group of interest for postural stability testing, we evaluated the effect of five leg preference tasks categorization (step up, hop, ball kick, balance, pick up) on single-leg postural stability of 16 field hockey athletes. The 'center of pressure speed' was calculated as the primary outcome variable of single-leg postural stability. Secondary variables were 'mean length of the GRF vector in the horizontal plane', 'mean length of the ankle angular velocity vector', and 'mean length of the hip angular velocity vector', as well as the separate outcomes per degree of freedom. Results showed that leg preference was inconsistent between leg preference tasks. Moreover, the primary and secondary variables yielded no significant difference between the preferred and non-preferred legs, regardless of the applied leg preference task categorization (p>0.05). The present findings do not support the usability of leg preference tasks in controlling for bias of postural stability. In conclusion, none of the applied leg preference tasks revealed a significant effect on postural stability in healthy field hockey athletes.

This study provides recommendations concerning the potential of various dynamic tests and force plate parameters as a tool to compare neuromusculoskeletal function between patients with foot and ankle pathology and healthy controls.

A B S T R A C TThe single leg drop jump landing test may assess dynamic and static balance abilities in different phases of the landing. However objective definitions of different phases following landing and associated reliability are lacking.Therefore, we determined the existence of possible distinct phases of single leg drop jump landing on a force plate in 82 elite youth soccer players. Three outcome measures were calculated over moving windows of five sizes: center of pressure (COP) speed, COP sway and horizontal ground reaction force (GRF).Per outcome measure, a Factor Analysis was employed with all windows as input variables. It showed that four factors (patterns of variance) largely (>75%) explained the variance across subjects/trials along the 12 s time series. Each factor was highly associated with a distinct phase of the time series signal: dynamic (0.4-2.7 s), late dynamic (2.5-5.0 s), static 1 (5.0-8.3 s) and static 2 (8.1-11.7 s).Intra-class correlations (ICC) between trials were lower for the dynamic phases (0.45-0.68) than for the static phases (0.60-0.86). The COP speed showed higher ICC's (0.63-0.86) than COP sway (0.45-0.61) and GRF (0.57-0.71) for all four phases.In conclusion, following a drop jump landing unique information is available in four distinct phases. The COP speed is most reliable, with higher reliability in the static phases compared to the dynamic phases. Future studies should assess the sensitivity of information from dynamic, late dynamic and static phases.