title: Invariant properties between stroke features in handwriting.
abstract: A handwriting pattern is considered as a sequence of ballistic strokes. Replications of a pattern may be generated from a single, higher-level memory representation, acting as a motor program. Therefore, those stroke features which show the most invariant pattern are probably related to the parameters of the higher-level representation, whereas the more noisy features are probably related to the parameters derived at the lower levels (top-down hierarchy). This hierarchy of invariances can be revealed by the signal-to-noise ratio (SNR), the between-parameter correlations, and the between-condition correlations. Similarly, at the higher level a sequence of strokes may act as a unit from which individual strokes are derived (sequence hierarchy). This hierarchy of invariances can be revealed by the between-stroke correlation, which forms a weaker criterion than rescalability, which has been rejected mostly. Previous research showed that vertical stroke size has higher SNRs and higher between-condition correlations than stroke duration or peak force, whereas the latter two features were also negatively correlated. This suggested that vertical stroke size is a higher-level parameter than the other two. The present research largely confirmed this top-down hierarchy and even for upstrokes and downstrokes separately. Downstrokes were more invariant than upstrokes in terms of vertical stroke size. However, contrary to the vertical stroke size, the horizontal stroke size was not invariant. Both vertical and horizontal sizes showed substantial between-stroke correlations. In contrast, the stroke durations did not show any between-stroke correlations. This suggests that stroke segmentation is reliable in spite of the discrete sampling of the handwriting movements.
authors: Nijmegen Institute for Cognition and Information (NICI), University of Nijmegen, The Netherlands.
authors: H L
authors: HL
authors: Teulings
authors: L R
authors: LR
authors: Schomaker
mesh_terms: D000328:Adult; D001288:Attention; D006236:Handwriting; D006801:Humans; D008297:Male; D009949:Orientation; D011597:Psychomotor Performance; D011930:Reaction Time