## 3 Materials and Methods
### Data Pre-Processing
#### 3.3.2 Single-Stride and Multi-Stride Gait Feature Modalities
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Gait Feature** & **Gait Feature Description** & **Gait Feature Formula** \\ \hline \multirow{3}{*}{AVM} & Magnitude of the vector of the AP axis for the & \(\sqrt{AP^{2}}\) computed from the acceleration of the AP axis \\  & entire stride & for the entire stride \\ \hline \multirow{3}{*}{VMD} & \multirow{3}{*}{Magnitude of the vector for the double stance} & \(\sqrt{ML^{2}+V^{2}+AP^{2}}\) computed from the acceleration of the three axes for the \(\pm 10\%\) portion surrounding \\  & & the heel strike event \\ \hline \multirow{3}{*}{LVMD} & Magnitude of the vector of the ML axis at the time & \(\sqrt{ML^{2}}\) computed from the acceleration of the ML axis \\  & of a double stance & for the \(\pm 10\%\) portion surrounding the heel strike event \\ \hline \multirow{3}{*}{VVMD} & Magnitude of the vector of the V axis at the time & \(\sqrt{V^{2}}\) computed from the acceleration of the V axis for the \(\pm 10\%\) portion surrounding the heel strike event \\  & & of a double stance & \(\sqrt{AP^{2}}\) computed from the acceleration of the AP axis \\ \hline \multirow{3}{*}{VM30} & Magnitude of the vector for the mid-stance & \(\sqrt{ML^{2}+V^{2}+AP^{2}}\) computed from the acceleration \\  & & of the three axes for the 30\% portion of the gait cycle \\ \hline \multirow{3}{*}{LVM30} & Magnitude of the vector of the ML axis at the time & \(\sqrt{ML^{2}}\) computed from the acceleration of the ML axis \\  & of the mid-stance & for the 30\% portion of the gait cycle \\ \hline \multirow{3}{*}{VVM30} & Magnitude of the vector of the V axis at the time & \(\sqrt{V^{2}}\) computed from the acceleration of the V axis for \\  & a mid-stance & the 30\% portion of the gait cycle \\ \hline \multirow{3}{*}{AVM30} & Magnitude of the vector of the AP axis at the time & \(\sqrt{AP^{2}}\) computed from the acceleration of the AP axis \\  & of a mid-stance & for the 30\% portion of the gait cycle \\ \hline \multirow{3}{*}{LHM} & Magnitude of heel strike of the ML axis & Max (ML) at the heel strike \\ \hline \multirow{3}{*}{LHSD} & Standard deviation of the acceleration of the ML & Std (ML) computed from the acceleration of the ML \\  & axis for the first 10\% portion of the stride & axis for the first 10\% portion of the stride \\ \hline \multirow{3}{*}{VHM} & Magnitude of heel strike of the V axis & Max (V) at the heel strike event \\  & & for the first 10\% portion of the stride \\ \hline \multirow{3}{*}{VHSD} & Standard deviation of the acceleration of the V axis & Std (V) computed from the acceleration of the V axis \\  & for the first 10\% portion of the stride & for the first 10\% portion of the stride \\ \hline \multirow{3}{*}{AHM} & Magnitude of heel strike of the AP axis & Max (AP) at the heel strike event \\  & & for the acceleration of the AP \\ \hline \multirow{3}{*}{AHSD} & Standard deviation of the acceleration of the AP & Std (AP) computed from the acceleration of the AP \\  & axis for the first 10\% portion of the stride & axis for the first 10\% portion of the stride \\ \hline \multirow{3}{*}{ST} & Stride time & Duration of two consecutive heel strike events \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{c c c} \hline \hline
**Label** & **Count** & **Percentage** \\ \hline Good & 3774 & 65\% \\ Irregular & 1995 & 35\% \\ Total & 5769 & 100\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Distribution of class labels of stride samples. classification performance. This led to the experimentation of the multi-stride gait feature modality. For this modality, a larger sliding window width of five samples was used to segment the data, which was equivalent to five strides, with an 80% overlap, as illustrated in Figure 7. The input segment vector had the shape of 40 dimensions as well.