Katherine J. Mimnaugh

HC
9papers
38citations
Novelty35%
AI Score35

9 Papers

33.5HCMar 27
Uncovering Patterns of Brain Activity from EEG Data Consistently Associated with Cybersickness Using Neural Network Interpretability Maps

Jacqueline Yau, Katherine J. Mimnaugh, Evan G. Center et al.

Cybersickness poses a serious challenge for users of virtual reality (VR) technology. Consequently, there has been significant effort to track its occurrence during VR use with passive measures like brain activity recorded through electroencephalogram (EEG). To classify cybersickness accurately, including in real time, machine learning algorithms which can extract meaningful signals from the rest of the brain data will be required. However, EEG datasets are typically very small and very high in variability between participants, which makes building effective models extremely challenging. To address these concerns, we first introduce a framework for neural networks which has subject-adaptive training with calibration and interpretation for classification given limited and imbalanced EEG data. Which features the models determine are most useful can be visualized by plotting interpretability maps from integrated gradients and class activation. The framework is demonstrated here with convolutional neural networks and transformer models. Using a set of brain data recorded with EEG while participants viewed a stimulus in VR designed to elicit cybersickness, we show which spatio-temporal EEG features (from electrodes and time steps) were most important for discomfort classification. Across 12 runs of our framework with three different neural networks over multiple random seeds, the models consistently pointed to the same scalp locations as having patterns of brain data that were the most helpful in determining whether or not a sample of EEG data belonged to someone who was experiencing cybersickness. These results help clarify a hidden pattern in other related research and can be used as tagged features for better real-time cybersickness classification with EEG in the future. We provide our code at [anonymized] to enable feature interpretation across different neural network architectures.

HCFeb 2, 2022
Augmenting Immersive Telepresence Experience with a Virtual Body

Nikunj Arora, Markku Suomalainen, Matti Pouke et al.

We propose augmenting immersive telepresence by adding a virtual body, representing the user's own arm motions, as realized through a head-mounted display and a 360-degree camera. Previous research has shown the effectiveness of having a virtual body in simulated environments; however, research on whether seeing one's own virtual arms increases presence or preference for the user in an immersive telepresence setup is limited. We conducted a study where a host introduced a research lab while participants wore a head-mounted display which allowed them to be telepresent at the host's physical location via a 360-degree camera, either with or without a virtual body. We first conducted a pilot study of 20 participants, followed by a pre-registered 62 participant confirmatory study. Whereas the pilot study showed greater presence and preference when the virtual body was present, the confirmatory study failed to replicate these results, with only behavioral measures suggesting an increase in presence. After analyzing the qualitative data and modeling interactions, we suspect that the quality and style of the virtual arms, and the contrast between animation and video, led to individual differences in reactions to the virtual body which subsequently moderated feelings of presence.

ROJan 7, 2022
Unwinding Rotations Improves User Comfort with Immersive Telepresence Robots

Markku Suomalainen, Basak Sakcak, Adhi Widagdo et al.

We propose unwinding the rotations experienced by the user of an immersive telepresence robot to improve comfort and reduce VR sickness of the user. By immersive telepresence we refer to a situation where a 360\textdegree~camera on top of a mobile robot is streaming video and audio into a head-mounted display worn by a remote user possibly far away. Thus, it enables the user to be present at the robot's location, look around by turning the head and communicate with people near the robot. By unwinding the rotations of the camera frame, the user's viewpoint is not changed when the robot rotates. The user can change her viewpoint only by physically rotating in her local setting; as visual rotation without the corresponding vestibular stimulation is a major source of VR sickness, physical rotation by the user is expected to reduce VR sickness. We implemented unwinding the rotations for a simulated robot traversing a virtual environment and ran a user study (N=34) comparing unwinding rotations to user's viewpoint turning when the robot turns. Our results show that the users found unwound rotations more preferable and comfortable and that it reduced their level of VR sickness. We also present further results about the users' path integration capabilities, viewing directions, and subjective observations of the robot's speed and distances to simulated people and objects.

HCSep 9, 2021
Comfort and Sickness while Virtually Aboard an Autonomous Telepresence Robot

Markku Suomalainen, Katherine J. Mimnaugh, Israel Becerra et al.

In this paper, we analyze how different path aspects affect a user's experience, mainly VR sickness and overall comfort, while immersed in an autonomously moving telepresence robot through a virtual reality headset. In particular, we focus on how the robot turns and the distance it keeps from objects, with the goal of planning suitable trajectories for an autonomously moving immersive telepresence robot in mind; rotational acceleration is known for causing the majority of VR sickness, and distance to objects modulates the optical flow. We ran a within-subjects user study (n = 36, women = 18) in which the participants watched three panoramic videos recorded in a virtual museum while aboard an autonomously moving telepresence robot taking three different paths varying in aspects such as turns, speeds, or distances to walls and objects. We found a moderate correlation between the users' sickness as measured by the SSQ and comfort on a 6-point Likert scale across all paths. However, we detected no association between sickness and the choice of the most comfortable path, showing that sickness is not the only factor affecting the comfort of the user. The subjective experience of turn speed did not correlate with either the SSQ scores or comfort, even though people often mentioned turning speed as a source of discomfort in the open-ended questions. Through exploring the open-ended answers more carefully, a possible reason is that the length and lack of predictability also play a large role in making people observe turns as uncomfortable. A larger subjective distance from walls and objects increased comfort and decreased sickness both in quantitative and qualitative data. Finally, the SSQ subscales and total weighted scores showed differences by age group and by gender.

ROMar 5, 2021
Analysis of User Preferences for Robot Motions in Immersive Telepresence

Katherine J. Mimnaugh, Markku Suomalainen, Israel Becerra et al.

This paper considers how the motions of a telepresence robot moving autonomously affect a person immersed in the robot through a head-mounted display. In particular, we explore the preference, comfort, and naturalness of elements of piecewise linear paths compared to the same elements on a smooth path. In a user study, thirty-six subjects watched panoramic videos of three different paths through a simulated museum in virtual reality and responded to questionnaires regarding each path. Preference for a particular path was influenced the most by comfort, forward speed, and characteristics of the turns. Preference was also strongly associated with the users' perceived naturalness, which was primarily determined by the ability to see salient objects, the distance to the walls and objects, as well as the turns. Participants favored the paths that had a one meter per second forward speed and rated the path with the least amount of turns as the most comfortable

ROFeb 25, 2021
Defining Preferred and Natural Robot Motions in Immersive Telepresence from a First-Person Perspective

Katherine J. Mimnaugh, Markku Suomalainen, Israel Becerra et al.

This paper presents some early work and future plans regarding how the autonomous motions of a telepresence robot affect a person embodied in the robot through a head-mounted display. We consider the preferences, comfort, and the perceived naturalness of aspects of piecewise linear paths compared to the same aspects on a smooth path. In a user study, thirty-six subjects (eighteen females) watched panoramic videos of three different paths through a simulated museum in virtual reality and responded to questionnaires regarding each path. We found that comfort had a strong effect on path preference, and that the subjective feeling of naturalness also had a strong effect on path preference, even though people consider different things as natural. We describe a categorization of the responses regarding the naturalness of the robot's motion and provide a recommendation on how this can be applied more broadly. Although immersive robotic telepresence is increasingly being used for remote education, clinical care, and to assist people with disabilities or mobility complications, the full potential of this technology is limited by issues related to user experience. Our work addresses these shortcomings and will enable the future personalization of telepresence experiences for the improvement of overall remote communication and the enhancement of the feeling of presence in a remote location.

HCFeb 5, 2021
The Plausibility Paradox for Resized Users in Virtual Environments

Matti Pouke, Katherine J. Mimnaugh, Alexis Chambers et al.

This paper identifies and confirms a perceptual phenomenon: when users interact with simulated objects in a virtual environment where the users' scale deviates greatly from normal, there is a mismatch between the object physics they consider realistic and the object physics that would be correct at that scale. We report the findings of two studies investigating the relationship between perceived realism and a physically accurate approximation of reality in a virtual reality experience in which the user has been scaled by a factor of ten. Study 1 investigated perception of physics when scaled-down by a factor of ten, whereas Study 2 focused on enlargement by a similar amount. Studies were carried out as within-subjects experiments in which a total of 84 subjects performed simple interaction tasks with objects under two different physics simulation conditions. In the true physics condition, the objects, when dropped and thrown, behaved accurately according to the physics that would be correct at that either reduced or enlarged scale in the real world. In the movie physics condition, the objects behaved in a similar manner as they would if no scaling of the user had occurred. We found that a significant majority of the users considered the movie physics condition to be the more realistic one. However, at enlarged scale, many users considered true physics to match their expectations even if they ultimately believed movie physics to be the realistic condition. We argue that our findings have implications for many virtual reality and telepresence applications involving operation with simulated or physical objects in abnormal and especially small scales.

ROFeb 25, 2020
Human Perception-Optimized Planning for Comfortable VR-Based Telepresence

Israel Becerra, Markku Suomalainen, Eliezer Lozano et al.

This paper introduces an emerging motion planning problem by considering a human that is immersed into the viewing perspective of a remote robot. The challenge is to make the experience both effective (such as delivering a sense of presence) and comfortable (such as avoiding adverse sickness symptoms, including nausea). We refer to this challenging new area as human perception-optimized planning and propose a general multiobjective optimization framework that can be instantiated in many envisioned scenarios. We then consider a specific VR telepresence task as a case of human perception-optimized planning, in which we simulate a robot that sends 360 video to a remote user to be viewed through a head-mounted display. In this particular task, we plan trajectories that minimize VR sickness (and thereby maximize comfort). An A* type method is used to create a Pareto-optimal collection of piecewise linear trajectories while taking into account criteria that improve comfort. We conducted a study with human subjects touring a virtual museum, in which paths computed by our algorithm are compared against a reference RRT-based trajectory. Generally, users suffered less from VR sickness and preferred the paths created by the presented algorithm.

HCDec 3, 2019
The Plausibility Paradox for Scaled-Down Users in Virtual Environments

Matti Pouke, Katherine J. Mimnaugh, Timo Ojala et al.

This paper identifies a new phenomenon: when users interact with simulated objects in a virtual environment where the user is much smaller than usual, there is a mismatch between the object physics that they expect and the object physics that would be correct at that scale. We report the findings of our study investigating the relationship between perceived realism and a physically accurate approximation of reality in a virtual reality experience in which the user has been scaled down by a factor of ten. We conducted a within-subjects experiment in which 44 subjects performed a simple interaction task with objects under two different physics simulation conditions. In one condition, the objects, when dropped and thrown, behaved accurately according to the physics that would be correct at that reduced scale in the real world, our true physics condition. In the other condition, the movie physics condition, the objects behaved in a similar manner as they would if no scaling of the user had occurred. We found that a significant majority of the users considered the latter condition to be the more realistic one. We argue that our findings have implications for many virtual reality and telepresence applications involving operation with simulated or physical objects in small scales.