Tool-Mediated Digital Behavior: Development of a 3D Motion-Capture Framework for Smartphone Typing Kinematics

Smartphone typing is a common form of tool-mediated behavior that requires continuous coordination between the user’s motor system and a handheld digital device. Although research has often focused on keystrokes, typing speed, or finger movements, less is known about how the smartphone itself is stabilized and adjusted during interaction. Measuring device movement may provide a complementary behavioral window onto sensorimotor coordination, motor automaticity, digital expertise, and the influence of task context. This thesis developed a three-dimensional motion-capture framework for characterizing smartphone kinematics during typing. Two reflective markers positioned on opposite corners of the device were used to construct continuous Motion and Tilt signals. Dominant frequency, root-mean-square amplitude, and robust peak-to-peak range were extracted from each signal. The framework was applied to empirical recordings from 36 participants and evaluated using synthetic trajectories containing controlled noise, drift, and missing data. The results showed that smartphone typing produces structured and measurable device-level kinematic patterns. The three Motion-derived descriptors and Tilt frequency were recovered reliably under simulated degradation, while Tilt-amplitude measures were more sensitive to noise. Exploratory analyses also indicated that the extracted variables contained variation associated with age-defined digital-experience cohorts and typing context, although these findings were not interpreted causally. By focusing on the movement of the tool rather than only on bodily movement, the framework may support future research on how digital skills are learned and organized, whether extensive digital experience modifies established tool-use processes, and how device-level behavior may contribute to developmental, cognitive, clinical, and human–computer interaction research.