# Improving Human Activity Monitoring by Imputation of Missing Sensory Data: Experimental Study
## 3 Results
### Data Classification
#### 3.2.2 Normalized Data  
Considering the accelerometer data, the results obtained with non-imputed and normalized data are reported in the confusion matrix presented in Table 12. The implemented method reported an accuracy of 85.89%, a precision of 86.21%, a recall value of 85.89%, and an F1 score of 86.05%. Considering the accelerometer and magnetometer sensors' data, the results obtained with non-imputed and normalized data are reported in the confusion matrix presented in Table 13. The implemented method reported an accuracy of 86.49%, a precision of 86.75%, a recall value of 86.49%, and an F1 score of 86.62%. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Predicted Class**} \\ \hline  & \multicolumn{2}{c}{**Walking Downstairs**} & \multicolumn{2}{c}{**Walking Upstairs**} & \multicolumn{2}{c}{**Running**} & \multicolumn{2}{c}{**Standing**} & \multicolumn{2}{c}{**Walking**} \\ \hline  & Walking Downstairs & 0 & 0 & 0 & 2000 & 0 \\ \cline{2-6} Actual Class & Walking Upstairs & 0 & 0 & 0 & 2000 & 0 \\ \cline{2-6} Actual Class & Running & 0 & 0 & 5 & 1995 & 0 \\ \cline{2-6}  & Standing & 0 & 0 & 0 & 2000 & 0 \\ \cline{2-6}  & Walking & 0 & 0 & 0 & 1995 & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Confusion matrix related to non-normalized and imputed data from the accelerometer and magnetometer sensors. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Predicted Class**} \\ \hline  & \multicolumn{2}{c}{**Walking Downstairs**} & \multicolumn{2}{c}{**Walking Upstairs**} & \multicolumn{2}{c}{**Running**} & \multicolumn{2}{c}{**Standing**} & \multicolumn{2}{c}{**Walking**} \\ \hline  & Walking Downstairs & 0 & 0 & 0 & 2000 \\ \cline{2-6} Actual Class & Walking Upstairs & 0 & 19 & 0 & 0 & 1981 \\ \cline{2-6} Actual Class & Running & 0 & 0 & 0 & 0 & 2000 \\ \cline{2-6}  & Standing & 0 & 0 & 0 & 0 & 2000 \\ \cline{2-6}  & Walking & 0 & 0 & 0 & 0 & 2000 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Confusion matrix related to non-normalized and imputed data from the accelerometer, magnetometer, and gyroscope sensors. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Predicted Class**} \\ \hline  & \multicolumn{2}{c}{**Walking Downstairs**} & \multicolumn{2}{c}{**Walking Upstairs**} & \multicolumn{2}{c}{**Running**} & \multicolumn{2}{c}{**Standing**} & \multicolumn{2}{c}{**Walking**} \\ \cline{2-6} Actual Class & Walking Upstairs & 1334 & 510 & 9 & 4 & 143 \\ \cline{2-6} Actual Class & Walking Upstairs & 230 & 1639 & 4 & 14 & 113 \\ \cline{2-6} Actual Class & Running & 20 & 34 & 1909 & 9 & 28 \\ \cline{2-6}  & Standing & 0 & 11 & 0 & 1985 & 4 \\ \cline{2-6}  & Walking & 109 & 128 & 9 & 32 & 1722 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Confusion matrix related to normalized and non-imputed data from the accelerometer sensor. Considering the accelerometer, magnetometer, and gyroscope sensors' data, the results obtained with non-imputed and normalized data are reported in the confusion matrix presented in Table 14. The implemented method reported an accuracy of 89.52%, a precision of 89.74%, a recall value of 89.51%, and an F1 score of 89.62%. Considering the accelerometer data, the results obtained with imputed and normalized data are reported in the confusion matrix presented in Table 15. The implemented method reported an accuracy of 94.56%, a recall value of 94.56%, and an F1 score of 94.59%. Considering the accelerometer and magnetometer sensors' data, the results obtained with imputed and normalized data are reported in the confusion matrix presented in Table 16. The implemented method reported an accuracy of 98.24%, a precision of 98.28%, a recall value of 98.24%, and an F1 score of 98.26%.