Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/45495
Title: Early diagnosis of neurodegenerative diseases by handwritten signature analysis
Authors: Pirlo, Giuseppe
Diaz, Moises 
Ferrer, Miguel Angel 
Impedovo, Donato
Occhionero, Fabrizio
Zurlo, Urbano
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Handwritten signature
Alzheimer Pre-diagnosis system
Pattern Recognition
Issue Date: 2015
Journal: Lecture Notes in Computer Science 
Conference: 18th International Conference on Image Analysis and Processing (ICIAP) 
18th International Conference on Image Analysis and Processing, ICIAP 2015 BioFor, CTMR, RHEUMA, ISCA, MADiMa, SBMI, and QoEM 
Abstract: Handwritten signatures are generally considered a powerful biometric traits for personal verification. Recently, handwritten signatures have been also investigated for early diagnosis of neurodegenerative diseases. This paper presents a new approach for early diagnosis of neurodegenerative diseases by the analysis of handwritten dynamic signatures. For the purpose, the sigma-lognormal model was considered and dynamic parameters are extracted for signatures. Based on these parameters, the health condition of the signer is analysed in terms of Alzheimer disease. The approach is cheap and effective, therefore it can be considered as a very promising direction for further research.
URI: http://hdl.handle.net/10553/45495
ISBN: 9783319232218
ISSN: 0302-9743
DOI: 10.1007/978-3-319-23222-5_36
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 9281, p. 290-297
Appears in Collections:Actas de congresos
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