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Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
05:58

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

Using automated comparisons to quantify handwriting individuality.

Christopher P Saunders1, Linda J Davis, JoAnn Buscaglia

  • 1Document Forensics Laboratory (MS 1G8), George Mason University, 4400 University Drive, Fairfax, VA 22030, USA. csaunde6@gmu.edu

Journal of Forensic Sciences
|March 12, 2011
PubMed
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Forensic handwriting analysis relies on unique writing profiles. This study proposes a statistical method to estimate the probability of two writers having indistinguishable handwriting, aiding in empirical validation.

Area of Science:

  • Forensic Science
  • Biometrics
  • Statistical Analysis

Background:

  • The uniqueness of handwriting profiles is a foundational assumption in forensic document examination.
  • Empirical validation of this uniqueness is challenging due to the impossibility of testing every individual's writing sample.

Purpose of the Study:

  • To propose a statistical strategy for bounding the probability of random matches between indistinguishable handwriting profiles.
  • To demonstrate the application of this strategy using an automated handwriting comparison procedure.

Main Methods:

  • Utilized a database of handwriting samples.
  • Employed an automated comparison procedure based on Pearson's chi-squared statistic.
  • Analyzed frequency distributions of letter shapes to quantify writing profile characteristics.

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Last Updated: Jun 3, 2026

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
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Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Na&#239;ve Adolescents at High Risk for Psychosis
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Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis

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Main Results:

  • Developed a method to statistically estimate the upper bound for the probability of two writers having indistinguishable handwriting profiles.
  • Demonstrated the computation of this bound using a convenience sample and an automated comparison system.

Conclusions:

  • The proposed statistical strategy provides a framework for assessing handwriting individuality.
  • This method can inform the design of future empirical studies investigating the uniqueness of handwriting profiles.