Researchers from Ben-Gurion University of the Negev and Tel Aviv University have developed a smartwatch application that could verify handwritten signatures by observing wrist movements during the signing process, thereby detecting forged ones.
According to the scientists, the software utilizes a motion sensor that is already installed on most wristband devices used today. The information, which was compiled from accelerometer and gyroscope sensors, could detect changes in rotational motion and orientation, and could train a machine learning algorithm to differentiate genuine signatures from forged ones.
To carry out the study, the researchers asked 66 students from Tel Aviv to record 15 samples of their genuine signature on a tablet using a digital pen while wearing a smartwatch on the writing hand. Each student was then given the chance to study other people's genuine signature and was asked to forge them.
"We based our hypothesis on the assumption that people adopt a specific signing pattern that is unique and very difficult for others to imitate, and that this uniqueness can be captured adequately using the motion sensors of a hand-worn device," Ben Nassi, a graduate student from Ben-Gurion University's department of software and information systems engineering, said.
So far, Nassi claimed that results for both random and skilled forgery tests have been encouraging and the system has been able to distinguish the forged and authentic ones with "high degree of accuracy."
Online signature verification technologies have, up to date, relied on dedicated digital devices like tablets or digital pens to capture, analyze and verify signatures. The team claimed that its current approach is unique, although it noted that there are other recent studies that use other types of motion data to verify authenticity.
"Using a wrist-worn device or fitness tracker provides more comprehensive data than other wearable devices, since it measures the gestures of a user's arm, hand and all fingers rather than just a single finger or the forearm," he added.