## 3 Results  
### Results of the Subjective Evaluations  
In order to analyze the relevance of the properties (descriptors) to the evaluation process, and to understand the evaluability of descriptor \"overall\" softness (subjective parameter--perceptive softness), after the experiment (fabric evaluation) the hand-feel panel was asked to compare the ease in assessing each property in a binary evaluation compared to each other. A summary table was created to evaluate the result (see Table 2). The table summarizes the results according to the binary principle, if the descriptor is rated as easier to assessable, it gets 1 point (score), if it is rated as difficult, it gets 0 points. If the evaluation among the experts is ambiguous, then the descriptor is evaluated with half a point (score of 0.5). The points are summed, and this determines the ranking.  
The summary shows that the easiest to assess is the fabric drape, as evidenced by the results' standard deviation. Next in rank is the general descriptor's overall softness. In addition, the experimental results show a high correlation between descriptor ratings.  
A standard deviation of maximally \(\pm 10\%\) was targeted. Figures 4 and 5 show that this target was reached for most properties. Larger disagreements were found on certain evaluated fabrics and in the description words. Further, the obtained results show similar  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Descriptor**} & \multicolumn{2}{c}{**Over-All**} & \multirow{2}{*}{**Smooth/Rough**} & \multirow{2}{*}{**Drapey/Stiff**} & \multirow{2}{*}{**Waxy/Dry**} & \multirow{2}{*}{**Evaluation**} \\  & & & & & \\ \hline over-all & & 0.5 & 0 & 1 & 1.5 \\ softness & & & 0.5 & 0 & 1 \\ \hline smooth/rough & 0.5 & & 0.5 & 0 & 1 \\ \hline drapey/stiff & 1 & 0.5 & & 1 & 2.5 \\ \hline waxy/dry & 0 & 1 & 0 & & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Binary evaluation of descriptors.  
t trends in all investigated properties. The Pearson correlation between all the parameters is higher than 0.9. This means, for this type of fabric, perceived flexibility and surface smoothness cannot be considered independent properties. The evaluation can, in this case, be abbreviated to one parameter. Therefore, in the approach of the method, a general evaluation (overall softness) of the fabric can be made in future evaluations. Nevertheless, in further analysis, each parameter will be discussed in relation to instrumental parameters with similar physical action.  
Figure 4: Average results and SD for each knitted fabric and each property.  
Figure 5: Average results and SD for each woven fabric and each property.  
For the knitted fabrics, the group average shows a significant difference between cotton and fabrics made of wood-based fibers. The cotton/lyocell blended fabric K4 lays in between. Among the wood-based group fabrics, the differences are in the trend. Other fabrics differ in the trend, showing higher scores for the modal-based fabrics K2 and K5, followed by the viscose and lyocell K1 and K3. Having the lyocell/cotton fabric between 100% cotton and 100% wood-based confirms the trend. The modal (micro) fabrics R2k and K6 excel significantly among the wood-based group.  
Woven fabrics showed less differentiation and more variation in the results than the knitted, whereas similar trends were observed. The group average shows a significant difference between the modal (micro) woven fabric (W1, R2w) and the 100% cotton fabrics (W2, R1w). The other fabrics made of wood-based fibers were felt by the group as more similar and could only be differentiated in trend.