# Detection of Personality Traits Using Handwriting and Deep Learning
## 2 Related Work
### Personality Traits Determined from Handwriting and Applications  
Even though there is no consensus among psychology specialists, there are numerous studies and results that demonstrate the connection between handwriting and a series of personality traits [1; 14].  
The literature surrounding handwriting analysis as an instrument of detecting personality traits has evolved significantly in recent years, reflecting a growing interest in the intersection of psychology and graphology. The foundational work by [PERSON] et al. [2] suggests that handwriting analysis is not merely an art but a scientific process that can reveal physiological and psychological insights, particularly in children. Their study correlates clinical diagnoses with graphological analysis, utilizing tools such as the Children's Personality Questionnaire to interpret personality dimensions through handwriting. This early work underscores the potential of handwriting analysis to discern personality traits, setting a precedent for future inquiries into the field.  
Building on this foundation, [PERSON] [15] explores the realm of online communication, examining how linguistic features in digital texts can be used to infer personality traits. His research delves into various platforms to assess the stability of personality traits across different textual samples. This inquiry expands the traditional boundaries of handwriting analysis to include digital expressions of personality, suggesting that the principles of graphology may extend into the analysis of online language, thereby enriching our understanding of personality detection in contemporary contexts.  
Furthering the discourse, [PERSON] and [PERSON] [16] provide a historical perspective on handwriting analysis within psychiatric settings. Their investigation into letters written by psychiatric patients reveals significant insights into cognitive and motor disruptions associated with various psychological disorders. By highlighting the historical underpinnings of handwriting as a diagnostic tool, they illuminate the complexities of graphology, while also acknowledging its controversial status in modern scholarship. This historical analysis not only reinforces the notion that handwriting can reflect mental states but also calls for a reevaluation of its relevance in contemporary psychological assessments.  
In a more recent contribution, [PERSON] and [PERSON] [17] introduce a formalized, computer-aided approach to handwriting psychology through their HSDetect system. This innovative methodology combines manual evaluation by experts with algorithmic calculations of psychological traits based on handwriting signs. By creating a structured database linking handwriting characteristics to psychological assessments, they enhance the reliability and validity of handwriting analysis in psychological contexts. This integration of technology into handwriting analysis signifies a pivotal shift towards more systematic and empirical methodologies in the field.  
In [3], job compatibility can be identified from handwriting analysis with personality recognition. Candidates' skills like creativity, activeness, leadership, and work dedication are recognized. In [8], the handwriting analysis with machine learning classification is used for analyzing financial behavior. It shows where the individual is a risk seeker, risk-tolerant, or risk-averse.