53 citations · 123 across the 12 of their papers we have counts for
10 papers · 1 filter
MyoInteract: A Framework for Fast Prototyping of Biomechanical HCI Tasks using Reinforcement Learning
Ankit Bhattarai, Hannah Selder, Florian Fischer +2
Reinforcement learning (RL)-based biomechanical simulations have the potential to revolutionise HCI research and interaction design, but currently lack usability and interpretabili…
Demystifying Reward Design in Reinforcement Learning for Upper Extremity Interaction: Practical Guidelines for Biomechanical Simulations in HCI
Hannah Selder, Florian Fischer, Per Ola Kristensson +1
Designing effective reward functions is critical for reinforcement learning-based biomechanical simulations, yet HCI researchers and practitioners often waste (computation) time wi…
Mind & Motion: Opportunities and Applications of Integrating Biomechanics and Cognitive Models in HCI
Arthur Fleig, Florian Fischer, Markus Klar +5
Computational models of how users perceive and act within a virtual or physical environment offer enormous potential for the understanding and design of user interactions. Cognitio…
What Makes a Model Breathe? Understanding Reinforcement Learning Reward Function Design in Biomechanical User Simulation
Hannah Selder, Florian Fischer, Per Ola Kristensson +1
Biomechanical models allow for diverse simulations of user movements in interaction. Their performance depends critically on the careful design of reward functions, yet the interpl…
SIM2VR: Towards Automated Biomechanical Testing in VR
Florian Fischer, Aleksi Ikkala, Markus Klar +6
Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design proc…
Towards a Deep(er) Understanding of Interaction through Modeling, Simulation, and Optimization
Florian Fischer, Arthur Fleig, Markus Klar +2
The traditional user-centered design process can hardly keep up with the ever faster technical development and increasingly diverse user preferences. As a solution, we propose to a…
Simulating Interaction Movements via Model Predictive Control
Markus Klar, Florian Fischer, Arthur Fleig +2
We present a method to simulate movement in interaction with computers, using Model Predictive Control (MPC). The method starts from understanding interaction from an Optimal Feedb…
OptiTrap: Optimal Trap Trajectories for Acoustic Levitation Displays
Viktorija Paneva, Arthur Fleig, Diego Martínez Plasencia +2
Acoustic levitation has recently demonstrated the ability to create volumetric content by trapping and quickly moving particles along reference paths to reveal shapes in mid-air. H…
Optimal Feedback Control for Modeling Human-Computer Interaction
Florian Fischer, Arthur Fleig, Markus Klar +1
Optimal feedback control (OFC) is a theory from the motor control literature that explains how humans move their body to achieve a certain goal, e.g., pointing with the finger. OFC…
An Optimal Control Model of Mouse Pointing Using the LQR
Florian Fischer, Arthur Fleig, Markus Klar +2
In this paper we explore the Linear-Quadratic Regulator (LQR) to model movement of the mouse pointer. We propose a model in which users are assumed to behave optimally with respect…