## 2 Materials and Methods
### Sensor Fusion-Based Concept  
The majority of the literature cited in the related work section focuses on a single device or sensor for signature verification. In contrast, we suggest the implementation of a system including three distinct devices. As previously stated, a tablet computer, a smartphone, and a smartwatch have been employed to collect the data. The rationale for this number of devices is the utilization of a greater quantity of sensors, including both integrated and external variants. The objective of such sensor fusion is to achieve better accuracy, stability, reliability, and other desirable properties compared to using a single sensor [38]. This allows us to determine a set of sensors that is most effective at verifying user identity employing handwriting samples. Since the tablet was employed for writing on the screen, we were unable to utilize its integrated camera sensor for tracking AruCo markers. Therefore, an available smartphone model was incorporated into the apparatus. Additionally, the smartphone's available 3.5 mm audio connector was utilized to connect a different model of the piezo sensor from the one attached to the tablet. The aim was to collect pressure data using an additional sensor with distinct characteristics and dimensions, which was placed in different locations beneath the tablet. The devices incorporated in the proposed apparatus can be replaced with other models having comparable features and sensors. Table 2 presents a comprehensive list of the devices utilized in the apparatus along with their respective sensors and the types of data they gather. Figure 3: The S Pen stylus has been enhanced with the integration of a magnet and an ArUco marker, which are securely held in place by holders fabricated using 3D printing technology. In the process of writing with a traditional pen and paper, some biometric data may inadvertently be omitted or remain unrecorded. The vast amount of collected data gathered using our proposed apparatus is specifically aimed at addressing this issue. Regarding online signature verification, each data point collected within the handwritten text contains a multitude of information. For instance, each point can be assigned its corresponding x and y coordinates, timestamp, pressure, velocity, size, and orientation. Moreover, it is possible to obtain the sensor readings from the magnetometer, gyroscope, and accelerometer. Consequently, based on the data for each corresponding point, the specific user's handwriting can be identified. The curvature, thickness, and width of the strokes are determined by the unique characteristics of each user. They are derived from the analysis of many factors such as pressure level, velocity, touch size, stylus tilt, etc. Figure 4 shows an example instance of data collected from a handwriting sample using the proposed apparatus. The information gained in this manner is more data-rich and distinct from those obtained via the more conventional ways of pen and paper writing. By using a tablet computer for writing instead of traditional paper, we are capable of gathering and analyzing diverse sets of data acquired via sensors. Apart from the aforementioned data such as stylus pressure level and writing speed, we may derive other information through additional analysis. For example, by using event information (i.e.,