# To use or not to use viewpoint oscillations when walking in VR? State of the art and perspectives

Yann Moullec, Justine Saint-Aubert, Mélanie Cogné, Anatole Lécuyer

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Yann Moullec, Justine Saint-Aubert, Mélanie Cogné, Anatole Lécuyer. To use or not to use viewpoint oscillations when walking in VR? State of the art and perspectives. IEEE Transactions on Visualization and Computer Graphics, 2024, pp.1-19. 10.1109/TVCG.2024.3436858. hal-04844847

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# To use or not to use viewpoint oscillations when walking in VR? State of the art and perspectives

Yann Moullec[1]

Justine Saint-Aubert[1]

[1] Univ Rennes, Inria, CNRS, IRISA
Rennes, France, email: {name.surname}@inria.fr

Mélanie Cogné[1,2]

[2] CHU Rennes
Rennes, France, e-mail: melanie.cogne@chu-rennes.fr

Anatole Lécuyer[1]

*Abstract*—Viewpoint oscillations are periodic changes in the position and/or orientation of the point of view in a virtual environment. They can be implemented in Virtual Reality (VR) walking simulations to make them feel closer to real walking. This is especially useful in simulations where users remain in place because of space or hardware constraints. As for today, it remains unclear what exact benefit they bring to user experience during walking simulations, and with what characteristics they should be implemented. To answer these questions, we conduct a systematic literature review focusing on five main dimensions of user experience (walking sensation, vector, cybersickness, presence and embodiment) and discuss 44 articles from the fields of VR, Vision, and Human-Computer Interaction. Overall, the literature suggests that viewpoint oscillations benefit vector, and with less evidence, walking sensation and presence. As for cybersickness, the literature contains contrasted results. Based on these results, we recommend using viewpoint oscillations in applications that require accurate distance or speed perception, or that aim to provide compelling walking simulations without a walking avatar, and a particular attention should be paid to cybersickness. Taken together, this work gives recommendations for enhancing walking simulations in VR, which may be applied to entertainment, virtual visits, and medical rehabilitation.

*Index Terms*—Viewpoint oscillations, virtual reality, walking sensation, vector, cybersickness, presence, embodiment.

## I. INTRODUCTION

In many Virtual Reality (VR) applications, users are required to walk in a virtual environment while remaining in place. The VR community has produced a lot of effort towards making these simulations more realistic using various stationary locomotion techniques [1] and sensory stimulation [2], including the display of a walking avatar [3], [4], vibrations to the feet [5], [6], footstep sounds [7], [8], passive proprioceptive stimulation to the lower limbs [9] and passive whole-body motion [10].

Among the developed techniques, researchers have explored adding oscillations to the linear displacement of the virtual viewpoint that simulates the head's motion while walking. These oscillations are expected to make simulations closer to actual walking biomechanics (described section III) and thus improve their naturalness. This was first implemented for desktop applications [11] and later adapted to setups using immersive displays and virtual environments [4] or stereoscopic videos of walking [7], [8].

In this systematic literature review, we are interested in how viewpoint oscillations influence users' experience during

VR walking simulations, and we discuss their benefits and drawbacks, including the risk of increasing cybersickness. We report on and analyze 44 articles from the field of VR, Vision, and Human-Computer Interaction that assess the effects of such oscillations on metrics related to the subjective experience of walking: walking sensation, vector, cybersickness, presence, and embodiment. In addition to considering these dimensions separately, we discuss their reported interactions in section X. We also consider the influence of various factors, such as the characteristics of the oscillations and the inclusion of additional sensory stimulation.

While our interest is immersive VR walking simulations, we do not restrict the search to immersive displays such as Head-Mounted Displays (HMDs) and Cave Automatic Virtual Environment-like (CAVE-like) rooms since valuable information can be acquired from studies using less immersive displays as well. Moreover, given the variety of the protocols in the considered studies (e.g., dependent variables, oscillation characteristics), we do not conduct a statistical analysis on their results, but we discuss them in the dedicated sections and provide highlights in Table II. With this paper, our goal is to synthesize the current knowledge on the effect of viewpoint oscillations on user experience, give recommendations for using them or not when simulating walking in VR, and identify areas that could need further consideration. The main contributions of the paper can be summarized as follows:

* Clarify the terminology and the main notions involved in viewpoint oscillations.

* Describe the different methods for implementing viewpoint oscillations in virtual environments and give guidelines to describe future implementations.

* Analyze the effects of viewpoint oscillations on the main dimensions of user experience during walking simulations in VR: (1) walking sensation, (2) vection, (3) cybersickness, (4) presence, and (5) embodiment.

* Discuss perspectives for future research on viewpoint oscillations in VR.

## II. TERMINOLOGY AND METHODOLOGY

Many terms have been used to refer to the simulation of head motion while walking. Some terms are related to biomechanics such as “head swaying” [4], [12], “head bobbing” [12], [13], and “head bumping” [14]. Other terms are related to simulations such as “viewpoint oscillations” [15]–[17] and
<figure><img src="image_2.png" /><figcaption>Fig. 1. PRISMA flow diagram: inclusion process for the 44 studies discussed in the review</figcaption></figure>

"display oscillations" [18], or generic terms such as "camera motion" [11], [19], [20]. In this paper, we propose to use the expression "viewpoint oscillations" to refer to **"periodic changes in position and/or orientation of the point of view in a virtual environment"**. Similarly to previous works from the VR, Vision, and Human-Computer Interaction communities [15]–[17], [21]–[24], we favor the term "viewpoint" oscillations rather than "head" or "camera" oscillations since walking simulations often do not depict a walking body, and thus no head, and because the term camera makes it less clear that we are dealing with simulations. In addition, we advocate for using the term "oscillations" to refer to smooth and continuous, although frame rate-limited, periodic changes in position and/or orientation rather than "jitter", which often refers to more unpredictable and discontinuous changes [25]–[28], although they have also been used interchangeably [22], [29], [30]. Moreover, "swaying" and "bobbing" often refer to physical motion and are sometimes associated with a particular direction (lateral and vertical, respectively).

For clarity purposes and since many terms can refer to directions, we refer to the *x*, *y*, and *z* axes as lateral (left-right), longitudinal (backward-forward), and vertical (down-up) axes, respectively. Thus, rotations around the *x*, *y*, and *z* axes correspond to pitch, roll, and yaw rotations, respectively. In addition, we consider these axes to be static with respect to the viewpoint. In the case of embodied VR, we consider the axis to move independently of the viewing direction: the *y* axis points towards the forward direction of the walking body, and the *z* axis points upwards at all times. For consistency, we refer to longitudinal translatory oscillations as relative to the body's average forward position. Moreover, most studies assess purely passive stimulations, with no locomotion technique involved. Thus, when we discuss studies on viewpoint oscillations, if we do not mention a locomotion technique, it is that none is used. Furthermore, most studies consider protocols in which users observe the oscillations while static, i.e., where users

do not physically engage in walking or oscillatory motion. Consequently, if we do not explicitly mention that the user is moving, they are static. However, they may move their head to look around the virtual environment or use controllers.

For our review, a search of the literature was conducted using the OpenAlex article database, which aggregates data on research work, authors, and institutions from numerous sources, including the Microsoft Academy Graph and Cross-Ref, but also other sources listed on their website<fnref n="1" />. The research query for the articles' abstract was: (oscillation OR jitter OR "camera motion" OR "head sway" OR bobbing OR bumping) AND (virtual OR VR OR generate OR simulate) AND (walking OR locomotion OR vection OR "self-motion" OR "self-movement") AND (experiment OR study OR evaluate OR evaluation OR examine OR examination OR assess OR assessment OR empirical). While our main interest is VR, we added other computer-related keywords to include all types of simulations since valuable information can also be acquired from studies using low-immersion devices. No limit on publication time was applied to the query. The results of the search were last checked on May 29, 2024.

To be selected, the articles' abstract had to refer to the observation of viewpoint oscillations or another stimulation resulting in an oscillating visual stimulation (e.g., oscillating whole-body motion combined with head-tracking in VR [10]). The identification process is detailed in Figure 1. Moreover, we only selected work that evaluated the effects of viewpoint oscillations when combined with a translation in a given direction of the virtual environment since, when walking, our point of view translates in the direction of the locomotion. We did not exclude articles on oscillations that are not compatible with human walking such as those with a very large amplitude or low frequency. In addition, we filtered out articles that did not assess the effect of viewpoint oscillations on walking sensation, vection, cybersickness, presence, or embodiment.

<footnote n="1">¹https://openalex.org/about</footnote>
<figure><img src="image_3.png" /><figcaption>Fig. 2. Typical natural head motion during walking at 1.11m/s: (a) Head translations along the three directions as a function of percentage of step cycle [33] (positive values represent the rightward, forward, and upward direction), (b) Resulting frontal plane pattern (vertical and lateral directions), (c) Vertical head translation and compensatory head pitch and eye motion during locomotion [31], [32], [35], [36] (scale is not representative)</figcaption></figure>

These metrics were chosen based on our focus on the subjective experience of walking while static. However, the influence of motion on these metrics is addressed in dedicated sections. Only articles written in English were selected, and short “abstract-only” formats were not retained. A total of 30 articles were gathered as direct results of the query. Additional articles were also identified through backward reference searching, which resulted in a set of 44 relevant articles.

### III. NATURAL HEAD OSCILLATIONS DURING WALKING

As mentioned in the introduction, viewpoint oscillations can be used to simulate the head's natural swaying pattern that occurs when walking. This section describes the parameters defining natural head oscillations during real walking. Several studies have characterized head kinematics during treadmill walking [31]–[35] and overground walking [36]. In these studies, head kinematics were assessed using video motion analysis [31], [32], accelerometers and heel switches [33], and an automatic optical tracking system [34]–[36]. This section is illustrated by Figure 2, which presents the results of a study on head translations in three directions (a and b) [33] and depicts head pitch rotations that compensate for vertical translations (c).

#### A. Directions, shape and amplitude of the oscillations

The studies that have assessed head motion while walking straight have shown that the head does not travel on a linear path, but makes sways and shakes in several directions [31]–[33], [36]. This complex motion includes vertical [31]–[33], [36], lateral and longitudinal [33] translations as well as pitch [31]–[36], roll and yaw [34], [35] rotations. Waters et al. stated that head translations resemble sine waves during locomotion [33], which is consistent with the results of a recent study that used HMD-embedded trackers to measure head motion [37]. Rotations were described as sinusoidal-like as well [35].

Measures of these oscillatory motions have identified amplitudes of 2 to 10cm for vertical translations [31]–[33], [36], 5cm for lateral [33], [35], less than 1cm for longitudinal [33], 3 to 8.5° for pitch rotations [31], [32], [36], and less than 3° for yaw [35]. In addition, one of the studies showed that, as walking speed increases, longitudinal translations get smaller, vertical translations larger, and lateral translations do not change much [33].

#### B. Temporal characteristics of the oscillations

Studies have also analyzed the temporal characteristics of head motion while walking, using the step cycle and the stride cycle as references. The former is bounded by two consecutive heel strikes (e.g., right heel strike to left heel strike), while the latter corresponds to two consecutive step cycles (e.g., right heel strike to next right heel strike). These studies have shown that the predominant frequency of the vertical translation [31]–[33], [36], pitch rotation [31], [32], [34], [36] and longitudinal translation [33] are close to the step frequency (around 2 to 2.5Hz [31], [32], [36]), while that of the lateral translation [33], yaw and roll rotation [34] are close to the stride frequency (around 1Hz [31], [32], [36]). These ranges are given as an order of magnitude and vary with walking speed and style.

Regarding phase, Waters et al. described when translation minima and maxima occur for each axis as fractions of the step cycle [33]. For instance, the vertical translation reached a minimum at 17% of the step cycle (0% for right heel strike, 100% for left heel strike) [33]. These relative timings are reported on Figure 2a. It should be noted that while the authors characterized the translation as sine waves, they also reported that the relative longitudinal position increased during 41% of the step cycle and decreased during 59%. On Figure 2a, longitudinal and vertical translations are thus represented as a concatenation of portions of sinusoidal curves. Figure 2b represents the resulting oscillating pattern when projected on the frontal plane (plane defined by the vertical and lateral directions), starting from the red arrow at $t = 0\%$. In another paper by Cappozzo, head motion during walking at different speeds was recorded [38], and the resulting head motion patterns were described for all planes, but since longitudinal translations are small and often not implemented (see section IV), we choose not to report on these patterns. It should also be mentioned that the amplitudes and relative timings on Figure 2a and Figure 2b correspond to the results of a study conducted on 5 young male subjects at a walking speed of 1.11m/s [33], and that they should not be taken as a definitive reference, as they were shown to vary between individuals and with walking speed [33]. Instead, this figure should serve as an illustration of typical translation patterns while walking.
### C. Compensation mechanisms and fixation points

In the literature, pitch rotations (around the *x* axis) of the head have been shown to compensate for its vertical translation [31], [32], [35], [36], which provides a more stable optic flow and gravitational reference [36]. As a consequence, during locomotion and when fixating a given point, the direction that the head is facing always intersects the same approximate point ahead of the body, called the head fixation point [31], [32], [35], [36] (see Figure 2c). The distance between the body and this point, referred to as the head fixation distance, tends to increase with the distance to the gaze's target and varies between subjects [31]. The roll rotations of the head (around the *y* axis) were also shown to compensate for lateral translations [35]. In addition to these head motions, complex mechanisms cause eye movements that compensate for residual motion to keep fixated objects static [31], [35].

## IV. IMPLEMENTATION OF VIEWPOINT OSCILLATIONS

In past work, viewpoint oscillations have been implemented in virtual environments using different methods. In this section, we describe these methods (model-based, tracking-based, animation-based) and give guidelines to describe future implementations. This section does not focus on the hardware-related aspects of the implementations (sensors, displays, etc.), rendering engines, or latency. Moreover, the technical challenges of mixing viewpoint oscillations and a virtual avatar, see section IX.

### A. Model-based viewpoint oscillations

In the studies that assess the effect of viewpoint oscillations on users, the most common method is to directly simulate them using mathematical models, which we call model-based viewpoint oscillations. Such models are periodic functions characterized by shape or wave form, direction, frequency, amplitude, and phase when necessary (i.e., when several periodic functions are considered, e.g., on separate axes). These periodic changes can be applied to one or more axes, either as translations and/or as rotations of the viewpoint.

As far as the shape of the oscillations is concerned, most articles have used sine waves [11], [13], [14], [16], [18]–[21], [23], [24], [29], [37], [39]–[44] (Figure 3 b and c) or sine-based functions [10], [37] (Figure 3d), but also triangular waves [15], [16] (Figure 3e). Some papers reported using a triangular velocity profile over time, which, in terms of displacement, results in a sine-like curve composed of parabolic curves [26], [28], [45]. Regarding directions, most of the articles we discuss implement vertical and/or lateral oscillations and, less often, longitudinal oscillations. When specifically designed to represent walking, all of the implementations we discuss used frontal plane oscillations (i.e., lateral and vertical) [13], [14], [19], [37], [46] or oscillations in three directions [11], [20], [41], [42], [46]–[48].

Figure 3 presents representative examples of viewpoint oscillations from the literature. The figure shows that various amplitudes have been used. In addition, it highlights how phase offsets between axes and oscillation shapes impact the pattern that oscillations draw when projected on the frontal

plane, which greatly varies as a result. Moreover, we can see that all of these examples differ from what Waters et al. measured when studying real head oscillations during walking (Figure 2a and b), e.g., with a larger longitudinal amplitude or discontinuities in the trajectory.

In the literature, only six articles have implemented viewpoint rotations [11], [18]–[20], [43], [46]. In some of these papers [11], [19], [20], rotations were applied to the viewpoint to compensate for viewpoint translations and keep a virtual point static at the center of the display, similarly to the concept of head fixation point presented in section III (see also Figure 2c). The same principle was also extended using a gaze tracker: the point kept static was the target of the user's gaze [19].

Overall, this implementation method allows for a large variety of oscillations and gives total control over the result, but building complex models that perfectly correspond to natural walking may require more work than other methods.

### B. Tracking-based viewpoint oscillations

A method that guarantees the fidelity of viewpoint oscillations to walking biomechanics is to measure a person's actual head motion while walking overground [7], [8], [12], [37], [49], on a treadmill [17], [30], [50], or walking in place [30], and apply it to the viewpoint, which we call tracking-based viewpoint oscillations. However, this method is dependent on the measuring tool and on the walking style of the considered person, and past work showed that the resulting viewpoint oscillation can sometimes contain unpredictable motion unapreciated by users [37]. Thus, it may be beneficial to process the motion data before it is used. Such processing may involve using filters like low-pass filters or sliding windows to smooth the tracking data, but no work in the literature discusses such implementations.

When the user is currently performing a walking-like motion [17], [30], [50], or more generally, an oscillatory motion of the head [22], [51]–[57], tracking devices such as HMD-embedded trackers can be used to measure the head's motion and apply it to the viewpoint in real-time, which also results in oscillations of the viewpoint. In normal, lag-limited, tracking conditions, even unpredictable motion should not increase cybersickness since both visual and motion-related vestibular information match [58]. When the user's head motion is tracked, viewpoint oscillations may also be integrated into the visual stimulation using other implementation techniques [4], [13]–[17], [29], [41], [42], [47], [59]. In this case, the visual stimulation combines the user's actual motion captured by the tracking device and the simulated viewpoint oscillations.

Overall, this method guarantees the naturalness of the oscillations regarding walking biomechanics, but recordings of head motion while walking may contain unpredictable displacements that could benefit from being preprocessed. Motion data can also be used to produce character animations that can also serve as a reference to generate viewpoint oscillations, as described in the following subsection.
### C. Animation-based viewpoint oscillations

In the field of embodied VR, i.e., when the user is represented in the virtual environment by an avatar, a popular approach to implement viewpoint oscillations is to apply a natural animation of a walking character to the user's avatar [4], [9], [60], [61]. Then, what we call animation-based viewpoint oscillations are generated by applying the avatar's head position and/or orientation to the viewpoint. These viewpoint oscillations are, by design, synchronized and consistent with the walking avatar's motion.

Several methods exist to animate walking characters [62], some of which are based on recordings and others are not. If the animation is not based on measures of a real walking person, the resulting viewpoint oscillations are not guaranteed to be faithful to walking biomechanics. For instance, Figure 3a presents the oscillation resulting from the “Standard Walk” animation from Mixamo<fnref n="2" />, applied to a 1.75m virtual human in Unity. This figure shows that the lateral and vertical oscillations are natural, which results in a similar frontal plane pattern as the reference presented on Figure 2b. However, the longitudinal oscillation's amplitude is too large, and its frequency is two times too low, which results in a slight limping-like motion: the head is ahead of the body during the right step and lags behind during the left.

Animation-based viewpoint oscillations can be adapted. For instance, if their magnitude is too large, it may be attenuated by applying only a fraction of it relative to a reference [4], [9], [60], [61]. Researchers may also choose to cancel certain directions of oscillation [4] or apply only translations and not rotations [4], [9], [60], [61]. However, making substantial changes may break the consistency between the oscillations and the animation.

Overall, while this method results in oscillations that are consistent with the avatar's walking animation, it gives less control over the oscillations and there is little guarantee that they will be faithful to real walking.

### D. Guidelines for characterizing viewpoint oscillations

Viewpoint oscillations have been described in many different ways, and it can be difficult to understand their implementation or to compare articles. In this subsection, we suggest guidelines for describing viewpoint oscillations that could help avoid ambiguities.

Some articles have characterized viewpoint oscillations with velocity over time or peak velocity instead of displacement over time and amplitude. For comparison purposes, amplitude can be computed from frequency and velocity, and reciprocally. When peak velocity is provided for a sinusoidal oscillation [21], [40], [63], peak-to-peak amplitude can be computed as follows: $A = v_{peak}/(\pi \times f)$. In this article, amplitude always refers to peak-to-peak amplitude. When oscillation velocity follows a triangular profile [45], it can be computed as a function of peak-to-peak velocity: $A = v_{amp}/(8f)$. In addition, some articles from the field of vision describe oscillations in terms of field of view angle [18], [23], [39],

<figure><img src="image_4.png" /><figcaption>Fig. 3. Representative viewpoint oscillations from the literature: (a) “Standard Walk” animation from Mixamo<fnref n="2" />, (b) Lecuyer et al. [11], (c) Palmisano and Riecke [59], (d) Liu et al. [37], (e) Bossard et al. [15] (positive values represent the rightward, forward, and upward direction). Pattern projected on the frontal plane on the right.</figcaption></figure>

[43], [44], [64], which can be difficult to convert to distance, or even makes it ambiguous whether the oscillations were implemented as rotations or translations of the viewpoint [18], [23]. Others describe the oscillation or the forward speed in terms of “unit” or “unit/s” [22], [27], [51], [54].

To be reproducible and understandable, we suggest that model-based viewpoint oscillations should be associated with a frequency, amplitude, and shape. In addition, phase should be reported when several oscillations are combined, as the resulting pattern greatly varies with phase changes (see Figure 3). It should be clear if the amplitude refers to peak-to-peak amplitude or not. The most accurate way to describe model-based oscillations would be to use a mathematical formula. One drawback of using such a representation is that complex formulas could be misleading or hard to picture on their own. We suggest that tracking-based, animation-based, and complex model-based oscillations would benefit from graphical representations. Figure 3 shows examples of graphical representations that give straightforward information on amplitude, period and phase for each axis. This representation could also be complemented with precise values for the various parameters. In addition, if an avatar is used, viewpoint oscillations should be linked to the walking animation of the avatar in some way, like on Figure 2a and Figure 3a. Taken together, following our guidelines would result in such descriptions:

**Model-based oscillations:** Both lateral and vertical translations are sinusoidal and are computed using the following function:

$$A/2 \times \sin(2\pi ft + \phi)$$

<footnote n="2">²https://www.mixamo.com</footnote>
$A = 4.4\text{cm}, f = 1\text{Hz}$ for lateral, and $A = 2.2\text{cm}, f = 2\text{Hz}$, and $\phi = 0$ for both. The resulting translations and frontal plane pattern are plotted in Figure 3c.

*Animation-based oscillations:* [Describe the implementation method and give the animation used]. The result is plotted on figure 3a. The viewpoint oscillates in all directions at a frequency of 0.86Hz with amplitudes of 3.64cm, 6.43cm, and 6.17cm for lateral, longitudinal, and vertical axes, respectively.

## V. EFFECTS OF VIEWPOINT OSCILLATIONS ON WALKING SENSATION

A variety of terms have been used to refer to the subjective quality of experience related to walking in VR simulations or the compellingness of the illusion of walking, including “walking sensation” [10], [11], [20], “walking perception” [65], [66], “walking illusion” [14], “walking impression” [61], “walking realism” [41], [47] and “walking naturalness” [67]. In this paper, we use the term *walking sensation*, which has been used often in the literature and straightforwardly refers to the user’s subjective experience. Besides, we note that walking sensation has been evaluated using various subjective metrics such as Likert (“I felt like I was walking”) [4], [19] or Visual Analog scales (“I felt like I was walking forward”) [8], or by ranking the conditions with regards to this criterion [11], all of which are reported in this section.

<figure><img src="image_5.png" /><figcaption>Fig. 4. Examples of visual stimulation used in studies that evaluate viewpoint oscillations</figcaption></figure>

### A. General effect of viewpoint oscillations on walking sensation

The first studies that assessed the effect of viewpoint oscillations on walking sensation while static were conducted using low-immersion devices such as monoscopic screens of various sizes [11], [19], [20]. For instance, when observing a walking simulation in a virtual environment on a small screen (Figure 4d), vertical oscillations were ranked higher by participants in terms of walking sensation than no oscillations [11]. Lateral and longitudinal oscillations also tended to be ranked higher than no oscillations, but the difference was not statistically significant [11]. In the same article, oscillations in three directions were also ranked higher than no oscillations [11]. In a subsequent study, oscillations in three directions induced more walking sensation than no oscillations when using a large curved screen and a different virtual environment (Figure 4e) [20]. In addition, frontal plane oscillations elicited more walking sensation than no oscillations in another using a large curved screen [19].

More recently, studies have been conducted using HMDs [4], [41], [47] which show more indefinite results. During the passive observation of a walking simulation [47] and during the evaluation of a controller-based locomotion technique [41], walking sensation tended to be higher with oscillations in three directions than without, but the difference was not significant. In a study in which users embodied a virtual avatar, viewpoint oscillations increased walking sensation only when the avatar was observed in third-person perspective, but there was no impact of oscillations in first-person perspective [4]. In section IX, we discuss this study in more detail, with a focus on the use of a virtual avatar.

Overall, these studies show a potential benefit of using viewpoint oscillations on walking sensation, but little evidence supports a benefit when using more immersive displays [High-light - Walking] (for all highlights, see Table II).

### B. Influence of oscillation characteristics

Previous studies have compared the effects of viewpoint oscillations with various characteristics on walking sensation [11], [19], [24], [41], [46]. For instance, three studies have been conducted on the direction of the oscillations [11], [41], [46]. Vertical oscillations were ranked higher than lateral oscillations regarding walking sensation when using a small screen [11]. They also tended to be ranked higher than longitudinal oscillations, but the difference was not statistically significant [11]. During a study on a controller-based locomotion technique, Sarupuri et al. showed that walking sensation tended to be higher for oscillations in three directions compared to frontal plane-only and vertical-only, but the effects were not significant [41]. Finally, de Barros et al. compared different combinations of oscillation directions, which resulted in various patterns, including frontal plane infinity-like, u-shaped, and n-shaped patterns, vertical translations, and translations and rotations in three directions [46]. Their results suggested that the infinity pattern was judged most realistic, but no thorough statistical analysis was reported [46].
The influence of oscillation frequency and amplitude on walking sensation was evaluated in a single study [24]. In this study, five combinations of these parameters were compared for vertical oscillations during treadmill walking [24]. While no statistical analysis was reported, the oscillation patterns that induced the most walking sensation was (40cm, 1Hz), then (40cm, 2Hz), the one that induced the least was (72cm, 2Hz), and (40cm, 0.67Hz) and (8cm, 2Hz) were in-between [24].

Finally, Lécuyer et al. have proposed to add viewpoint rotations that compensate for translations in three directions [11], similarly to compensation mechanisms that occur during natural walking (see subsection III-C). In an evaluation of the system using a small screen, adding a compensation tended to increase walking sensation compared to translations only, but the difference was not significant [11]. In a follow-up study using a large curved screen, adding compensatory rotations to frontal plane oscillations elicited significantly more walking sensation only when the compensation was based on the target of the user's gaze instead of being locked at the center of the screen [19].

Overall, evidence suggests that walking sensation benefits from the use of compensatory rotations based on gaze direction [Highlight - Rotations] and that of vertical viewpoint oscillations compared to lateral [Highlight - Direction].

### C. Influence of other sensory stimulation

Audio and haptic stimulation were combined with viewpoint oscillations in a study by Peng et al. [47]. Their results showed that viewpoint oscillations induced significantly more walking sensation when presented along with step sounds or vibrations to the head, despite not significantly increasing walking sensation on their own [47]. A study by Amemiya et al. investigated viewpoint oscillations combined with vestibular stimulation induced by passive whole-body motion with a seat attached to a motion platform and head tracking with HMD-embedded trackers [10]. This sensory stimulation elicited a higher walking sensation than the static condition without oscillations, and the walking sensation was higher for low amplitudes of passive motion [10].

Overall, additional and consistent sensory stimulation seems to render simulations that induce even more walking sensation [Highlight - Sensory].

## VI. EFFECTS OF VIEWPOINT OSCILLATIONS ON VECTION

Vection can be defined as the “visually-mediated perception of self-motion” (either real or illusory) [68]. Since virtual walking involves motion in a virtual environment, vection is part of the complex, multi-sensory experience of virtual walking. The effects of viewpoint oscillations on vection have been largely studied in the past [69].

Most studies from the field of vision involve monoscopic (2D) large projection screens placed at a close distance from static observers, observers making active head movements, or walking on treadmills [69]. Results have also been obtained using more immersive displays [55], [56], [59]. Usually, these studies present a point cloud moving towards and past the observer at a constant speed (see Figure 4a), that matches

the treadmill's speed when one is used. This abstract visual stimulus, or “optic flow”, is characterized either as radially-expanding – since the resulting visual pattern has objects move away from the center –, or as linear – since the simulation corresponds to a linear displacement. Since most of these studies do not aim at simulating human walking, some of the reported viewpoint oscillations have characteristics that are far from natural (see Figure 2). Studies from the field of VR and human-computer interaction have also assessed the effects of viewpoint oscillations on vection as part of the subjective experience of walking [4], [15], [16], [20], [29], [42]. These studies use more natural oscillation characteristics and virtual environments, such as dotted planes [20] (see Figure 4e), grassy planes [41] (see similar environment in Figure 4f) or hills [4], and virtual tunnels [15]–[17] (see Figure 4b). In addition to vection, this section discusses results on connected metrics such as the estimation of travel distances, which tends to be consistently underestimated in virtual environments [70], and perceived speed.

### A. General effect of viewpoint oscillations on vection

The addition of oscillations or jitter – more unpredictable displacements – to a linear optic flow is known to increase vection when observed while static [69], and the vast majority of the studies discussed in this section support this conclusion [12], [13], [18], [21]–[23], [26]–[28], [30], [39], [40], [43]–[45], [50], [59], [64], [71]. Only two studies did not identify a significant effect of viewpoint oscillations on vection [4], [63]. One of these results may be attributed to the fact that a 7-point Likert scale was used to assess vection [4], where a lot of studies use the non-oscillatory stimulus as a reference in the middle of their scale [21]–[24], [27], [30], [39], [40], [44], [50], [51], [53], [54], [57], [64], [71]. As for the other, the authors suggested that elements of the virtual environment could have given clues to the virtual speed, which may have canceled the effect on vection [63].

In addition to vection strength, other metrics like vection onset latency – the time it takes to induce vection from the start of the visual stimulation – and vection duration – the time it takes for the effects to disappear – have been assessed in the past. These effects are largely similar to those observed on vection strength: shorter onset latency [12], [21], [23], [27], [28], [43], [44], [44], [45], [51], [59], [63], [64] and/or longer duration [21], [23], [27], [28], [39], [43], [63], [64] were found with viewpoint oscillations in most studies, even if a small set failed to identify a significant effect on vection onset latency [26], [40], [56], [71] or duration [40], [44].

Estimated travel distance [15]–[17], [20], [29], [41] and perceived speed [26], which both relate to spatial perception, have also been assessed. Both of these metrics were shown to increase with the inclusion of viewpoint oscillations by most studies [15]–[17], [20], [29]. A single study did not find such an effect on estimated travel distance when evaluating a controller-based locomotion technique [41]. This result may be explained by the relatively low amount of visual cues (see similar environment in Figure 4f) or by the procedure called the “triangle completion task”, which had users follow
a triangular path, contrary to other studies that used linear trajectories [15]–[17], [20], [29].

Overall, strong evidence supports the positive effect of viewpoint oscillations on vection strength, onset latency, and duration, as well as estimated travel distance and perceived speed [Highlight - Vection 1]. In the following, we discuss in more detail the effects of viewpoint oscillations on these metrics depending on the characteristics of oscillations and the user's body motion and posture.

## B. Influence of transform and direction

Several types of viewpoint oscillations have been explored in studies on vection regarding transform – translation or rotation – and direction [21], [27], [29], [39], [43]–[45], [53], [71]. For instance, large lateral oscillations in translation and in rotation (yaw) were both shown to increase vection, and no significant difference between the two was identified in a study by Kim et al. [71]. However, large roll oscillatory rotations induced a stronger vection than lateral oscillatory translations of comparable amplitude [43].

As for directions, frontal plane oscillations – i.e., lateral and vertical – were shown to have more impact on vection than longitudinal oscillations [45]. Similarly, a stronger vection was elicited by the observation of lateral oscillations, but it was not the case for similar longitudinal oscillations [53]. In a study that simulated vertical motion instead of longitudinal, a stronger vection was induced by lateral oscillations compared to vertical oscillations [39]. In another similar study, vertical oscillations decreased vection [44]. These results suggest that oscillations are more beneficial for vection when their direction is orthogonal to the direction of the motion. When moving along the longitudinal axis, lateral and vertical oscillations have also been compared in three studies [21], [27], [29]. There was no difference in vection in two studies [21], [27]. However, Bury et al. showed that triangular vertical oscillations significantly increased the estimated travel distance in the VE, whereas lateral oscillations did not [29].

Overall, oscillations in rotation and in translation both positively contribute to vection, and there is some evidence that rotations may have more impact. There is also evidence that oscillations in the direction of the linear motion have less impact or can even be detrimental to vection compared to oscillations along orthogonal directions. In addition, there may be an advantage of vertical oscillations over lateral [Highlight - Direction].

## C. Influence of frequency and amplitude

Various values for frequency and amplitude have been explored in the literature. Concerning frequency, positive effects on vection have been identified from less than 1Hz [23], [24], [45], [52]–[56], to more than 7Hz [18]. Studies that have compared the effect of various frequencies have shown no significant difference in vection for oscillations with frequencies between 1.8 and 7.4Hz [18], under 1Hz [45], [55], and between 1 and 2Hz [28], which suggests that oscillation frequency does not affect vection strength. On the contrary, a strong positive correlation between oscillation frequency and

vection strength was identified for frequencies under 2Hz, in a study on treadmill walking [24]. In another study, higher frequencies benefited vection for viewpoint oscillations and hindered vection for fixation point oscillations – i.e., with the instruction to fixate an oscillating point – with frequencies under 1Hz [23].

As for amplitude, past work suggests that higher amplitudes of oscillation increase vection [24], [43], [53], [54], [71]. This was shown for oscillations implemented as roll rotations [43] and lateral translations [43], [71], and yaw rotations [71]. However, vertical viewpoint oscillations with amplitudes between 6.25cm and 25cm all yielded similar levels of vection in a study by Seno et al. [28]. During treadmill walking, a strong positive correlation was identified between oscillation amplitude and vection strength for amplitudes between 8 and 72cm [24]. Similarly, when users actually moved their head from side to side [52]–[54] or back and forth [54], integrating these physical oscillations into the motion of the viewpoint with a larger amplitude gain was shown to induce a stronger vection in two out of three studies [53], [54].

Overall, there is evidence that oscillation amplitude positively impacts vection, but the effects of frequency are more contrasted [Highlight - Vection 2]. In addition, since both frequency and amplitude positively influence oscillation speed, these results suggest that oscillation speed may increase vection as well.

## D. Influence of body posture and motion

The influence of body posture and motion on the effects of oscillations on vection has been investigated in past work. Concerning posture, Guterman et al. showed that viewpoint oscillations increased vection in a similar way whether the users were standing, sitting, or lying [21]. However, standing and sitting induced a stronger vection than lying [21].

As far as motion is concerned, viewpoint oscillations have been shown to increase vection not only when autonomous, but also when caused by users' physical head motion [22], [30], [50]–[57] such as when walking on a treadmill [30], [50] or walking in place [30]. Comparisons between motions have also been made [13], [30], [50]. For instance, Kruijf et al. showed that additional frontal plane oscillations increased vection whether the walking was controlled by a joystick or by leaning the body [13]. When walking on a treadmill [30], [50] or when walking in place [30], integrating the user's real head oscillations into the linear motion of the viewpoint was shown to increase vection, and no significant difference was observed between oscillations resulting from treadmill walking and those resulting from walking in place [30]. In addition, the advantage for vection was found to be similar when actively performing these motions and when observing recordings from previous trials while static [30], [50], even if treadmill walking was shown to inhibit vection in some cases [50]. However, when walking on a treadmill, no advantage of integrating the user's real head oscillations into the viewpoint's motion was identified on estimated travel distance in a study using an HMD [17] (see environment in Figure 4b), even though other studies showed positive effects with the static
observation of similar visual stimuli using an HMD [29], or a CAVE-like room [15], [16]. To account for these results, the authors suggest that the contribution of proprioceptive and efferent information caused by treadmill walking predominates over dynamic visual information in the estimation of traveled distance [17].

When users performed oscillatory motions, researchers have manipulated the level of conflict between the physical motion and its translation into visual oscillations, with little effect on vection [51]–[54]. For instance, the direction of the visual oscillation was investigated in two studies [51], [57]. In the first study, when users rotated their head from side to side, integrating these physical oscillations into the motion of the viewpoint in the same direction increased vection, but integrating it in the opposite direction did not [57]. On the contrary, in the second study, when users translated their head from side to side, both methods increased vection similarly [51]. Moreover, little difference in vection was found when integrating the oscillations on an axis that was orthogonal to the physical motion [54]. In addition, integrating a user's head oscillations in-phase or completely out-of-phase seems to induce a similar advantage for vection, as shown in two studies [53], [54]. Similarly, when manipulating display lag between physical motion and visual oscillations, levels of lag that resulted in oscillations closest to in-phase and completely out-of-phase induced more vection than other levels of lag [52]. This result suggests that some level of synchronization between the physical and visual oscillations is beneficial to vection.

Overall, posture and motion do not seem to influence the advantage of viewpoint oscillations on vection, but treadmill walking may cancel the advantage for estimated travel distance [Highlight - Vection 5]. In addition, studies suggest that the advantage for vection is quite robust to some level of conflict between the physical motion and its visual translation [Highlight - Vection 3].

### E. Influence of gaze

Studies have reproduced the advantage for vection brought by viewpoint oscillations by imposing oscillations of the user's fixation point [23], [64], which shows that oscillations in gaze direction can also improve vection without simulated viewpoint oscillations. In addition, Palmisano and Kim have investigated the influence of gaze behavior, i.e., where the user is looking, during the passive observation of an oscillating optic flow [27]. Their results showed that oscillations similarly improved vection whether observers fixated the center or the periphery of the display and that alternating between the two increased vection further [27], which seems consistent with the results on fixation point oscillations [23], [64]. More generally, by comparing various combinations of the fixation point and viewpoint oscillations, Nakamura showed that it is the oscillation of the stimulus on the user's retina that benefits vection rather than the viewpoint oscillations per se [64] [Highlight - Vection 4]. While this conclusion could have suggested that users may compensate for viewpoint oscillations with eye motion when not instructed to fixate a

static point, Kim et al. found no effect of whether participants were instructed to fixate the center or not [43]. In addition, there have been numerous accounts of studies that did not provide gaze instructions and still found an increase in vection with viewpoint oscillations [12], [18], [21], [26], [45].

### F. Factors breaking the advantage for vection

Among the studies that have tried to explain the advantage for vection brought by viewpoint oscillations and jitter, some have tested the limits of these effects [25], [39], [40]. These studies concluded that the combination of the oscillating motion and the linear motion needs to be consistent over all objects in the scene in order to achieve this increase in vection [25], [39], [40]. In particular, Nakamura showed that the objects' visual oscillation must be in phase and share the same amplitude [39], and that all objects must be applied both the oscillation and the linear motion, rather than applying the oscillation to some and the linear motion to others [40]. In addition, in a study on jitter, Palmisano et al. showed that, at a given time, all objects should be displaced along the same direction and distance, and that this distance should be visually consistent with objects' depth in the virtual environment [25].

Overall, the factors necessary for achieving this advantage for vection are met when considering our scope: an oscillation of the point of view combined with a translation in a given direction relative to other objects.

### G. Influence of oscillation naturalness

Several studies have evaluated viewpoint oscillations relatively faithful to walking biomechanics. For instance, the addition of oscillations specifically designed to represent walking in a natural way was shown to improve the accuracy of estimated travel distance [20]. Similarly, Bubka and Bonato showed that viewing a video shot with a hand-held camera, which thus contains real gait information, induced a stronger vection than viewing an equivalent video shot with a rolling camera [12] (see similar environment in Figure 4c). Bossard et al. investigated whether the naturalness with regards to real walking was necessary to improve the accuracy of estimated travel distance in two consecutive studies conducted with a CAVE-like immersive room [15], [16]. These studies showed that 3D sinusoidal oscillations and vertical triangular oscillations both elicited a similar improvement in estimated travel distance [16], and that inverting the ratio of frequency between vertical and lateral translations had no effect on this improvement [15].

Overall, these results suggest that naturalness does not impact the effect of viewpoint oscillations on estimated travel distance [Highlight - Vection 4].

## VII. EFFECT OF VIEWPOINT OSCILLATIONS ON CYBERSICKNESS

Cybersickness is a set of symptoms related to disorientation, nausea, and oculomotor effects that emerge from exposure to VR [58]. Davis et al. made a distinction between “motion sickness”, “simulator sickness”, and “cybersickness”, which
all relate to similar symptoms but are respectively caused by traveling on a moving vehicle, using a flight simulator, or being exposed to VR. In the remainder of this paper, and for readability purposes, we use the term “cybersickness”. Several theories have been suggested to account for cybersickness, such as the sensory conflict theory, which states that cybersickness is caused by a conflict between the visual and vestibular senses [58]. According to this theory, adding visual oscillations inconsistent with vestibular information about head motion should increase sensory conflict and, thus, cybersickness. However, this is not the case in all studies, as presented in this section.

### A. General effect of viewpoint oscillations on cybersickness

Compared to vector, fewer studies have assessed the effect of observing viewpoint oscillations while static on cybersickness [13], [18], [20], [41], [42], [47], [49], [59]. Two studies have shown that adding viewpoint oscillations to a linear optic flow increases cybersickness [18], [49]. For instance, this was the case for small vertical oscillations observed on a projection screen [18]. Similarly, when observing 360° videos with an HMD, stabilizing the camera, which eliminated walk-related oscillations from the optic flow, was found to decrease cybersickness [49].

However, other studies have not identified a significant effect of observing viewpoint oscillations on cybersickness [13], [20], [29], [59]. For instance, small frontal plane oscillations tended to increase cybersickness when viewed on a large distant screen, but the difference was not statistically significant in a study by Palmisano and Riecke [59]. In a subsequent study, observing the same visual stimuli with an HMD induced almost no cybersickness, whether oscillations were included or not [59]. However, the authors highlighted the rather short exposure time of the trials (30s) and the fact that cybersickness did increase with repeated exposure to the stimuli [59]. Similarly, in two other VR studies, cybersickness remained low with and without viewpoint oscillations, which did not significantly differ [13], [29]. However, one of these evaluations was part of a more complex experimental design that also evaluated other consistent sensory stimulation, such as audio (footstep sounds) and haptics (various vibrations on feet), and gave control over the virtual motion with a joystick or a leaning motion [13]. Since adding consistent multisensory stimulation seems to reduce cybersickness, as discussed in subsection VII-C, this experimental design may have contributed to hiding an effect of oscillations on cybersickness. Finally, small viewpoint oscillations did not significantly impact cybersickness when observed on a large curved screen [20]. However, the authors mention that participants were disturbed by a visual element present in all conditions, which may have overridden the potential effect of the oscillations [20] (see Figure 4e). In addition, the viewpoint oscillations used in the study included rotations designed to compensate for the translations and keep the center of the display stationary, which may have been less disturbing than translatory-only oscillations.

On the contrary, some studies have suggested that viewpoint oscillations tend to decrease cybersickness [41], [42], [47]. For

instance, Peng et al. showed that, during the observation of a walking simulation in VR, viewpoint oscillations tended to induce lower levels of cybersickness than linear displacement, although not significantly [47]. In two papers, Sarupuri et al. evaluated the effect of TriggerWalking, a trigger-based locomotion technique with viewpoint oscillations [41], [42]. Their results showed that, while the difference between the conditions was not statistically significant, cybersickness tended to be lower with oscillations in three directions (vertical, lateral, and longitudinal) than without oscillations [41]. Their technique also induced significantly less cybersickness than joystick [41], [42] and keyboard control [42], which did not include viewpoint oscillations.

In the following, we discuss these contrasted results and factors that may account for them. To support this discussion, the eight articles examined in this section are presented and compared in Table I. It includes the characteristics of the oscillations, the visual stimulation – forward speed, display characteristics, and scene content –, the locomotion technique (if any), and details of the procedures – trial duration, cybersickness evaluation method, number of participants and experimental design, and the effect on cybersickness. From this general view, some of the results without significance may be explained in part by short exposures to the visual stimuli [13], [20], [41], [59]. The table also shows the variety of scales used to assess cybersickness, which includes the Simulator Sickness Questionnaire (SSQ, 16 items) [72], the Subjective Symptoms of Motion Sickness (SSMS) [73], and single items such as the Fast Motion Sickness scale (FMS) [74]. Interestingly, Palmisano et al. identified almost no effect on cybersickness when using an HMD, while viewpoint oscillations tended to increase cybersickness when observed on a monoscopic screen [59]. Moreover, all of the decreases in cybersickness with oscillations were identified in studies using HMDs [41], [42], [47]. In Palmisano et al.'s study, this difference could be attributed to variations in the procedures, such as the number of participants and blocks, but the display characteristics may also have played a part. In addition, three of the studies evaluated the effect of oscillations as part of a locomotion technique [13], [41], [42]. This implies that users were given control over the virtual motion and that there were changes in advance speed and direction during the trials [13], [41], [42]. Since two of these studies yielded rather positive results [41], [42] and the third showed no effect with an overall low level of cybersickness [13], the degree of control and/or the irregular advance speed may be factors of interest for explaining these contrasted results. Moreover, in two of these studies, the considered conditions correspond to different locomotion techniques with various speed and direction controls in addition to including viewpoint oscillations or not [41], [42], which makes it difficult to isolate the effect of oscillations only. Future work needs to be conducted to explore these research leads.

Overall, studies on the effect of viewpoint oscillations on cybersickness have found contrasted results [Highlight - Sickness 1]. Six studies identified no significant difference with and without oscillations [13], [20], [29], [41], [47], [59], two identified an increase in cybersickness with oscillations
<caption>TABLE I
COMPARISON BETWEEN STUDIES ON THE GENERAL EFFECT OF VIEWPOINT OSCILLATIONS ON CYBERSICKNESS (AMBIGUITIES ARE DOTTED).</caption>

OSCILLATION PARAMETERS: *T* AND *R* FOR PEAK-TO-PEAK AMPLITUDE OF TRANSLATION AND ROTATION, *f* FOR FREQUENCY, *φ* FOR PHASE AS USED IN 2π*f* + *φ*. LOCOMOTION TECHNIQUE: JS FOR JOYSTICK, DIR. FOR DIRECTION, CTLER FOR CONTROLLER. EFFECT OF OSCILLATIONS ON CYBERSICKNESS: INCREASED (↗), DECREASED (↘), NO SIGNIFICANT EFFECT (Ø), NO EFFECT (Ø).

<table><thead><tr><th>Ref</th><th>Oscillation parameters: f (Hz),<br>T (cm), R (°), φ (rad)</th><th>Speed</th><th>Visual<br>Display</th><th>Scene</th><th>Locomotion<br>technique</th><th>N</th><th>Procedure</th><th>Effect on<br>cyber.</th></tr></thead><tbody><tr><td>[18]</td><td>Sin, x, f = 1.8/3.7/7.4,<br>R = 9</td><td>7<br>m/s</td><td>Screen, 2D,<br>46° × 38°</td><td>Point<br>cloud</td><td>None</td><td>18</td><td>10min trials, SSQ before and after trial,<br>SSMS and 0-10 item every 2min</td><td>↗</td></tr><tr><td>[49]</td><td>Oscillations from walking</td><td>NA</td><td>HMD, 2D,<br>101°</td><td>Nature<br>video</td><td>None</td><td>50</td><td>10min trials, Yes/No then SSQ after trial</td><td>↗</td></tr><tr><td>[59]</td><td>Shape NA, T = (4.4, 0, 2.2),<br>f = (1, 0, 2), φ = (0, 0, 0)<br>(∞ shape)</td><td>1.1<br>m/s</td><td>Screen, 2D,<br>71° × 41°</td><td>Point<br>cloud</td><td>None</td><td>23</td><td>40s trials × 2 oscillations × 4 blocks,<br>Yes/No then FMS after trial</td><td>↗ (ns)</td></tr><tr><td></td><td></td><td></td><td>HMD, 3D,<br>100° diag.</td><td></td><td></td><td>13</td><td>Same with 3 blocks</td><td>Ø</td></tr><tr><td>[20]</td><td>Sin, T = (2.5, 2.5, 6),<br>f = (0.75, 1.5, 1.5),<br>φ = (0, 0, π/2), compensatory<br>rotations wrt. display center</td><td>1.2<br>m/s</td><td>Screen, 2D,<br>55° × 45°</td><td>Dotted<br>plane</td><td>None</td><td>12</td><td>4-11s trials × 2 oscillations × 4 travel<br>distances × 7 blocks, 7-point Likert item<br>after experiment</td><td>Ø</td></tr><tr><td>[47]</td><td>From ref. [11], [48]: Sin,<br>f = (0.625, 1.25, 1.25), φ, T<br>NA</td><td>2/4/6<br>m/s</td><td>HMD, 3D,<br>110° diag.</td><td>City /<br>Forest /<br>Spaceship</td><td>None</td><td>240</td><td>Between-participants (8 conditions), 9min<br>trials, 0-10 item every 20s, SSQ before and<br>after experiment</td><td>↘ (ns)</td></tr><tr><td>[13]</td><td>Sin, T from ref. [75], f<sub>y</sub> = 2 ×<br>f<sub>x</sub>, f<sub>z</sub> = 0, φ = (0, 0, 0) (∞<br>shape)</td><td>Var.</td><td>HMD, 3D,<br>93° × 99°</td><td>Virtual<br>forest</td><td>JS / Leaning for<br>speed and dir.</td><td>12</td><td>10s trials × 2 oscillations × 2 controls × 3<br>foot stimuli × 2 blocks, 0-10 item after trial</td><td>Ø</td></tr><tr><td>[41]</td><td>Sin, T = (11.5, 5.7, 0.1 ×<br>height), f<sub>y</sub> = f<sub>z</sub> = 2 × f<sub>x</sub><br>(variable f)</td><td>Var.</td><td>HMD, 3D,<br>113° diag.</td><td>Grass<br>plane</td><td>Trigger for speed,<br>Ctler for dir.</td><td>24</td><td>10-14s trials, 4 oscillations × 18 paths, 0-<br>10 item after each oscillation</td><td>↘ (ns)</td></tr><tr><td></td><td></td><td></td><td></td><td>House<br>interior</td><td>Same / JS for<br>speed, head for dir.</td><td>16</td><td>3min trials × 4 navigation techniques, SSQ<br>after condition</td><td>↘</td></tr><tr><td>[42]</td><td>Same as previous with T<sub>y</sub> = 0</td><td>Var.</td><td>HMD, 3D,<br>113° diag.</td><td>House<br>interior</td><td>Trigger for speed,<br>Ctler for dir. /<br>On/Off / JS for<br>speed, Head for dir.</td><td>15</td><td>3min trials × 3 locomotion techniques, SSQ<br>before experiment after condition</td><td>↘</td></tr></tbody></table>

[18], [49], and two showed that a controller-based locomotion technique with oscillations induced less cybersickness than other static locomotion techniques without oscillations [41], [42]. Among the six studies that identified no significant effect on cybersickness, one showed that viewpoint oscillations tended to increase cybersickness [59], and two showed that they tended to decrease cybersickness [41], [47]. Without a definitive conclusion, researchers who consider using viewpoint oscillations should evaluate whether their implementation does increases cybersickness.

## B. Influence of oscillation parameters

Different implementations of viewpoint oscillations have been compared with regard to cybersickness. This includes studies on the influence of oscillations' direction [41], frequency [18], [55], [57], and implementation technique [37]. Concerning oscillations' direction, Sarupuri et al. compared various oscillation directions for TriggerWalking, a locomotion technique that includes viewpoint oscillations [41]. Their results showed that oscillations in three directions (vertical, lateral, and longitudinal) tended to induce less cybersickness compared to vertical-only, vertical and lateral, and no-oscillation, but the difference between the conditions was not statistically significant [41].

As for frequency, viewpoint oscillations with higher frequencies seem to increase cybersickness since 3.7Hz and 7.4Hz induced more cybersickness than 1.8Hz oscillations in a study that identified an increase in cybersickness with oscillations [18]. Similarly, when users rotated their head from side to side with various amounts of display lag in an HMD,

1Hz head motion induced more cybersickness than 0.5Hz motion [55]. However, this result concerned the main effect of frequency over all levels of lag, not only the stimulation with no display lag [55], which makes it more difficult to a draw general conclusion on oscillation frequency. In addition, cybersickness, which is related to sensory conflict [58], was probably influenced by proprioceptive and efferent information caused by real head motion [55]. This is discussed, along with the influence of other sensory stimulation, in the next subsection.

Various implementation techniques were explored in a study using an HMD: recording one's own or another's head motion while walking – i.e., tracking-based techniques –, or building a model based on the recordings – i.e., model-based [37]. The results showed that the two tracking-based implementations induced more cybersickness than the model-based implementation, which, as verbal feedback suggested, was related to the presence of unpredictable jitter in the recordings [37]. These results may help explain the increase in cybersickness with oscillations identified in another study on 360° videos since it also assessed the effect of tracking-based viewpoint oscillations [49].

Overall, viewpoint oscillations in three directions seem to elicit less cybersickness compared to frontal plane and vertical oscillations, as shown in a study that identified a decreased cybersickness with oscillations. In addition, higher oscillation frequencies seem to increase cybersickness, as shown in a study that identified an increase in cybersickness with oscillations. Finally, it seems that tracking-based viewpoint oscillations that contain jitter induce more cybersickness than
smooth oscillations [Highlight - Sickness 2].

### C. Influence of body motion and other sensory stimulation

Various body motions and sensory stimulation, consistent with viewpoint oscillations, have been evaluated in past studies with regards to their effect on cybersickness. In terms of motion, Amemiya et al. explored the effect of passive whole-body motion with a seat attached to a motion platform, which induced vestibular stimulation in addition to viewpoint oscillations as a result of tracking by HMD-embedded trackers [10]. In the evaluation of the system, several amplitudes and frequencies of passive motion were considered [10]. In the results, cybersickness was only reported as correlated to walking sensation and body motion perception, not as a function of motion amplitude and frequency [10]. From the reported results on walking sensation and the links between walking sensation and cybersickness, which are discussed in section X, we can infer that cybersickness tended to be higher with oscillations than without and that higher amplitudes of motion may have caused a stronger cybersickness, although no direct link was made between these variables in the study [10]. This suggests that additional vestibular stimulation induced by passive whole-body motion may be prone to increase cybersickness during walking simulations, especially for large amplitudes [10].

In three studies, a focus was made on active motion, with associated vestibular, proprioceptive, and motor or efferent information [13], [14], [57]. For instance, in addition to evaluating the effect of viewpoint oscillations, Kruijff et al. compared the effect of actively leaning to control the walk and controlling it with a joystick [13]. Their results showed no effect of control mode on cybersickness, which remained low across conditions, nor interaction with the inclusion of viewpoint oscillations [13].

Active cycling was investigated as part of the VR strider, a cycling-based locomotion interface that includes viewpoint oscillations, which was shown to induce less cybersickness than a joystick control without oscillations [14]. This suggests that visual oscillations, when combined with consistent active motion, may decrease cybersickness. However, the procedure does not allow us to identify if the effect can be attributed to the inclusion of viewpoint oscillations, active motion, or an interaction of both factors. Finally, the effect of manipulating sensory conflict between physical motion and visual oscillations was evaluated in a study using an HMD [57]. When users performed large and slow head rotations from side to side, a stronger cybersickness was induced when the viewpoint rotated in the opposite direction along the z axis compared to when it rotated in the same direction (ecological head tracking) or when the yaw rotations were canceled [57]. In addition, the two latter conditions did not induce significantly different levels of cybersickness [57]. This demonstrates the detrimental effect of conflict between visual information and sensory information caused by active motion.

The combination of viewpoint oscillations with other sensory stimulation, such as haptics and audio, has also been studied [37], [47]. Interestingly, Peng et al. evaluated viewpoint oscillations as a part of various sensory combinations

to reduce cybersickness in VR walking simulations, which also included audio and haptic stimulation [47]. Their results showed that viewpoint oscillations tended to reduce cybersickness, although not significantly [47]. However, adding haptic stimulation to the sides of the head as vibrations, either synchronized or not with the oscillations, or as synchronized tapping, significantly reduced cybersickness compared to linear displacement without haptic stimulation, but adding audio had no effect [47]. Similarly, combining viewpoint oscillations and tapping feedback to the head reduced cybersickness compared to oscillations only [37]. Finally, Kruijff et al. investigated audio (footstep sounds) and haptic (various vibrations on the feet) stimulation in VR, but cybersickness was not impacted by any dependant variable, including the use of viewpoint oscillations [13].

Overall, this subsection highlights that passive vestibular stimulation seems to increase cybersickness. Concerning active motion as a way to control walking, active leaning seems to have no influence, and active cycling seems to reduce cybersickness compared to controller-based techniques. When physical oscillatory motion is translated to a visual viewpoint oscillation, introducing a strong sensory conflict between the two increases cybersickness. Finally, adding haptic stimulation to the head seems to reduce cybersickness, whereas audio seems not to [Highlight - Sensory].

## VIII. EFFECT OF VIEWPOINT OSCILLATIONS ON PRESENCE

One of the main measures to assess user experience in VR is known as presence, or the sense of “being there” in the virtual environment [76], which has been investigated in a set of studies on viewpoint oscillations [13], [14], [19], [20], [41], [49], [55]. Three studies have found no effect of observing viewpoint oscillations while static on presence [20], [41], [49]. For instance, oscillations in three directions did not significantly impact presence in a study using a large curved screen [20]. Similarly, eliminating oscillations caused by walking from 360 videos did not affect presence either [49]. However, a controller-based VR locomotion technique with viewpoint oscillations in three directions tended to induce more presence than joystick control without oscillations, although not significantly [41]. Two studies have shown a positive effect of viewpoint oscillations on presence [13], [19]. When observed on a large curved screen, frontal plane oscillations were found to increase presence and increase it further when compensatory rotations were introduced to keep the center of the screen static, and even further when the eyes' fixation point was used as reference [19]. Kruijff et al. also showed that frontal plane viewpoint oscillations increased presence when navigating in VR with a joystick or when leaning to navigate and when using an HMD [13].

Two studies have assessed the effect of oscillations on presence when users were not static [14], [55]. When users rotated their head from side to side using an HMD, higher levels of presence were elicited for 0.5Hz head oscillations compared to 1Hz, although the results reflected different levels of display lag [55]. In addition, Freiwald et al. found that a VR locomotion technique that combines a cycling motion
with frontal plane oscillations increased presence compared to joystick control [14]. However, this effect may mainly be attributed to the additional user motion and synchronized avatar motion in the VE rather than to the addition of oscillations.

Overall, results suggest a slight positive effect of adding viewpoint oscillations on presence [Highlight - Presence].

## IX. EFFECTS OF VIEWPOINT OSCILLATIONS ON AVATAR EMBODIMENT

An avatar or self- avatar represents the user's body in a virtual environment, which can induce a sense of embodiment in the user [77]. Before discussing the specific effects of viewpoint oscillations when combined with an avatar in VR, we discuss how oscillations have been implemented in relationship to the avatar [4], [9], [14], [60], [61]. As discussed in section IV, the most convenient way to implement viewpoints oscillations in simulations with walking avatars is to use the avatar's animation as the source of the oscillation, i.e., animation-based oscillations. This leads to an oscillation that is by design consistent with the walking animation, but issues related to animation-based oscillations may still occur (see subsection IV-C). Model-based viewpoint oscillations may also be combined with a virtual avatar [14]. In this case, however, oscillations must be manually synchronized in phase and frequency with the avatar's walking. In addition, the resulting oscillations are not guaranteed to correspond exactly to the motion of the avatar's head, which could impair user experience.

The sense of virtual embodiment refers to the feeling of being inside, owning, and controlling the avatar [77]. A single study assessed the effects of viewpoint oscillations on subcomponents of embodiment, namely agency and ownership, in addition to other dimensions of user experience such as walking sensation and vection [4]. This study used animation-based frontal plane oscillations of small amplitude, and the walking avatar was either observed in first-person perspective or in third-person perspective [4]. The results showed that viewpoint oscillations increased walking sensation only when the avatar was observed in third-person perspective, but that there was no difference when the avatar was observed in first-person perspective [4]. To account for this phenomenon, the authors suggest that the benefit in walking sensation induced by observing the walking avatar in first-person perspective may have overridden the smaller benefit brought by the oscillations [4], which is consistent with a recent study that found that observing a walking avatar increased walking sensation only in first-person perspective [3]. In addition, the inclusion of viewpoint oscillations did not affect ownership and had no interaction with the avatar observation perspective [4]. As for agency, there was an interaction between the avatar observation perspective and the inclusion of viewpoint oscillations: viewpoint oscillations decreased agency when the avatar was observed in first-person, but it had no impact in third-person [4]. The authors do not provide explanations to account for this decrease in agency with oscillations [4].

Overall, a study suggests that viewpoint oscillations do not benefit walking sensation nor ownership and reduce agency

when embodying an avatar in first-person perspective [Highlight - Avatar]. We would thus recommend not to use viewpoint oscillations in this context, but additional work should be conducted to investigate the interaction between viewpoint oscillations and avatar observation.

## X. INTERACTIONS BETWEEN THE DIMENSIONS OF USER EXPERIENCE

Previous sections gave a detailed view of the effects of viewpoint oscillations on each dimension of user experience considered separately. This section discusses the links made between these dimensions in five studies from the literature. The studies that assessed the effect of oscillations on several dimensions of user experience without providing a joint analysis are not examined since their results are already discussed in the previous sections.

Walking sensation and cybersickness were both evaluated in a study where seated users were passively moved by a seat attached to a motion platform, which caused vestibular stimulation and viewpoint oscillations in VR [10]. In their results, the conditions with passive motion and viewpoint oscillations increased both cybersickness and walking sensation compared to the static condition [10]. In addition, a negative correlation between walking sensation and cybersickness was identified since larger passive displacements seemed to decrease walking sensation and increase cybersickness [10].

The link between vection and cybersickness when the user is experiencing viewpoint oscillations was evaluated in two studies [18], [59], one of which identified a positive correlation for 1.8Hz oscillations only [18], and the other study identified no such link [59]. In addition, Palmisano et al. showed that an increased sensory conflict between physical oscillatory motion and visual oscillations was associated with a decreased vection and an increased cybersickness, and that both were negatively correlated [57]. More generally, when not considering viewpoint oscillations specifically, a review of the literature concluded that vection can be induced without visually-induced cybersickness, but that visually-induced cybersickness is often associated with a greater likelihood of experiencing vection [78].

As for vection and presence, a single study provides a joint analysis, in which users performed large and slow real head oscillations with different levels of display lag [55]. Vection and presence were found to be positively correlated in this context, as both seemed to decrease with increased display lag [55]. Interestingly, a review showed that presence and cybersickness were negatively correlated in VR, but it also identified vection as a mediating factor in this relationship which makes it more complex [79].

Overall, walking sensation and cybersickness seem negatively correlated when considering the effect of viewpoint oscillations combined with vestibular stimulation induced by passive motion. In addition, there seems to be a positive correlation between vection and cybersickness when a sensory conflict between a physical oscillatory motion and visual oscillations is introduced. More generally, there seems to be a complex relationship between vection, presence, and cybersickness.
<table><caption>TABLE II
TAKE-AWAY MESSAGES REGARDING THE EFFECTS OF VIEWPOINT OSCILLATIONS ON USER EXPERIENCE WHEN WALKING IN VR</caption><thead><tr><th colspan="2">Results supported by several studies:</th></tr></thead><tbody><tr><td>Vection 1</td><td>Viewpoint oscillations benefit vection strength, duration and onset latency, perceived speed and estimated travel distance in virtual environments.</td></tr><tr><td>Vection 2</td><td>Higher amplitudes of oscillation increase vection.</td></tr><tr><td>Vection 3</td><td>When actively moving, the advantage for vection brought by oscillations is robust to some level of conflict between the physical motion and the visual oscillations.</td></tr><tr><td>Vection 4</td><td>The advantage for vection brought by oscillations relies on additional motion on the retina, not on oscillations' naturalness.</td></tr></tbody></table>

<table><thead><tr><th colspan="2">Results supported by some studies or contrasted results (need to be further investigated in future work):</th></tr></thead><tbody><tr><td>Vection 5</td><td>Posture and motion do seem to not have a strong influence on the advantage for vection brought by oscillations, but treadmill walking may cancel the advantage for estimated travel distance.</td></tr><tr><td>Walking</td><td>Viewpoint oscillations increase may walking sensation in VR, but results with HMDs are supported by less evidence.</td></tr><tr><td>Sickness 1</td><td>The effects of viewpoint oscillations on cybersickness are contrasted.</td></tr><tr><td>Sickness 2</td><td>Jitter and unpredictable displacements in tracking-based viewpoint oscillations seem to increase cybersickness compared to smooth oscillations.</td></tr><tr><td>Presence</td><td>Viewpoint oscillations seem to increase presence.</td></tr><tr><td>Rotations</td><td>Compensatory rotations seem to increase presence, and walking sensation as well when rotations are based on gaze direction.</td></tr><tr><td>Direction</td><td>Vertical viewpoint oscillations seem to induce more vection and walking sensation than lateral oscillations. Viewpoint oscillations in the direction of the linear motion do not seem to benefit vection.</td></tr><tr><td>Sensory</td><td>Sensory stimulation consistent with viewpoint oscillations increases walking sensation and, when concerning haptic stimulation to the head specifically, decreases cybersickness.</td></tr><tr><td>Avatar</td><td>When embodying an avatar in first-person perspective, viewpoint oscillations viewpoint oscillations seem not to affect walking sensation and ownership, and decrease agency.</td></tr></tbody></table>

XI. RESEARCH PERSPECTIVES

This section discusses the current gaps in the literature and proposes research topics related to the studies reported in the review in addition to more general perspectives for future research.

A. *Typology of walking sensation*

The section on walking sensation raised several questions with regard to the typology of walking sensation. It is not certain whether all measures of walking sensation refer to the same underlying subjective experience. For instance, observing displacement in a virtual environment on a small distant screen does probably not yield the same subjective walking experience as being immersed in a virtual environment and viewing a walking avatar in first-person perspective (e.g., [11] and [4], respectively). Similar to Slater's argument that types of presence are qualitatively different for two systems that offer different levels of immersion [80], we could argue that the nature of the walking sensation changes with factors such as immersion and the degree of control given over the walking (see review by Nilsson et al. [1]). Future work is therefore needed to properly establish a typology regarding the notion of walking sensation and the subjective experience of walking in VR.

B. *Experimental work*

Our systematic review of the literature highlighted that the effects of viewpoint oscillations on all of the considered dimensions of user experience are not supported by the same level of evidence (see Table II). For instance, although most studies showed that viewpoint oscillations tend to be beneficial for walking sensation, and presence, a high percentage did not identify significant effects: two out of three for studies

on walking sensation using HMDs, and three out of five for studies on presence. Concerning cybersickness, the current literature contains contrasted results, which does not allow us to make definitive conclusions with regards to the effect of viewpoint oscillations. As discussed in section VII and presented in Table I, a number of aspects of the studies could be investigated further in order to explain these results. These factors include exposure time, display type, control over the motion, variability in forward speed, and oscillation implementation. They may also be explained by the too small sample sizes in the studies or effect size trying to be identified, or by the complex protocols with multiple factors that may have hidden some of the effects.

In addition, relatively few studies have compared different implementations and their effects on cybersickness, walking sensation and presence. For instance, even if a generic conclusion on cybersickness may not be possible, future research could be conducted to find implementations that are less detrimental than others and to confirm the detrimental impact of unpredictable jitter in the oscillations. Another characteristic that could benefit from further evaluation is oscillation naturalness, or how close the oscillations are to real walking. Indeed, the characteristics of some of the reported viewpoint oscillations seem far from natural, with too-high longitudinal amplitudes or discontinuities in the trajectories, which could have affected the results. As discussed, two studies by Bossard et al. have suggested that naturalness does not impact estimated travel distance. Similar work could be conducted on other dimensions of user experience, such as walking sensation and, more generally, on users' ability to perceive changes in the oscillations' naturalness. Further studies could also be conducted on rotations that compensate for viewpoint translations, which seem to be beneficial for walking sensation [11], [19]. For instance, this result could
be replicated using more immersive displays in order to confirm that it is applicable to modern VR. In addition, as the advantage for vection was shown to be related to visual motion on the retina (see subsection VI-E), this compensation mechanism may reduce vection, and its effect on cybersickness is uncertain. This could be explored in future work as well.

From a technical standpoint, more complex models for viewpoint oscillations could be built and evaluated in the future, in the continuation of Terziman et al.'s work on viewpoint oscillations adapted to avatar state and locomotion mode [48]. For instance, these models could include variations for accelerations and turns, described in studies on head dynamics during walking [35]. Another lead that was not explored extensively is the customization of viewpoint oscillations. It was suggested by Terziman et al. who developed models to adapt viewpoint oscillations to the type of locomotion and to the user's physiology [48]. Liu et al.'s tracking-based implementation was also an attempt at customizing the oscillations [37].

As far as the sense of embodiment is concerned, only one study was conducted on the effect of viewpoint oscillations in this regard. This study opens leads for future research, since it suggests that, when embodying virtual avatar in first-person perspective, the benefit for walking sensation brought by oscillations is overridden, and that oscillations are overall detrimental to embodiment. Further studies should be conducted to better understand this interaction, for instance by manipulating the degree of control over the virtual walk.

Beyond including avatars in the simulations, more studies could be conducted in ecological contexts instead of isolating the effects of viewpoint oscillations only. This work would show whether the effects still hold when combined with other sensory stimulation such as haptics, which may override the benefit brought by oscillations as the use of an avatar in first-person perspective did with walking sensation [4]. In addition, only five of the reported studies give control over the virtual motion to users [13], [14], [37], [41], [42]. Besides constituting a technical challenge of synchronizing the user's inputs to the oscillations' characteristics and to the virtual avatar, if one is used, it may have an influence on the effects of the oscillations on user experience. The same goes for the tasks that participants were instructed to perform. Aside from the estimation of travel distance along a linear path and detecting vection onset and duration, only a few of the reported studies required users to perform a specific task other than observing the stimulation and rating their perception. These tasks include following a path [13], [37], the triangle completion task that assesses spatial cognition [14], [41], and finding objects in a scene [41], [42]. Exploring whether the tasks have an influence on the perception of the oscillations would thus be beneficial as well. The influence of individual factors may also be explored in future work such as age and gender, which were investigated in a single study [29], or personality traits.

### C. Other dimensions of user experience

Metrics related to physical walking and usability were not included in this review since our interest was the subjective

experience of walking, with a focus on static walking simulations. If viewpoint oscillations were to be implemented to applications with physical walking from users, their impact on stability during walking, which can be assessed using pressure sensors [24], should be analyzed. This is especially important as past work suggests that viewpoint oscillations have a negative impact on walking stability [81]–[87].

As for usability, it may be of interest to the human-computer interaction community, and further reviews may be conducted. To our knowledge, results are scarce on the subject. A single study from our corpus evaluated the effect of viewpoint oscillations on usability and found no effect [13]. Three other studies use oscillations as part of more complex navigation systems, which makes it difficult to isolate the effect of oscillations [14], [41], [42]. Overall, higher scores on the System Usability Scale (SUS) were elicited by a cycling-based locomotion technique with viewpoint oscillations compared to a joystick without oscillations, and similar scores as teleportation [14]. In addition, a controller-based locomotion technique with oscillations did not differ from joystick and teleportation using the NASA Task Load Index [41], [42], but higher SUS scores were elicited compared to other controller-based techniques [42]. More generally, viewpoint oscillations may also be involved in concrete use cases such as medical rehabilitation and virtual visits. In this context, their effect on context-dependent metrics, such as therapeutic outcomes, could be explored.

## XII. CONCLUSION

Viewpoint oscillations are periodic changes in the position and/or orientation of the point of view in virtual environments. With this paper, our goal was to survey the existing techniques and the potential benefits or limitations of using such during walking simulations in VR. We were more specifically interested in the effects of viewpoint oscillations on walking sensation, vection, cybersickness, presence, and embodiment. To this end, we conducted a systematic search of the literature using the OpenAlex article database and gathered 43 articles on the topic. From this search, we concluded that viewpoint oscillations seem to overall benefit vection, and with less evidence, walking sensation and presence. As for cybersickness, the literature presents contrasted results. Overall, we could recommend using viewpoint oscillations when willing to travel distance or speed estimation or to enhance walking simulations without a walking avatar, and we recommend future research works to examine more systematically the effect on cybersickness. By gathering and synthesizing our current understanding of the effects of viewpoint oscillations, we hope our work can pave the way towards providing more compelling walking simulations to static users in VR, with potential applications to virtual visits and medical rehabilitation.

## ACKNOWLEDGMENTS

The authors would like to thank Anne-Hélène Olivier for providing help on the section concerning natural head motion while walking.
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<figure><img src="image_6.png" /></figure>

**Yann Moullec** has graduated from INSA Rennes and University Rennes 1, France, in 2021 and is currently preparing a PhD in computer science in the Hybrid team at University Rennes and Inria Rennes, France. His thesis addresses how multisensory feedback can be used to enhance the experience of users during walking simulations in Virtual Reality.

<figure><img src="image_7.png" /></figure>

**Justine Saint-Aubert** PhD, is a research fellow at CNRS in Rennes, France. She graduated with a PhD in Robotics at Sorbonne University in 2019, after a MS degree in Mechatronics Systems for Rehabilitation by Sorbonne University, France, and University Degli Studi di Brescia, Italy. Her main research interests include humancomputer interaction, multisensory integration, haptic interfaces, and Virtual Reality.

<figure><img src="image_8.png" /></figure>

**Mélanie Cogné** MD, PhD, is a researcher in the Hybrid team at Inria Rennes, France, and a medical doctor in Physical and Rehabilitation Medicine at the University Hospital of Rennes, France. She obtained her PhD in Cognitive Sciences in 2017. Her current research projects focus on innovative technologies and rehabilitation of people with neurological diseases.

<figure><img src="image_9.png" /></figure>

**Anatole Lécuyer** PhD, is a senior researcher and head of the Hybrid team at Inria Rennes, France. He is currently an associate editor of the IEEE TVCG, Frontiers in VR, and Presence journals, and was an associate editor of the ACM Transactions on Applied Perception and the International Journal of Humanities and Cultural Studies. He was a program chair of the IEEE Symposium on 3D User Interfaces (2012-2013) and the IEEE VR Conference (2015-2016), and a general chair of IEEE ISMAR 2017. He also obtained the IEEE VGTC Technical Achievement Award in Virtual/Augmented Reality in 2019.