Handwriting Markers for the Onset of Alzheimer's Disease.

INTRODUCTION: Alzheimer's disease has an impact on handwriting (AD). Numerous researchers reported that fact. Therefore, examining handwriting characteristics could be a useful way to screen for AD. The aim of the article is to present the reliability and effectiveness of the AD-HS tool. METHOD: Most of the existing studies examine either linguistic manifestations of writing or certain motor functions. However, handwriting is a complex of cognitive and motor activities. Since the influence of AD on handwriting is individual, it is important to analyze the complete set of handwriting features. The AD-HS instrument is based on this principle. Validation of the AD-HS instrument for revealing cognitive impairment in AD-diagnosed persons in comparison to the control group. The study is based on the evaluation of free handwritten texts. AD-HS includes 40 handwriting and 2 linguistic features of handwritten texts. It is based on the standard protocol for handwriting analysis. The cumulative evaluation of all features builds a quantitative AD-Indicator (ADI) as a marker of possible AD conditions. The analyzed experiment includes 53 AD-diagnosed persons and a control group of 192 handwriting specimens from the existing database. RESULT: AD-HS shows a distinct difference in evaluated ADI for the participants (the mean value equals 0.49) and the control group (the mean value equals 0.28). CONCLUSION: The handwriting marker of AD could be an effective supplement instrument for earlier screening. It is also useful when traditional biomarkers and neurological tests could not be applied. AD-HS can accompany therapy as an indication of its effect on a person.

Formalized Computer-Aided Handwriting Psychology: Validation and Integration into Psychological Assessment.

In contrast to traditional researches that involve a manual, non-quantitative, and subjective way of performing handwriting analysis, in the current research, a special computer-aided method of revised handwriting analysis is used. It includes the detection of personality traits via manual quantitative registration of handwriting signs and their automated quantitative evaluation. This method is based on a mathematical-statistical model that integrates multiple international publications on the evaluation of handwriting signs. The first aim is the validation of the revised method against the 16 Personality Factor Questionnaire Revised (16PF-R), which is performed as a self-report personality test by test persons and was developed and researched empirically by Raymond B. Cattell et al. A second aim is the development of an integrated model for assessment including handwriting analysis: when both methods come to the same result on a certain scale, then the construct can be accepted with higher reliability; in contrast, when results are contradictory, they should be regarded as a limitation of each method and raise awareness in the researchers, as these contradictions are a precious source of additional information regarding the complexity, ambiguity, and context specificity of personality traits.