Determining the association between dermatoglyphics and schizophrenia by using fingerprint asymmetry measures

Jen Feng Wang, Chen Liang Lin, Chen Wen Yen, Yung Hsien Chang, Teng Yi Chen, Kuan Pin Su, Mark L. Nagurka

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Early detection and intervention strategies for schizophrenia are receiving increasingly more attention. Dermatoglyphic patterns, such as the degree of asymmetry of the fingerprints, have been hypothesized to be indirect measures for early abnormal developmental processes that can lead to later psychiatric disorders such as schizophrenia. However, previous results have been inconsistent in trying to establish the association between dermatoglyphics and schizophrenia. The goal of this work is to try to resolve this problem by borrowing well-developed techniques from the field of fingerprint matching. Two dermatoglyphic asymmetry measures are proposed that draw on the orientation field of homologous fingers. To test the capability of these measures, fingerprint images were acquired digitally from 40 schizophrenic patients and 51 normal individuals. Based on these images, no statistically significant association between conventional dermatoglyphic asymmetry measures and schizophrenia was found. In contrast, the sample means of the proposed measures consistently identified the patient group as having a higher degree of asymmetry than the control group. These results suggest that the proposed measures are promising for detecting the dermatoglyphic patterns that can differentiate the patient and control groups.

Original languageEnglish
Pages (from-to)601-616
Number of pages16
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Issue number3
StatePublished - 1 May 2008
Externally publishedYes


  • Dermatoglyphic
  • Fingerprint
  • Fluctuating asymmetry
  • Mutual information
  • Ridge count
  • Schizophrenia

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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