Analysis of Gender Differences in Online Handwriting Signals for Enhancing e-Health and e-Security Applications

Abstract Handwriting is a complex perceptual–motor skill that mastered around the age of 8. Although its computerized analysis has been utilized in many biometric and digital health applications, possible effect gender frequently neglected. The aim this paper to analyze different online handwritten tasks performed by intact subjects explore differences commonly used temporal, kinematic, dynamic features. were explored BIOSECUR-ID database. We have identified significant difference on-surface/in-air time genuine skilled forgery signatures, on-surface cursive letters numbers, pressure, speed, acceleration text written capital letters. Our findings accent need consider as an important confounding factor studies dealing with handwriting signal processing.