Biomechanical User Models for Two-Handed Typing on Touchscreen Devices using Reinforcement Learning

Status: open / Type of Theses: Master theses / Location: Leipzig

Typing on smartphones and tablets is one of the most frequent forms of daily interaction, yet most research focuses on single-thumb typing. In practice, many users rely on two hands, introducing complex coordination between fingers, wrists, and posture. These motor patterns vary widely across users and can significantly influence typing speed, comfort, and error rates.

The primary goal of this work is to develop biomechanical user models that simulate two-handed typing behavior on touchscreen devices under human physiological constraints. The project will build on the existing BimanualMuscle body and extend it to coordinated bimanual interaction. These models will be grounded in computational rationality, assuming that users type in ways that optimize performance given their motor abilities, cognitive load, and task context. Reinforcement learning will be used to train agents to type on virtual keyboards while respecting biomechanical constraints such as finger reach, movement cost, and joint limits. The results can contribute to improved keyboard layouts and adaptive typing interfaces that better support diverse users.

BimanualMuscle body:

Computational Rationality as a Theory of Interaction:

Breathing Life into Biomechnical User Models:

Adapting User Interfaces with Model-based Reinforcement Learning:

Touchscreen Typing As Optimal Supervisory Control:

Simulating Interaction Movements via Model Predictive Control:

Biomechnical