  Introduction Existing literature about online handwriting analysis to support
pathology diagnosis has taken advantage of in-air trajectories. A similar
situation occurred in biometric security applications where the goal is to
identify or verify an individual using his signature or handwriting. These
studies do not consider the distance of the pen tip to the writing surface.
This is due to the fact that current acquisition devices do not provide height
formation. However, it is quite straightforward to differentiate movements at
two different heights: a) short distance: height lower or equal to 1 cm above a
surface of digitizer, the digitizer provides x and y coordinates. b) long
distance: height exceeding 1 cm, the only information available is a time stamp
that indicates the time that a specific stroke has spent at long distance.
Although short distance has been used in several papers, long distances have
been ignored and will be investigated in this paper. Methods In this paper, we
will analyze a large set of databases (BIOSECURID, EMOTHAW, PaHaW,
Oxygen-Therapy and SALT), which contain a total amount of 663 users and 17951
files. We have specifically studied: a) the percentage of time spent
on-surface, in-air at short distance, and in-air at long distance for different
user profiles (pathological and healthy users) and different tasks; b) The
potential use of these signals to improve classification rates. Results and
conclusions Our experimental results reveal that long-distance movements
represent a very small portion of the total execution time (0.5 % in the case
of signatures and 10.4% for uppercase words of BIOSECUR-ID, which is the
largest database). In addition, significant differences have been found in the
comparison of pathological versus control group for letter l in PaHaW database
(p=0.0157) and crossed pentagons in SALT database (p=0.0122)
