Graduate Students
Bassma Ghali
PhD Candidate
Institute of Biomaterials and Biomedical Engineering
University of Toronto
Advisor: Dr. Tom Chau
E-mail: bassma[dot]ghali[at]utoronto[dot]ca
Education & Training
Bassma Ghali received her B.Eng. degree in Computer Engineering at Ryerson University and M.A.Sc. degree in Electrical and Computer Engineering at McMaster University. After getting her M.A.Sc. degree, she gained industry experience by working as a system engineer in Honeywell and Aversan Inc. She chose to work on biomedical engineering projects for her undergraduate and master theses. She has experience in modeling and simulation of soft tissues using Finite Element Method. Also, she had gained experience in building devices and developing algorithms to create a handy mouse for the paralyzed.
Research Title
Biometric authentication using handwriting biomechanics: a focus on grip kinetics
Research Abstract
Signature authentication has had a great attention in the field of biometrics since it is a traditional method to personal verification. Most of the work available in the literature use kinetic (e.g. axial and normal forces), kinematic (e.g., position, velocity, acceleration, inclination angle) and spatiotemporal features (e.g., stroke durations, stroke length, in-air time) for the signature authentication and have ignored the writer’s biomechanics. Therefore, Bassma’s project studies the grip patterns that people use when writing in order to use these features to identify a person’s identity. She is proposing to use the biomechanics of handwriting for signature authentication by using a special instrumented pen while writing the signature on a digitizing tablet. This pen measures how hard you press on the page. It also measures how you hold the pen. This information will help to describe the uniqueness of each person’s writing pattern and be able to identify an authentic signature from a forged signature. This research could lead to the development of a new device that will recognize signatures and be used as a new anti-fraud tool that can improve security and privacy.
Funding
NSERC CGSD3
