## 3 Experimental Results
The confusion matrix obtained after the cross-validation is presented in Figure 9.  
In addition, experimental and benchmarking results are shown in Table 6, Table 7, and Table 8. Finally, the relationship between the LSTM's accuracy and DCT vector size (n) is listed in Table 9 and illustrated with a graph in Figure 10, and evaluation of the experimental and benchmarking results is done at the end. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Metrics/Classes** & **Standing** & **Walking** & **Clapping** & **Lifting** & **Punching** & **Average** \\ \hline TPR & 62.667 & 85.217 & 100.00 & 100.000 & 91.667 & 87.910 \\ \hline TNR & 99.775 & 99.469 & 99.157 & 100.000 & 99.899 & 99.660 \\ \hline PPV & 91.262 & 85.965 & 5.556 & 100.000 & 96.117 & 75.780 \\ \hline NPV & 98.615 & 99.436 & 100.00 & 100.000 & 99.773 & 99.565 \\ \hline FPR & 0.225 & 0.531 & 0.843 & 0.000 & 0.101 & 0.340 \\ \hline FNR & 37.333 & 14.783 & 0.000 & 0.000 & 8.333 & 12.090 \\ \hline FDR & 8.738 & 14.035 & 94.444 & 0.000 & 3.883 & 24.220 \\ \hline FOR & 1.385 & 0.564 & 0.000 & 0.000 & 0.227 & 0.435 \\ \hline ACC & 98.432 & 98.946 & 99.157 & 100.000 & 99.68 & 99.243 \\ \hline F1 & 74.308 & 85.59 & 10.526 & 100.000 & 93.839 & 72.853 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Cross-validation results of LSTM classifier based on the employed performance metrics. Figure 9: Confusion matrix. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Feature Vector** & **Accuracy (\%)** & **F-1 (\%)** & **Precision (\%)** & **Recall (\%)** \\ \hline Dimension reduction with averaging & & & & \\ (Previous Coordinate System) & 65.7 & 73.9 & 78.1 & 67.9 \\ \hline Dimension reduction with averaging & & & & \\ (Proposed Coordinate System) & 85.1 & 65.4 & 68.3 & 71.5 \\ \hline Dimension reduction with HWT & & & & \\ (Previous Coordinate System) & 75.7 & 79.3 & 81.6 & 74.3 \\ \hline Dimension reduction with HWT & & & & \\ (Proposed Coordinate System) & 93.5 & 68.7 & 71.3 & 80.2 \\ \hline Dimension reduction with DCT & & & & \\ (Previous Coordinate System) & 83.1 & 85.4 & 87.6 & 82.7 \\ \hline Dimension reduction with DCT & & & & \\ (Proposed Coordinate System) & 99.2 & 72.9 & 75.8 & 87.9 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Benchmarking of cross-validation results of LSTM classifier with different feature vectors. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Feature vector** & **Accuracy (\%)** & **F-1 (\%)** & **Precision (\%)** & **Recall (\%)** \\ \hline Dimension reduction with averaging & & & \\ (Previous Coordinate System) & 53.8 & 48.1 & 53.7 & 45.3 \\ \hline Dimension reduction with averaging & & & & \\ (Proposed Coordinate System) & 68.1 & 62.9 & 65.2 & 69.0 \\ \hline Dimension reduction with HWT & & & & \\ (Previous Coordinate System) & 57.1 & 56.1 & 59.4 & 55.1 \\ \hline Dimension reduction with HWT & & & & \\ (Proposed Coordinate System) & 72.5 & 63.6 & 66.1 & 71.6 \\ \hline Dimension reduction with DCT & & & & \\ (Previous Coordinate System) & 61.6 & 63.4 & 68.2 & 62.6 \\ \hline Dimension reduction with DCT & & & & \\ (Proposed Coordinate System) & 83.9 & 66.7 & 71.4 & 74.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Benchmarking of experimental results of LSTM classifier with different feature vectors. \begin{table}
\begin{tabular}{c c c} \hline \hline
**DCT** & **Accuracy (\%)** & **Accuracy (\%)** \\ \hline
**Vector Size** & **(Previous Method)** & **(Proposed Method)** \\ \hline
1 & 5.3 & 17.9 \\ \hline
2 & 17.1 & 24.5 \\ \hline
4 & 25.4 & 31.8 \\ \hline
8 & 32.7 & 45.2 \\ \hline
12 & 41.6 & 68.3 \\ \hline
16 & 49.7 & 75.5 \\ \hline
20 & 55.1 & 79.4 \\ \hline
24 & 61.6 & 83.9 \\ \hline
30 & 64.3 & 85.4 \\ \hline
40 & 65.7 & 87.2 \\ \hline
48 & 66.3 & 88.1 \\ \hline
60 & 67.8 & 89.4 \\ \hline
80 & 68.5 & 90.1 \\ \hline
120 & 69.3 & 90.5 \\ \hline
240 & 70.2 & 91.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Benchmarking of accuracies of previous and proposed method in varying DCT vector sizes.