# Validation of Smartphone Sway Analysis for Fall Prevention
## 3 Results  
The summary of the participants' characteristics and the main results of this investigation is shown in Table 1.  
The correlation between average path length and average velocity as measured by the force plate and the phone application was calculated to be 0.83 and 0.86, respectively. The correlations were also calculated for the medial-lateral and anterior-posterior directions. (Table 2). \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Mean** & **Standard Deviation** \\ \hline Age (years) & 20.5 & 1.10 \\ Height (m) & 1.75 & 0.09 \\ Weight (N) & 712 & 131 \\ Male (number) & 25 & n/a \\ Female (number) & 8 & n/a \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of the participants. Figure 2: Typical plots of the position of center of pressure (COP) in the anterior-posterior direction as calculated from the data acquired by the force plate and the phone application. Visually, the correlation may be seen in Figure 3, which shows average path length and average velocity for each subject as measured by the force plate and smart phone application. The correlations in the medial-lateral direction fell below 60 (Table 3). Thus, smartphone application and force plate data cannot be correlated. For the anterior-posterior direction, which is often associated with falls, it can be observed that the correlations were very high (Table 4). The average path length correlations between the plate and application was nearly 0.83, and the velocities between both application and plate correlated at 0.84. The lowest correlation in this direction was the correlation of the path length of the application with that of the plate's velocities at 0.72, which is not necessarily as important as a criterion, since the comparison of path length to velocity is the comparison of two different categories. In short, correlations in the direction most associated with falls between directly comparable variables suggest a strong correlation between the application and the force plate results. \begin{table}
\begin{tabular}{c c c c c} \hline  & **APLP** & **APLA** & **AVP** & **AVA** \\ \hline APLP & 1.00 & 0.832 & 0.90 & 0.86 \\ APLA & 1.00 & 0.69 & 0.89 \\ AVP & & 1.00 & 0.86 \\ AVA & & & 1.00 \\ \hline \end{tabular}
\end{table} 
Table 2: Correlation results for both directions (33 subjects). Figure 3: Average path length (on the left) and average velocity (on the right) as evaluated from the force plate and smart phone application results (33 subjects). \begin{table}
\begin{tabular}{c c c c} \hline  & **APLP** & **APLA** & **AVP** & **AVA** \\ \hline APLP & 1.00 & 0.58 & 0.98 & 0.50 \\ APLA & & 1.00 & 0.60 & 0.97 \\ AVP & & & 1.00 & 0.54 \\ AVA & & & 1.00 \\ \hline \end{tabular}
\end{table} 
Table 3: Correlation results for the medial-lateral direction (33 subjects). Another way of relating the phone application and the force plate is through the total path length exhibited by a subject. The results shown in the Table 5 suggest a strong correlation between total path calculated for the force plate and the application at 0.83. In the posterior-anterior direction the correlation was at 0.82, very close to the correlation between the variables that account for both medial-lateral and anterior-posterior directions. The average path length calculated for all subjects from the smartphone data was 0.388 mm (SD 0.118 mm), while from the data acquired by the force plate this was 0.802 mm (SD 0.327 mm). In the medial-lateral direction, the average path length for the smartphone application was 0.270 mm (SD 0.111 mm) and for the force plate it was 0.491 mm (SD 0.216 mm). In the anterior-posterior direction, the average path length for the smartphone application was 0.226 mm (SD 0.0878 mm) and for the force plate it was 0.516 mm (SD 0.218 mm). Overall, there was a significant difference in the absolute values of the total path lengths as calculated from the force plate and smartphone application. This difference was expected since the smartphone measured angular deviations that were converted to the smartphone's displacements.