Personal authentication analysis using finger-vein patterns in patients with connective tissue diseases - Possible association with vascular disease and seasonal change

• Kono, Miyuki

• Miura, Naoto

• Fujii, Takao

• Ohmura, Koichiro

• Yoshifuji, Hajime

• Yukawa, Naoichiro

• Imura, Yoshitaka

• Nakashima, Ran

• Ikeda, Takaharu

• Umemura, Shinichiro

• Miyatake, Takafumi

• Mimori, Tsuneyo

Abstract

Objective: To examine how connective tissue diseases affect finger-vein pattern authentication. Methods: The finger-vein patterns of 68 patients with connective tissue diseases and 24 healthy volunteers were acquired. Captured as CCD (charge-coupled device) images by transmitting near-infrared light through fingers, they were followed up in once in each season for one year. The similarity of the follow-up patterns and the initial one was evaluated in terms of their normalized cross-correlation C. Results: The mean C values calculated for patients tended to be lower than those calculated for healthy volunteers. In midwinter (February in Japan) they showed statistically significant reduction both as compared with patients in other seasons and as compared with season-matched healthy controls, whereas the values calculated for healthy controls showed no significant seasonal changes. Values calculated for patients with systemic sclerosis (SSc) or mixed connective tissue disease (MCTD) showed major reductions in November and, especially, February. Patients with rheumatoid arthritis (RA) and patients with dermatomyositis or polymyositis (DM/PM) did not show statistically significant seasonal changes in C values. Conclusions: Finger-vein patterns can be used throughout the year to identify patients with connective tissue diseases, but some attention is needed for patients with advanced disease such as SSc.

Journal

• PLOS ONE

  PLOS ONE 10 (12), 2015-12-01

  Public Library of Science

Details

• CRID: 1050845760763119488
• NII Article ID: 120005763405
• ISSN: 19326203
• HANDLE: 2433/214514
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • CiNii Articles