## Appendix A \begin{table}
\begin{tabular}{c c c} \hline \hline
**Analysis Parameter** & **Applied Setting** & **Rationale** \\ \hline Face model & Children & In accordance with subjects’ age \\ \hline Calibration & Continuous calibration & \begin{tabular}{c} Aims to correct for person-specific biases in \\ facial expressions, thus not requiring an initial \\ input of a neutral face of each subject \\ \end{tabular} \\ \hline Classification & Smoothen classification & \begin{tabular}{c} Raw classification data are smoothened in \\ relation to between-frame time gap (default \\ setting) \\ \end{tabular} \\ \hline Image rotation & No & All faces were recorded in upright position \\ \hline Video sample rate & Every frame & No recorded frame to be skipped \\ \hline Contempt & \begin{tabular}{c} Treat contempt as an \\ emotional state \\ \end{tabular} & \begin{tabular}{c} To gain intensity values for “contempt” \\ \end{tabular} \\ \hline \begin{tabular}{c} Preset for face-finding \\ function \\ \end{tabular} & Find all faces (slow) & \begin{tabular}{c} The most robust setting in terms of size of \\ potential target face on the frame (minimum \\ face fraction = 0.08) \\ \end{tabular} \\ \hline \begin{tabular}{c} Preset for face-modeling \\ function \\ \end{tabular} & Maximum accuracy (slow) & \begin{tabular}{c} Robust setting in terms of the maximum \\ number of iterations per frame to find face (12) \\ \end{tabular} \\ \hline Engine & Use deep face engine & \
\begin{tabular}{c} Slower but more accurate analysis which \\ attempts to model the face even from partial \\ information \\ \end{tabular} \\ \hline Maximum face model error & 0.6 &
\begin{tabular}{c} Measure of error for estimating if face model is \\ valid \\ \end{tabular} \\ \hline Size of interest, maximum & \multirow{2}{*}{\(1\)} & Maximum value, allows the face surface to be \\ face fraction & & the same as the entire image \\ \hline Size of interest, face size & \multirow{2}{*}{\(1.1\)} & The default factor value for increasing face size \\ scaling factor & & within minimum and maximum, for the \\ analysis & & analysis \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Relevant FR8 analysis settings and their rationale. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Magnitude Range** & **Neutral** & **Happy** & **Sad** & **Angry** & **Surprised** & **Scared** & **Disgusted** & **Contempt** \\ \hline diff = \(-1\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-1\) \(<\) diff \(\leq-0.9\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.9\) \(<\) diff \(\leq-0.8\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.8\) \(<\) diff \(\leq-0.7\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.7\) \(<\) diff \(\leq-0.6\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.6\) \(<\) diff \(\leq-0.5\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.5\) \(<\) diff \(\leq-0.4\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.4\) \(<\) diff \(\leq-0.3\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.3\) \(<\) diff \(\leq-0.2\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(-0.2\) \(<\) diff \(<-0.1\) & 0 & 0 & 0 & 0 & 168 & 0 & 0 \\ \hline \(-0.1\) \(<\) diff \(\leq 0\) & 5638 & 7493 & 5920 & 10,405 & 9736 & 397 & 9593 & 9680 \\ \hline \(0<\) diff \(\leq 0.1\) & 11,661 & 511 & 9113 & 15 & 5661 & 11,322 & 1676 & 1 \\ \hline \(0.1\) \(<\) diff \(\leq 0.2\) & 0 & 0 & 0 & 0 & 242 & 0 & 0 & 0 \\ \hline \(0.2\) \(<\) diff \(\leq 0.3\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(0.3\) \(<\) diff \(\leq 0.4\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \(0.4\) \(<\) diff \(\leq 0.5\) & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Example distributions of test\({}_{1}\)–test\({}_{2}\) differences, with corresponding means, separately for the 8 emotions: subject #2 (ASD). Test\({}_{2}\)–test\({}_{3}\) data for subject #2 were identical. Frequency distributions include only data points with intensity values assigned in both test\({}_{1}\) and test\({}_{2}\) (therefore numerical difference could be calculated); however, matching data points with zero difference were omitted.