## 3 Result
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Phase**} & \multirow{2}{*}{**Regression Statistics**} & \multicolumn{4}{c}{**a\(\omega\)**} & \multicolumn{4}{c}{**aM\({}_{\text{a}}\)**} \\ \cline{3-8}  & & **WS** & **BMI** & **WS \& BMI** & **WS** & **BMI** & **WS \& BMI** \\ \hline \multirow{3}{*}{IC to FF} & Multiple R (p1) & 0.625 & 0.159 & 0.666 & 0.558 & 0.117 & 0.560 \\  & R Square (p1\({}^{\text{2}}\)) & 0.391 & 0.025 & 0.444 & 0.311 & 0.014 & 0.314 \\  & Standard Error (Se1) & 0.822 & 1.040 & 0.786 & 2.253 & 2.695 & 2.251 \\ \hline \multirow{3}{*}{FF to HO} & Multiple R (p2) & 0.830 & 0.199 & 0.837 & 0.246 & 0.154 & 0.277 \\  & R Square (p2\({}^{\text{2}}\)) & 0.689 & 0.039 & 0.700 & 0.060 & 0.024 & 0.077 \\  & Standard Error (Se2) & 0.235 & 0.413 & 0.231 & 1.245 & 1.270 & 1.236 \\ \hline \multirow{3}{*}{HO to TO} & Multiple R (p3) & 0.645 & 0.607 & 0.839 & 0.130 & 0.357 & 0.369 \\  & R Square (p3\({}^{\text{2}}\)) & 0.416 & 0.368 & 0.705 & 0.017 & 0.128 & 0.136 \\ \cline{1-1}  & Standard Error (Se3) & 1.060 & 1.103 & 0.755 & 0.742 & 0.699 & 0.696 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Regression statistic result. Figure 9: The regression of (**a**) average ankle velocity (a\(\omega\)) and (**b**) average ankle torque (aM\({}_{\text{a}}\)) with different critical parameter during HO to TO phase. The standard error (Se) results in Table 4 show that in general, the estimation of aM\({}_{\rm a}\) has higher Se compare to estimation of a\(\omega\) (Se1(aM\({}_{\rm a}\)) = 2.251 \(>\) Se1(a\(\omega\)) = 0.786, Se2(aM\({}_{\rm a}\)) = 1.236 \(>\) Se2(a\(\omega\)) = 0.231, Se3(aM\({}_{\rm a}\)) = 0.696 \(<\) Se3(a\(\omega\)) = 0.755). BMI based estimation resulted in the highest estimated Se for each a\(\omega\) and aM\({}_{\rm a}\). On the other hand, the estimation based on walking speed only shows a smaller standard error, but the error reduced more when the two critical parameters were combined. For instance, during HO to TO, the standard error of a\(\omega\) was 1.060 based on WS only, 1.103 based on BMI only, and 0.755 based on the combination of both. For illustrations of the reduced standard error, see Figures 7-9. The estimations based on both walking speed and BMI show wider coverage in hitting the actual value compare to estimation based on walking speed or BMI only. The results of critical parameter coefficient estimation show that the WS coefficient consistently has the opposite sign between a\(\omega\) and aM\({}_{\rm a}\) estimation for the whole stance phase, similar to the correlation analysis result. BMI coefficient results also show agreement with the correlation analysis result. The \(t\)-test results reveal that all coefficients for a\(\omega\) estimation were significantly not possible to be zero (\(P\)-value \(<\)  
situations to maximize the benefit of using PICAFO [11]. Here, different subjects were represented by BMI, while the walking situations were represented by walking speed. Therefore, a superior control reference parameter is expected to have a high correlation with the BMI and walking speed during the stance phase. The results of the regression analysis revealed that the ankle angular velocity is the preferable control reference parameter rather than ankle torque. The ankle angular velocity has a higher correlation score with BMI and walking speed compared to ankle torque, as shown in Table 3. The overall standard error of ankle angular velocity estimation is lower than the ankle torque estimation, which strengthens the correlation score result. The result of estimation and t-test of the critical parameter coefficient also shows the superiority of ankle angular velocity as control reference parameter where all the critical parameter coefficients were statistically significant not zero as shown in Table 4. However, the presented result cannot conclude the relationship between control reference and critical parameter due to a lack of sufficient participating subjects and regression model testing, which is a limitation of this study.