The Least Increasing Aversion (LIA) Protocol: Illustration on Identifying Individual Susceptibility to Cybersickness Triggers.

This paper introduces the Least Increase aversion (LIA) protocol to investigate the relative impact of factors that may trigger cybersickness. The protocol is inspired by the Subjective Matching methodology (SMT) from which it borrows the incremental construction of a richer VR experience, except that the full-blown target experience may cause undesired discomfort. In the first session, the participant briefly encounter all factors at the maximum level. Then in the second session they start with the minimum level of all factors as a Baseline. Subsequently, we expect the participant to minimize their exposure to the most adverse factors. This approach ranks the factors from mildest to worst and helps detect individual susceptibility to cybersickness triggers.To validate the applicability of LIA protocol, we further evaluate it with an experiment to identify individual susceptibility to three rotational axes (Yaw, Pitch, and Roll). The findings not only confirm the protocol's capability to accurately discern individual rankings of various factors to cybersickness but also indicate that individual susceptibility is more intricate and multifaceted than initially anticipated.

Who says you are so sick? An investigation on individual susceptibility to cybersickness triggers using EEG, EGG and ECG.

In this research paper, we conducted a study to investigate the connection between three objective measures: Electrocardio-gram(EGG), Electrogastrogram (EGG), and Electroencephalogram (EEG), and individuals' susceptibility to cybersickness. Our primary objective was to identify which of these factors plays a central role in causing discomfort when experiencing rotations along three different axes: Roll, Pitch, and Yaw. This study involved 35 participants who were tasked with destroying asteroids using their eye gaze while undergoing passive rotations in four separate sessions. The results, when combined with subjective measurements (specifically, Fast motion sickness questionnaire (FMS) and Simulator sickness questionnaire (SSQ) score), demonstrated that EGG measurements were superior in detecting symptoms associated with nausea. As for ECG measurements, our observations did reveal significant changes in Heart Rate Variability (HRV) parameters. However, we caution against relying solely on ECG as a dependable indicator for assessing the extent of cybersickness. Most notably, EEG signals emerged as a crucial resource for discerning individual differences related to these rotational axes. Our findings were significant not only in the context of periodic activities but also underscored the potential of aperiodic activities in detecting the severity of cybersickness and an individual's susceptibility to rotational triggers.

In Case of Doubt, One Follows One's Self: The Implicit Guidance of the Embodied Self-Avatar.

The sense of embodiment in virtual reality (VR) is commonly understood as the subjective experience that one's physical body is substituted by a virtual counterpart, and is typically achieved when the avatar's body, seen from a first-person view, moves like one's physical body. Embodiment can also be experienced in other circumstances (e.g., in third-person view) or with imprecise or distorted visuo-motor coupling. It was moreover observed, in various cases of small or progressive temporal and spatial manipulations of avatars' movements, that participants may spontaneously follow the movement shown by the avatar. The present work investigates whether, in some specific contexts, participants would follow what their avatar does even when large movement discrepancies occur, thereby extending the scope of understanding of the self-avatar follower effect beyond subtle changes of motion or speed manipulations. We conducted an experimental study in which we introduced uncertainty about which movement to perform at specific times and analyzed participants' movements and subjective feedback after their avatar showed them an incorrect movement. Results show that, when in doubt, participants were influenced by their avatar's movements, leading them to perform that particular error twice more often than normal. Importantly, results of the embodiment score indicate that participants experienced a dissociation with their avatar at those times. Overall, these observations not only demonstrate the possibility of provoking situations in which participants follow the guidance of their avatar for large motor distortions, despite their awareness about the avatar movement disruption and on the possible influence it had on their choice, and, importantly, exemplify how the cognitive mechanism of embodiment is deeply rooted in the necessity of having a body.

Customizing the human-avatar mapping based on EEG error related potentials.

Objective.A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside the virtual body when they perceive erroneous interaction, i.e. a break-in-embodiment (BiE). However, the way to detect such an inadequate event is currently limited to questionnaires or spontaneous reports from users. The ability to implicitly detect BiE in real-time enables us to adjust human-avatar mapping without interruption.Approach.We propose and empirically demonstrate a novel brain computer interface (BCI) approach that monitors the occurrence of BiE based on the users' brain oscillatory activity in real-time to adjust the human-avatar mapping in VR. We collected EEG activity of 37 participants while they performed reaching movements with their avatar with different magnitude of distortion.Main results.Our BCI approach seamlessly predicts occurrence of BiE in varying magnitude of erroneous interaction. The mapping has been customized by BCI-reinforcement learning (RL) closed-loop system to prevent BiE from occurring. Furthermore, a non-personalized BCI decoder generalizes to new users, enabling 'Plug-and-Play' ErrP-based non-invasive BCI. The proposed VR system allows customization of human-avatar mapping without personalized BCI decoders or spontaneous reports.Significance.We anticipate that our newly developed VR-BCI can be useful to maintain an engaging avatar-based interaction and a compelling immersive experience while detecting when users notice a problem and seamlessly correcting it.

EEG signature of breaks in embodiment in VR.

The brain mechanism of embodiment in a virtual body has grown a scientific interest recently, with a particular focus on providing optimal virtual reality (VR) experiences. Disruptions from an embodied state to a less- or non-embodied state, denominated Breaks in Embodiment (BiE), are however rarely studied despite their importance for designing interactions in VR. Here we use electroencephalography (EEG) to monitor the brain's reaction to a BiE, and investigate how this reaction depends on previous embodiment conditions. The experimental protocol consisted of two sequential steps; an induction step where participants were either embodied or non-embodied in an avatar, and a monitoring step where, in some cases, participants saw the avatar's hand move while their hand remained still. Our results show the occurrence of error-related potentials linked to observation of the BiE event in the monitoring step. Importantly, this EEG signature shows amplified potentials following the non-embodied condition, which is indicative of an accumulation of errors across steps. These results provide neurophysiological indications on how progressive disruptions impact the expectation of embodiment for a virtual body.

Avatar error in your favor: Embodied avatars can fix users' mistakes without them noticing.

In immersive Virtual Reality (VR), users can experience the subjective feeling of embodiment for the avatar representing them in a virtual world. This is known to be strongly supported by a high Sense of Agency (SoA) for the movements of the avatar that follows the user. In general, users do not self-attribute actions of their avatar that are different from the one they actually performed. The situation is less clear when actions of the avatar satisfies the intention of the user despite distortions and noticeable differences between user and avatar movements. Here, a within-subject experiment was condutected to determine wether a finger swap helping users to achieve a task would be more tolerated than one penalizing them. In particular, in a context of fast-paced finger movements and with clear correct or incorrect responses, we swapped the finger animation of the avatar (e.g. user moves the index finger, the avatar moves the middle one) to either automatically correct for spontaneous mistakes or to introduce incorrect responses. Subjects playing a VR game were asked to report when they noticed the introduction of a finger swap. Results based on 3256 trials (∼24% of swaps noticed) show that swaps helping users have significantly fewer odds of being noticed (and with higher confidence) than the ones penalizing users. This demonstrates how the context and the intention for motor action are important factors for the SoA and for embodiment, opening new perspectives on how to design and study interactions in immersive VR.

Reaching articular limits can negatively impact embodiment in virtual reality.

Providing Virtual Reality(VR) users with a 3D representation of their body complements the experience of immersion and presence in the virtual world with the experience of being physically located and more personally involved. A full-body avatar representation is known to induce a Sense of Embodiment (SoE) for this virtual body, which is associated with improvements in task performance, motivation and motor learning. Recent experimental research on embodiment provides useful guidelines, indicating the extent of discrepancy tolerated by users and, conversely, the limits and disruptive events that lead to a break in embodiment (BiE). Based on previous works on the limit of agency under movement distortion, this paper describes, studies and analyses the impact of a very common yet overlooked embodiment limitation linked to articular limits when performing a reaching movement. We demonstrate that perceiving the articular limit when fully extending the arm provides users with an additional internal proprioceptive feedback which, if not matched in the avatar's movement, leads to the disruptive realization of an incorrect posture mapping. This study complements previous works on self-contact and visuo-haptic conflicts and emphasizes the risk of disrupting the SoE when distorting users' movements or using a poorly-calibrated avatar.

Adapting Virtual Embodiment Through Reinforcement Learning.

In Virtual Reality, having a virtual body opens a wide range of possibilities as the participant's avatar can appear to be quite different from oneself for the sake of the targeted application (e.g., for perspective-taking). In addition, the system can partially manipulate the displayed avatar movement through some distortion to make the overall experience more enjoyable and effective (e.g., training, exercising, rehabilitation). Despite its potential, an excessive distortion may become noticeable and break the feeling of being embodied into the avatar. Past researches have shown that individuals have a relatively high tolerance to movement distortions and a great variability of individual sensitivities to distortions. In this article, we propose a method taking advantage of Reinforcement Learning (RL) to efficiently identify the magnitude of the maximum distortion that does not get noticed by an individual (further noted the detection threshold). We show through a controlled experiment with subjects that the RL method finds a more robust detection threshold compared to the adaptive staircase method, i.e., it is more able to prevent subjects from detecting the distortion when its amplitude is equal or below the threshold. Finally, the associated majority voting system makes the RL method able to handle more noise within the forced choices input than adaptive staircase. This last feature is essential for future use with physiological signals as these latter are even more susceptible to noise. It would then allow to calibrate embodiment individually to increase the effectiveness of the proposed interactions.

The Critical Role of Self-Contact for Embodiment in Virtual Reality.

With the broad range of motion capture devices available on the market, it is now commonplace to directly control the limb movement of an avatar during immersion in a virtual environment. Here, we study how the subjective experience of embodying a full-body controlled avatar is influenced by motor alteration and self-contact mismatches. Self-contact is in particular a strong source of passive haptic feedback and we assume it to bring a clear benefit in terms of embodiment. For evaluating this hypothesis, we experimentally manipulate self-contacts and the virtual hand displacement relatively to the body. We introduce these body posture transformations to experimentally reproduce the imperfect or incorrect mapping between real and virtual bodies, with the goal of quantifying the limits of acceptance for distorted mapping on the reported body ownership and agency. We first describe how we exploit egocentric coordinate representations to perform a motion capture ensuring that real and virtual hands coincide whenever the real hand is in contact with the body. Then, we present a pilot study that focuses on quantifying our sensitivity to visuo-tactile mismatches. The results are then used to design our main study with two factors, offset (for self-contact) and amplitude (for movement amplification). Our main result shows that subjects' embodiment remains important, even when an artificially amplified movement of the hand was performed, but provided that correct self-contacts are ensured.

Egocentric Mapping of Body Surface Constraints.

The relative location of human body parts often materializes the semantics of on-going actions, intentions and even emotions expressed, or performed, by a human being. However, traditional methods of performance animation fail to correctly and automatically map the semantics of performer postures involving self-body contacts onto characters with different sizes and proportions. Our method proposes an egocentric normalization of the body-part relative distances to preserve the consistency of self contacts for a large variety of human-like target characters. Egocentric coordinates are character independent and encode the whole posture space, i.e., it ensures the continuity of the motion with and without self-contacts. We can transfer classes of complex postures involving multiple interacting limb segments by preserving their spatial order without depending on temporal coherence. The mapping process exploits a low-cost constraint relaxation technique relying on analytic inverse kinematics; thus, we can achieve online performance animation. We demonstrate our approach on a variety of characters and compare it with the state of the art in online retargeting with a user study. Overall, our method performs better than the state of the art, especially when the proportions of the animated character deviate from those of the performer.

Characterizing first and third person viewpoints and their alternation for embodied interaction in virtual reality.

Empirical research on the bodily self has shown that the body representation is malleable, and prone to manipulation when conflicting sensory stimuli are presented. Using Virtual Reality (VR) we assessed the effects of manipulating multisensory feedback (full body control and visuo-tactile congruence) and visual perspective (first and third person perspective) on the sense of embodying a virtual body that was exposed to a virtual threat. We also investigated how subjects behave when the possibility of alternating between first and third person perspective at will was presented. Our results support that illusory ownership of a virtual body can be achieved in both first and third person perspectives under congruent visuo-motor-tactile condition. However, subjective body ownership and reaction to threat were generally stronger for first person perspective and alternating condition than for third person perspective. This suggests that the possibility of alternating perspective is compatible with a strong sense of embodiment, which is meaningful for the design of new embodied VR experiences.

Sensitivity of hip tissues contact evaluation to the methods used for estimating the hip joint center of rotation.

Computer-based simulations of human hip joints generally include investigating contacts happening among soft or hard tissues during hip movement. In many cases, hip movement is approximated as rotation about an estimated hip center. In this paper, we investigate the effect of different methods used for estimating hip joint center of rotation on the results acquired from hip simulation. For this reason, we use three dimensional models of hip tissues reconstructed from MRI datasets of 10 subjects, and estimate their center of rotation by applying five different methods (including both predictive and functional approaches). Then, we calculate the amount of angular and radial penetrations that happen among three dimensional meshes of cartilages, labrum, and femur bone, when hip is rotating about different estimated centers of rotation. The results indicate that hip simulation can be highly affected by the method used for estimating hip center of rotation. However, under some conditions (e.g. when Adduction or External Rotation are considered) we can expect to have a more robust simulation. In addition, it was observed that applying some methods (e.g. the predictive approach based on acetabulum) may result in less robust simulation, comparing to the other methods.

Penetration depth method--novel real-time strategy for evaluating femoroacetabular impingement.

We introduce a new method for computerized real-time evaluation of femoroacetabular impingement (FAI). In contrast to previously presented stress analyses, this method is based on two types of predictions of penetration depths for two rotating bodies: curvilinear and radial penetration depth. This intuitive method allows the analysis of both bony and soft tissue structures (such as cartilage and acetabular labrum) in real time. Characteristic penetration depth patterns were found for different subtypes of FAI, such as cam and pincer pathologies. In addition, correlation between the penetration depths (estimated by applying this method) and the existing contact stresses (estimated by applying the finite element method) of various hip morphologies were found. A strong correlation with predicted stress values existed, with a mean correlation coefficient of 0.91 for the curvilinear and 0.80 for the radial penetration method. The results show that the penetration depth method is a promising, fast, and accurate method for quantification and diagnosis of FAI.

Fast collision detection methods for joint surfaces.

In the recent years medical diagnosis and surgery planning often require the precise evaluation of joint movements. This has led to exploit reconstructed three-dimensional models of the joint tissues obtained from CT or MR Images (for bones, cartilages, etc.). In such context, efficiently and precisely detecting collisions among the virtual tissues is critical for guaranteeing the quality of any further analysis. The common methods of collision detection are usually designed for general purpose applications in computer graphics or CAD-CAM. Hence they face worst case scenarios when handling the quasi-perfect concavity-convexity matching of the articular surfaces. In this paper, we present two fast collision detection methods that take advantage of the relative proximity and the nature of the movement to discard unnecessary calculations. The proposed approaches also accurately provide the penetration depths along two functional directions, without any approximation. They are compared with other collision detection methods and tested in different biomedical scenarios related to the human hip joint.

Virtual reality software and technology.

This special issue contains an introductory survey on 3D user interfaces by leading VR authorities and significantly expanded versions of the four best short papers from the proceedings of the 14th ACM Symposium on Virtual Reality Software and Technology (VRST 07).

A fast method for finding range of motion in the human joints.

Finding the range of motion for the human joints is a popular method for diagnosing joint diseases. By current technology, it is more trustable and easier to find the range of motion by employing computer based models of the human tissues. In this paper we propose a novel method for finding range of motion for human joints without using any collision detection algorithm. This method is based on mesh classifying in a cylindrically segmented space. The method shows to be much faster than the traditional ones and provides the accurate results. This method is illustrated on the case of finding the range of motion in the human hip joint.

Efficient collision detection within deforming spherical sliding contact.

Handling the evolving permanent contact of deformable objects leads to a collision detection problem of high computing cost. Situations in which this type of contact happens are becoming more and more present with the increasing complexity of virtual human models, especially for the emerging medical applications. In this context, we propose a novel collision detection approach to deal with situations in which soft structures are in constant but dynamic contact, which is typical of 3D biological elements. Our method proceeds in two stages: First, in a preprocessing stage, a mesh is chosen under certain conditions as a reference mesh and is spherically sampled. In the collision detection stage, the resulting table is exploited for each vertex of the other mesh to obtain, in constant time, its signed distance to the fixed mesh. The two working hypotheses for this approach to succeed are typical of the deforming anatomical systems we target: First, the two meshes retain a layered configuration with respect to a central point and, second, the fixed mesh tangential deformation is bounded by the spherical sampling resolution. Within this context, the proposed approach can handle large relative displacements, reorientations, and deformations of the mobile mesh. We illustrate our method in comparison with other techniques on a biomechanical model of the human hip joint.