Jörg Müller

HC
h-index2
11papers
241citations
Novelty42%
AI Score27

11 Papers

HCMay 13, 2020Code
Levitation Simulator: Prototyping Ultrasonic Levitation Interfaces in Virtual Reality

Viktorija Paneva, Myroslav Bachynskyi, Jörg Müller

We present the Levitation Simulator, a system that enables researchers and designers to iteratively develop and prototype levitation interface ideas in Virtual Reality. This includes user tests and formal experiments. We derive a model of the movement of a levitating particle in such an interface. Based on this, we develop an interactive simulation of the levitation interface in VR, which exhibits the dynamical properties of the real interface. The results of a Fitts' Law pointing study show that the Levitation Simulator enables performance, comparable to the real prototype. We developed the first two interactive games, dedicated for levitation interfaces: LeviShooter and BeadBounce, in the Levitation Simulator, and then implemented them on the real interface. Our results indicate that participants experienced similar levels of user engagement when playing the games, in the two environments. We share our Levitation Simulator as Open Source, thereby democratizing levitation research, without the need for a levitation apparatus.

LGFeb 5, 2024
Efficient and Interpretable Traffic Destination Prediction using Explainable Boosting Machines

Yasin Yousif, Jörg Müller

Developing accurate models for traffic trajectory predictions is crucial for achieving fully autonomous driving. Various deep neural network models have been employed to address this challenge, but their black-box nature hinders transparency and debugging capabilities in a deployed system. Glass-box models offer a solution by providing full interpretability through methods like \ac{GAM}. In this study, we evaluate an efficient additive model called \ac{EBM} for traffic prediction on three popular mixed traffic datasets: \ac{SDD}, \ac{InD}, and Argoverse. Our results show that the \ac{EBM} models perform competitively in predicting pedestrian destinations within \ac{SDD} and \ac{InD} while providing modest predictions for vehicle-dominant Argoverse dataset. Additionally, our transparent trained models allow us to analyse feature importance and interactions, as well as provide qualitative examples of predictions explanation. The full training code will be made public upon publication.

HCFeb 27, 2022
Evoking realistic affective touch experiences in virtual reality

Sofia Seinfeld, Ivette Schmidt, Jörg Müller

This study aims to better understand the emotional and physiological correlates of being caressed in VR depending on the type of multisensory feedback provided and the animate or inanimate nature of the virtual representation that touches an embodied virtual body. We evaluated how pleasure, arousal, embodiment, and the illusion of being touched in VR were influenced by the inclusion of only visual feedback compared to visuotactile stimulation conditions, where participants, in addition to seeing an avatar or feather caressing their virtual bodies, also perceived congruent mid-air ultrasonic tactile stimulation or real interpersonal touch. We found that visuotactile feedback, either based on ultrasound or real interpersonal touch, boosts the illusion of being affectively touched and embodied in a virtual body compared to conditions only based on visual feedback. However, real interpersonal touch led to the strongest behavioral and emotional responses compared to the other conditions. Moreover, arousal and the desire to withdraw the caressed hand was highest when being touched by a female avatar compared to a virtual feather. Female participants reported a stronger illusion of being caressed in VR compared to males. Overall, this study advances knowledge of the emotional and physiological impact of affective touch in VR.

HCOct 1, 2021
Optimal Feedback Control for Modeling Human-Computer Interaction

Florian Fischer, Arthur Fleig, Markus Klar et al.

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 is based on the assumption that humans aim to control their body optimally, within the constraints imposed by body, environment, and task. In this paper, we explain how this theory can be applied to understanding Human-Computer Interaction (HCI) in the case of pointing. We propose that the human body and computer dynamics can be interpreted as a single dynamical system. The system state is controlled by the user via muscle control signals, and estimated from observations. Between-trial variability arises from signal-dependent control noise and observation noise. We compare four different models from optimal control theory and evaluate to what degree these models can replicate movements in the case of mouse pointing. We introduce a procedure to identify parameters that best explain observed user behavior. To support HCI researchers in simulating, analyzing, and optimizing interaction movements, we provide the Python toolbox OFC4HCI. We conclude that OFC presents a powerful framework for HCI to understand and simulate motion of the human body and of the interface on a moment by moment basis.

HCMar 15, 2021
Intermittent control as a model of mouse movements

J. Alberto Álvarez Martín, Henrik Gollee, Jörg Müller et al.

We present Intermittent Control (IC) models as a candidate framework for modelling human input movements in Human--Computer Interaction (HCI). IC differs from continuous control in that users are not assumed to use feedback to adjust their movements continuously, but only when the difference between the observed pointer position and predicted pointer positions become large. We use a parameter optimisation approach to identify the parameters of an intermittent controller from experimental data, where users performed one-dimensional mouse movements in a reciprocal pointing task. Compared to previous published work with continuous control models, based on the Kullback-Leibler divergence from the experimental observations, IC is better able to generatively reproduce the distinctive dynamical features and variability of the pointing task across participants and over repeated tasks. IC is compatible with current physiological and psychological theory and provides insight into the source of variability in HCI tasks.

QMNov 13, 2020
Reinforcement Learning Control of a Biomechanical Model of the Upper Extremity

Florian Fischer, Miroslav Bachinski, Markus Klar et al.

Among the infinite number of possible movements that can be produced, humans are commonly assumed to choose those that optimize criteria such as minimizing movement time, subject to certain movement constraints like signal-dependent and constant motor noise. While so far these assumptions have only been evaluated for simplified point-mass or planar models, we address the question of whether they can predict reaching movements in a full skeletal model of the human upper extremity. We learn a control policy using a motor babbling approach as implemented in reinforcement learning, using aimed movements of the tip of the right index finger towards randomly placed 3D targets of varying size. We use a state-of-the-art biomechanical model, which includes seven actuated degrees of freedom. To deal with the curse of dimensionality, we use a simplified second-order muscle model, acting at each degree of freedom instead of individual muscles. The results confirm that the assumptions of signal-dependent and constant motor noise, together with the objective of movement time minimization, are sufficient for a state-of-the-art skeletal model of the human upper extremity to reproduce complex phenomena of human movement, in particular Fitts' Law and the 2/3 Power Law. This result supports the notion that control of the complex human biomechanical system can plausibly be determined by a set of simple assumptions and can easily be learned.

HCMay 13, 2020
LeviCursor: Dexterous Interaction with a Levitating Object

Myroslav Bachynskyi, Viktorija Paneva, Jörg Müller

We present LeviCursor, a method for interactively moving a physical, levitating particle in 3D with high agility. The levitating object can move continuously and smoothly in any direction. We optimize the transducer phases for each possible levitation point independently. Using precomputation, our system can determine the optimal transducer phases within a few microseconds and achieves round-trip latencies of 15 ms. Due to our interpolation scheme, the levitated object can be controlled almost instantaneously with sub-millimeter accuracy. We present a particle stabilization mechanism which ensures the levitating particle is always in the main levitation trap. Lastly, we conduct the first Fitts' law-type pointing study with a real 3D cursor, where participants control the movement of the levitated cursor between two physical targets. The results of the user study demonstrate that using LeviCursor, users reach performance comparable to that of a mouse pointer.

HCMay 13, 2020
HaptiRead: Reading Braille as Mid-Air Haptic Information

Viktorija Paneva, Sofia Seinfeld, Michael Kraiczi et al.

Mid-air haptic interfaces have several advantages - the haptic information is delivered directly to the user, in a manner that is unobtrusive to the immediate environment. They operate at a distance, thus easier to discover; they are more hygienic and allow interaction in 3D. We validate, for the first time, in a preliminary study with sighted and a user study with blind participants, the use of mid-air haptics for conveying Braille. We tested three haptic stimulation methods, where the haptic feedback was either: a) aligned temporally, with haptic stimulation points presented simultaneously (Constant); b) not aligned temporally, presenting each point independently (Point-By-Point); or c) a combination of the previous methodologies, where feedback was presented Row-by-Row. The results show that mid-air haptics is a viable technology for presenting Braille characters, and the highest average accuracy (94% in the preliminary and 88% in the user study) was achieved with the Point-by-Point method.

HCFeb 27, 2020
Impact of Visuomotor Feedback on the Embodiment of Virtual Hands Detached from the Body

Sofia Seinfeld, Jörg Müller

It has been shown that mere observation of body discontinuity leads to diminished body ownership. However, the impact of body discontinuity has mainly been investigated in conditions where participants observe a collocated static virtual body from a first-person perspective. This study explores the influence of body discountinuity on the sense of embodiment, when rich visuomotor correlations between a real and an artificial virtual body are established. In two experiments, we evaluated body ownership and motor performance, when participants interacted in virtual reality either using virtual hands connected or disconnected from a body. We found that even under the presence of congruent visuomotor feedback, mere observation of body discontinuity resulted in diminished embodiment. Contradictory evidence was found in relation to motor performance, where further research is needed to understand the role of visual body discontinuity in motor tasks. Preliminary findings on physiological reactions to a threat were also assessed, indicating that body visual discontinuity does not differently impact threat-related skin conductance responses. The present results are in accordance with past evidence showing that body discontinuity negatively impacts embodiment. However, further research is needed to understand the influence of visuomotor feedback and body morphological congruency on motor performance and threat-related physiological reactions.

HCFeb 27, 2020
Impact of Information Placement and User Representations in VR on Performance and Embodiment

Sofia Seinfeld, Tiare Feuchtner, Johannes Pinzek et al.

Human sensory processing is sensitive to the proximity of stimuli to the body. It is therefore plausible that these perceptual mechanisms also modulate the detectability of content in VR, depending on its location. We evaluate this in a user study and further explore the impact of the user's representation during interaction. We also analyze how embodiment and motor performance are influenced by these factors. In a dual-task paradigm, participants executed a motor task, either through virtual hands, virtual controllers, or a keyboard. Simultaneously, they detected visual stimuli appearing in different locations. We found that, while actively performing a motor task in the virtual environment, performance in detecting additional visual stimuli is higher when presented near the user's body. This effect is independent of how the user is represented and only occurs when the user is also engaged in a secondary task. We further found improved motor performance and increased embodiment when interacting through virtual tools and hands in VR, compared to interacting with a keyboard. This study contributes to better understanding the detectability of visual content in VR, depending on its location in the virtual environment, as well as the impact of different user representations on information processing, embodiment, and motor performance.

HCJul 18, 2019
ReconViguRation: Reconfiguring Physical Keyboards in Virtual Reality

Daniel Schneider, Alexander Otte, Travis Gesslein et al.

Physical keyboards are common peripherals for personal computers and are efficient standard text entry devices. Recent research has investigated how physical keyboards can be used in immersive head-mounted display-based Virtual Reality (VR). So far, the physical layout of keyboards has typically been transplanted into VR for replicating typing experiences in a standard desktop environment. In this paper, we explore how to fully leverage the immersiveness of VR to change the input and output characteristics of physical keyboard interaction within a VR environment. This allows individual physical keys to be reconfigured to the same or different actions and visual output to be distributed in various ways across the VR representation of the keyboard. We explore a set of input and output mappings for reconfiguring the virtual presentation of physical keyboards and probe the resulting design space by specifically designing, implementing and evaluating nine VR-relevant applications: emojis, languages and special characters, application shortcuts, virtual text processing macros, a window manager, a photo browser, a whack-a-mole game, secure password entry and a virtual touch bar. We investigate the feasibility of the applications in a user study with 20 participants and find that, among other things, they are usable in VR. We discuss the limitations and possibilities of remapping the input and output characteristics of physical keyboards in VR based on empirical findings and analysis and suggest future research directions in this area.