Project Description
81 subjects provided handwriting samples done on two different surfaces – on a Wacom graphic tablet and on ordinary paper. The differences were compared to each other in two steps.
In the first step three writing patterns on a graphic table were analyzed: normal, accurate and quick. Every subject wrote the same text three times which had been analyzed by CSWin software with regard to several variables: path, speed, pressure, number of touches and some others. These different samples were compared to each other to find out whether the writing patterns influenced the handwriting signs. Different writing patterns showed significant difference between them in regard to speed, time, touches and related signs. Other signs like pressure or path were not influenced by the writing pattern (they remained the same). Comparing subjects to each other it could be proven who was quicker in normal writing remained also quicker in slow writing.
In a second step the results received in the first step were compared to the results of handwritings on ordinary paper which was done by professional graphologists. They evaluated the same handwriting signs as CSWin and some additional. The correlation between the CSWin results and the manual results were statistically significant practically for all involved handwriting signs.
Results
- Different writing patterns showed significant difference between them in regard to speed and related signs. Other signs like pressure were not influenced by the writing pattern (they remained the same). Performing the comparison of subjects to each other as to who was quicker at normal writing remained quicker at slow and accurate writing there was no significant difference found.
Conclusion: Different conditions (writing patterns) do not influence the writing. - The evaluation of handwriting signs done by CSWin statistically does not differ from the evaluation done manually by graphologists.
Conclusion: Graphological approach that estimates certain handwriting signs indirectly is acceptable and objective – does not differ from direct evaluations done by CSWin.
Project Team
Boris Peterka, ZHAW Zurich University of Applied Sciences, Switzerland
Dr. Marie Anne Nauer, IHS Institute for Handwriting Sciences, Zurich, Switzerland
Dr. Yury Chernov, IHS Institute for Handwriting Sciences, Zurich, Switzerland