Use of Nintendo Wii Balance Board for posturographic analysis of Multiple Sclerosis patients with minimal balance impairment

Abstract

Background: The Wii Balance Board (WBB) has been proposed as an inexpensive alternative to laboratory-grade Force Plates (FP) for the instrumented assessment of balance. Previous studies have reported a good validity and reliability of the WBB for estimating the path length of the Center of Pressure. Here we extend this analysis to 18 balance related features extracted from healthy subjects (HS) and individuals affected by Multiple Sclerosis (MS) with minimal balance impairment.

Methods: Eighteen MS patients with minimal balance impairment (Berg Balance Scale 53.3 ± 3.1) and 18 age-matched HS were recruited in this study. All subjects underwent instrumented balance tests on the FP and WBB consisting of quiet standing with the eyes open and closed. Linear correlation analysis and Bland-Altman plots were used to assess relations between path lengths estimated using the WBB and the FP. 18 features were extracted from the instrumented balance tests. Statistical analysis was used to assess significant differences between the features estimated using the WBB and the FP and between HS and MS. The Spearman correlation coefficient was used to evaluate the validity and the Intraclass Correlation Coefficient was used to assess the reliability of WBB measures with respect to the FP. Classifiers based on Support Vector Machines trained on the FP and WBB features were used to assess the ability of both devices to discriminate between HS and MS.

Results: We found a significant linear relation between the path lengths calculated from the WBB and the FP indicating an overestimation of these parameters in the WBB. We observed significant differences in the path lengths between FP and WBB in most conditions. However, significant differences were not found for the majority of the other features. We observed the same significant differences between the HS and MS populations across the two measurement systems. Validity and reliability were moderate-to-high for all the analyzed features. Both the FP and WBB trained classifier showed similar classification performance (>80%) when discriminating between HS and MS.

Conclusions: Our results support the observation that the WBB, although not suitable for obtaining absolute measures, could be successfully used in comparative analysis of different populations.

Keywords: Multiple Sclerosis; Posturographic Analysis; Wii Balance Board.

Fig. 1

Example of the calculation of Stabilogram Diffusion Analysis features from a diffusion plot. Diffusion plots are characterized by a behavior that can be modeled as two intersecting linear functions. The parameter < Δr² _CR > is calculated as the first negative zero crossing of the derivative of the SDA line. The parameter D_s is calculated as half of the slope of the line best fitting the portion of the curve from 0 to < Δr² _CR>

Fig. 2

Comparison of the stabilograms for each combination of task/population. Each plot presents the superimposed detrended stabilograms for each task of each subject. Grey lines represent COP trajectories obtained from the FP, while black lines represent those obtained from the WBB. Stabilograms obtained from the WBB are generally wider than those obtained from FP. Moreover, while for both the WBB and the FP in HS there are limited differences between the stabilograms relative to eyes-open and eyes-closed conditions, for MS stabilograms relative to the eyes-closed condition are generally more extended than those relative to eyes-open condition

Fig. 3

Linear Correlation analysis between path lengths (ML, AP and Total) calculated using the FP and WBB. Data for HS and MS and for both testing conditions (eyes-open and eyes-closed) have been pooled together in this analysis. Parameters of the fitting (p-value, R², Slope and Intercept of the fitting) are presented in the plot for each analysis. WBB and FP present similar linear trends for both ML and AP COP directions, consistent with an overestimation of the directional sway in the WBB with respect to FP

Fig. 4

Bland-Altman Plots for each combination of task/population. Subplot (a) presents the results for ML direction, subplot (b) for the AP direction and subplot (c) for the total path length. Y axis of each plot presents the difference between FP and WBB, while X axis presents the average between the two measures. All the plots show a decrease in accuracy of the WBB with respect to the FP as the magnitude of the estimated value increases

Fig. 5

Stabilogram Diffusion Plots for eyes-open and eyes-closed conditions. Black lines represent data from MS, while grey lines represent data from HS. Bold lines represent data obtained using the FP, while dash-dot lines present data obtained using the WBB. Each line represents the average Stabilogram Diffusion Plot across all the subjects for each measurement system in each condition. MS patients present higher diffusion plot curves that are consistent with increased sway. Diffusion plots obtained from WBB follow similar trends with respect to those obtained from FP

Fig. 6

Classification performance for the 4 different set of SVM-based classifiers trained. Classifiers have been trained for each combination of task/measurement device. Y axis shows the percentage of successful classifications for each set of classifiers. All classifiers show similar accuracy. Classifier built from the eyes-closed database for both WBB and FP yield classification performance >80%