# Utilization of a Mobile Application for Motor Skill Evaluation in Children +
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Path Type** & **Statistics** & **1 st Grade** & **2 nd Grade** & **3 rd Grade** & **4 th Grade** & **5 th Grade** & **6 th Grade** \\ \hline \multirow{4}{*}{Straight line} & Mean & 0.88 & 0.7 & 0.55 & 0.54 & 0.47 & 0.38 \\  & Median & 0.88 & 0.71 & 0.54 & 0.54 & 0.47 & 0.38 \\  & STD & 0.22 & 0.22 & 0.15 & 0.15 & 0.16 & 0.12 \\  & IQR & 0.3 & 0.24 & 0.14 & 0.23 & 0.21 & 0.19 \\ \hline \multirow{4}{*}{Parabola curve} & Mean & 0.94 & 0.74 & 0.63 & 0.6 & 0.54 & 0.45 \\  & Median & 0.93 & 0.71 & 0.62 & 0.57 & 0.52 & 0.44 \\  & STD & 0.22 & 0.22 & 0.18 & 0.17 & 0.16 & 0.14 \\  & IQR & 0.36 & 0.35 & 0.23 & 0.21 & 0.19 & 0.22 \\ \hline \multirow{4}{*}{Zig-zag polygonal line} & Mean & 1.03 & 0.83 & 0.72 & 0.7 & 0.63 & 0.54 \\  & Median & 1.01 & 0.86 & 0.71 & 0.7 & 0.62 & 0.53 \\ \cline{1-1}  & STD & 0.22 & 0.21 & 0.25 & 0.2 & 0.17 & 0.15 \\ \cline{1-1}  & IQR & 0.33 & 0.32 & 0.27 & 0.22 & 0.25 & 0.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Reference thresholds as a function of the path type, considering all modes. STD: standard deviation; IQR: interquartile range. guaranteeing that the hand used by children for the required tasks was the same hand that they were used in their day-to-day life, especially in the youngest cases. Thanks to the registered data, this app allows users to quantify the fine motor coordination of a child based on measuring the error in the execution of the child's movement, which has not been addressed by previous works that are traditionally more focused on execution time [16; 21; 22]. In addition, the use of external tools for the study of performance in precision activities (such as a pencil or a pen in a manual recording, or a pen or a mouse in a computer recording) can lead to a bias when assessing the movement quality, since the information obtained will be more related to the specific manipulation of the object than to the child's basal visual-motor coordination. In the case of the MABC-2 tests, used as a screening tool in this study, the records related to trace precision only quantify the number of errors made by the child when leaving the established path without reflecting the magnitude of that error, i.e., a child who deviates 0.1 cm from the path and a child who deviates 1 cm would obtain the same record at that point, which is one error for both cases. For this reason, the data presented here must be taken into account as a precise, objective and quantifiable measurement of movement quality in children. To our knowledge, this is the first study exploring a mobile app as a resource for assessing fine motor development in children in primary education. Some authors suggest that children may be developing new fine motor skills due to the use of touch screen devices such as phones or tablets [18]. Therefore, the use of new technologies in education and rehabilitation might be increasingly necessary. In the infant and primary school stages, the need for an educational reinforcement that allows an improvement in the learning of fine motor skills is frequent. Thus, an appropriate early intervention with the support of informatics tools could facilitate not only the detection of some common problems but could also contribute to the follow-up of these children during their rehabilitation process. Although our preliminary data were limited due to the small sample size, we consider that the results might provide an incentive for multidisciplinary investigation in this area. These studies should be aimed not only at establishing that mobile applications are useful as support tools during the rehabilitation of children with difficulties in fine motor function, but also at investigating precise reference values that are present in children with developmental coordination disorders in order to implement early problem detection.