# Evaluation of BLE Star Network for Wireless Wearable Prosthesis/Orthosis Controller +
## 4 Results
### Latency  
For a given configuration, latency seemed to grow proportionally with he connection interval. Thus, to evaluate if we could combine latency measurements across the different configurations, each measurement was normalized by dividing by its respective connection interval. This normalization converted the units of the measured latencies from milliseconds to multiples of the connection interval, potentially simplifying the relationship between connection interval and latency. The results of the Kolmogorov-Smirnoff test showed that the normalized latency data were not normally distributed. [PERSON]'s test was applied to both sets of normalized latency measurements separately, comparing the 18 conditions (6 connection intervals by 3 event lengths). There was no statistically significant difference detected in the latencies between the application of the step and its detection in the ADC data on the peripheral (\(p\) = 0.068). The results of [PERSON]'s test when applied to the latencies between application of the step and detection in the received BLE data on the central node found a statistically significant difference (\(p\) = 6.65 \(\times\) 10\({}^{-5}\)). [PERSON]'s post hoc test showed that, of the 153 unique \(p\)-values, only 6 were statistically significant, as shown in Table 4. Since the vast majority of normalized latencies did not indicate statistically significant differences between conditions, only normalized latencies were further considered in this work. Figure 6 shows histograms of the normalized latency measurements, aggregating the results from all the combinations of connection interval and event length. When looking at the latency measured between the step input and its detection on the peripheral node, the data looked to be uniformly random over the range from just above 0 to just above 1 of the connection interval (mean \(\pm\) std. dev. of 0.54 \(\pm\) 0.27 connection intervals). The data for the \begin{table}
\begin{tabular}{c c c} \hline \hline
**Combination \#1** & **Combination \#2** & \\
**(Connection Interval,** & **(Connection Interval,** & **(Connection Interval,** & **\(p\)-Value** \\ Event Length) & **Event Length)** & \\ \hline (10 ms, 2500 \(\mu\)s) & (50 ms, 2500 \(\mu\)s) & 0.022 \\ (10 ms, 2500 \(\mu\)s) & (100 ms, 5000 \(\mu\)s) & 0.001 \\ (10 ms, 2500 \(\mu\)s) & (40 ms, 7500 \(\mu\)s) & 0.009 \\ (10 ms, 2500 \(\mu\)s) & (100 ms, 7500 \(\mu\)s) & 0.001 \\ (10 ms, 5000 \(\mu\)s) & (100 ms, 5000 \(\mu\)s) & 0.016 \\ (20 ms, 5000 \(\mu\)s) & (100 ms, 5000 \(\mu\)s) & 0.034 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistically significant combinations of second latencies (from step input on the peripheral to detection on the central). \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{ \begin{tabular}{c} **Connection** \\ **Interval 1 (ms)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Connection** \\ **Interval 2 (ms)** \\ \end{tabular}  } & \multicolumn{4}{c}{ \begin{tabular}{c} **Average Current:** \\ **\(p\)-Value (Significant) for:** \\ \end{tabular}  } & \multicolumn{4}{c}{ \begin{tabular}{c} **Maximum Current:** \\ **\(p\)-Value (Significant) for:** \\ \end{tabular}  } \\ \cline{2-7}  & & \begin{tabular}{c} **Event Length** \\ **2500 \(\mu\)s** \\ \end{tabular}  & \begin{tabular}{c} **Event Length** \\ **5000 \(\mu\)s** \\ \end{tabular}  & \begin{tabular}{c} **Event Length** \\ **7500 \(\mu\)s** \\ \end{tabular}  & \begin{tabular}{c} **Event Length** \\ **2500 \(\mu\)s** \\ \end{tabular}  & \ \begin{tabular}{c} **Event Length** \\ **5000 \(\mu\)s** \\ \end{tabular}  & \begin{tabular}{c} **Event Length** \\ **7500 \(\mu\)s** \\ \end{tabular}  \\ \hline \multirow{4}{*}{20} & 30 & 0.750 & 0.819 & 0.819 & 0.900 & 0.090 & 0.001 (\({}^{\circ}\)) \\ \cline{2-7}  & 40 & 0.181 & 0.005 (\({}^{\circ}\)) & 0.160 & 0.009 (\({}^{\circ}\)) & 0.001 (\({}^{\circ  
second latency measurement (from step input at the peripheral's ADC to step detected on the central node) show a triangle-like distribution with a mean \(\pm\) std. dev.