Survey of the Stability of Uniqueness of Muscle Synergy Patterns in Handwritten Signature over Time

Authors

• Arsalan Asemi ¹
• Arsalan Asemi ¹
• Fereidoun Nowshiravan Rahatabad ²
• Hamid Azadeh ³

1. Department of Biomedical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2. Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
3. Department of Physical Therapy, School of Rehabilitation Sciences, Isfahan University of Medical Sciences, Isfahan, Iran

Abstract

Biometric characteristics of the human body can play a decisive role in the accuracy of automatic signature verification systems due to their stability over time and resistance to variability in different conditions. In this study, the accuracy of an automatic handwritten signature verification system is checked for nine months. In this system, the electromyography (EMG) signals from the hand muscles of people during signing are recorded at different times up to nine months, and after the pre-processing of the signals, muscle synergy patterns are extracted by the non-negative matrix factorization (NMF) method. Finally, the patterns extracted by the SVM classifier are classified into two classes: genuine and forgery signatures.

Keywords

• EMG
• Handwritten Signature
• Muscle Synergy