A Systematic Review and Meta-Analysis on The Use of Tactile Stimulation in Vection Research

Lars Kooijman*, Houshyar Asadi, Shady Mohamed and Saeid Nahavandi, Institute for Intelligent Systems Research and Innovation, Deakin University, Australia.

* Corresponding author. E-mail address: [email protected].

Authors’ affiliated emails: {L.Kooijman; Houshyar.Asadi; Shady.Mohamed; Saeid.Nahavandi}@deakin.edu.au

ABSTRACT

Vection is classically defined as the illusory perception of self-motion induced via visual stimuli. The utility of vection research lies in its potential to enhance simulation fidelity, as measured through presence, and reduce the probability that motion sickness symptoms occur. Recent studies have shown a multimodal interaction of various sensory systems in facilitating vection. Moreover, the utility of co-stimulating some of these sensory systems along with the presentation of visual stimuli have been reviewed. However, a review on the use of tactile stimulation in vection research appears to be missing from literature. The purpose of this review is to evaluate the current methodologies, and outcomes, of tactile stimulation in vection research. We searched for articles through EBSCOHost, Scopus and Web of Science. Studies were included only if they detailed an experiment on the effect of tactile stimulation on vection. Twenty-three studies were obtained and distilled in tabular form. Twenty studies contained sufficient information to be included in a meta-analysis. We identified that tactile stimulation has mostly been applied in the form of vibrational stimulation to the feet. Furthermore, tactile stimulation is most effective when it is presented in a temporally congruent manner to other sensory cues whereas tactile stimulation as a unisensory stimulus does not appear to be effective in eliciting vection. We discuss the need for more qualitative research to reduce methodological inhomogeneities and recommend future research in tactile-mediated vection to investigate stimulation to the torso and investigate the use of forces as a tactile stimulus.

Keywords and Phrases: Vection, Tactile Stimulation, cue-integration, Systematic Review, Meta-analysis.

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1 INTRODUCTION Sometimes when we are stationary, we experience the illusion that we are moving. The illusory experience of self-motion is often exemplified using historical anecdotal accounts. Wood (1895) detailed his perception of illusory self-motion, which he described as "goneness within”, based on his experiencing of the Haunted Swing illusion (Wood, 1895). In this illusion the contents of a room are rotated around you and thereby eliciting the feeling that you are moving yourself. The Haunted Swing illusion can nowadays be experienced in theme park rides such as the Madhouse or Villa Volta manufactured by Vekoma. Another common example of illusory self- motion perception is the train illusion, which can be traced back to William James’ book Principles of Psychology. James (1890) described that “...when another train comes alongside of ours in a station, and fills the entire window, and, after standing still awhile, begins to glide away, we judge that it is our train which is moving, and that the other train is still.” (James, 1890, p.91). These illusory experiences of self-movement are often referred to as vection in scientific research. The utility of vection research lies mainly in the understanding how vection is elicited and which sensory systems contribute to its perception, and subsequently using this information to 1) enhance the fidelity (e.g., immersiveness or presence) of virtual driving or flight simulators and 2) reduce the risk of eliciting motion sickness (MS). The fidelity of simulators is often assessed via measures of presence (e.g., Brackney & Priode, 2017), and previous research has shown a positive correlation between vection and spatial presence when participants viewed naturalistic moving stimuli (Riecke et al., 2005a). Currently, there is no consensus as to whether vection is a predeterminant of MS: findings either indicate that vection is (Nooij et al., 2017) or isn’t (Kuiper et al., 2019) a predeterminant of MS (see Keshavarz et al., 2015 for a review). The leading hypothesis is that MS occurs due to a mismatch between sensory signals and the neural storage of what these sensory signals are expected to be (Reason, 1978). For example, MS could occur when one perceives strong visual cues indicating self-motion while standing still. Since most motion simulators are incapable of generating large or fast physical motions of real vehicles to corroborate the virtual visual stimuli, there is a high probability that participants will experience MS in these simulators. Additionally, a novel theory by Palmisano et al. (2020) proposes that motion sickness in virtual reality (VR), which is also known as Cybersickness (CS), could be due to the lag in the rendering of visual feedback present in modern Head Mounted Displays (HMDs), which creates a discrepancy between participants’ virtual and physical head position. Although the use of HMDs has shown to be more immersive compared to screen-based methods (Shu et al., 2019), simulators utilizing HMDs are more likely to elicit CS due to this inherent rendering lag, which could negatively impact simulator fidelity. A review by Weech et al. (2019) concluded that there appears to be a negative relationship between presence and CS, and the authors highlighted the need to measure vection, CS and presence concurrently (e.g., see D’Amour et al. 2017; Fauville et al., 2021). Thus, it is worthwhile investigating if, and how, multisensory stimulation can elicit the appropriate (illusory) sensation of self-motion in a high-fidelity environment with the lowest probability of eliciting MS/CS. As such, it is necessary to disentangle the physiological and behavioural responses to MS/CS, presence and vection and compare them to subjective measures targeted at evaluating each phenomenon. Lastly, vection research can assist in our understanding of the functionality of, and correlation between, received information from multisensory systems that facilitate human perception. For example, it has recently been shown that vection can facilitate perspective switching which contributes to our spatial orientation (Riecke et al., 2015). Such fundamental information on human perception highlights the functional significance of vection research outside of the field of simulator development. Vection has classically been identified as a visually-induced illusion (Palmisano et al., 2015) and this inference can presumably be traced back to Mach (1875), who concluded that it was highly unlikely that sensations from connective tissue and bones (i.e., ‘Bindegewebe und Knochen’, pp. 65-66), skin (i.e., ‘Haut’, pp. 66-69), muscles (‘Muskeln’, pp. 69-76), blood (‘Blut’, pp. 76-79) and cerebellum (‘Kleinhirn’, pp. 90-94) contributed to our motion perception (Bewegungsempfindungen). However, the contribution and integration of various sensory signals involved in vection have been acknowledged (e.g., Britton & Arshad, 2019; Campos & Bülthoff, 2012; Greenlee et al., 2016; Väljamäe, 2009). Accordingly, Palmisano et al. (2015) analysed the definitions of vection that are used in literature and distilled their findings into four definitions. Throughout this paper, we shall adhere to the fourth definition, namely that vection is “…[a] conscious subjective experience of self-motion”, as it

2 encompasses both illusory as real self-motion perception identified through a multitude of sensory organs (Palmisano et al., 2015). One of the senses involved in self-motion perception is the human tactile sense. The contribution of tactile stimulation to vection is not a novel concept. Riecke and Schulte-Pelkum (2013) noted that it was Helmholtz who suggested as early as “…1866 that vibrations and jerks that naturally accompany self-motions play an important role for self-motion illusions, in that we expect to experience at least some vibrations or jitter...”. Furthermore, the potential of tactile stimulation in eliciting or enhancing vection has been highlighted in the well-cited work of Dichgans and Brandt (1978) over four decades ago. However, tactile-vection research does not appear to be as prevalent in literature as, for example, vection research using visual and auditory stimulation. Visual, vestibular, and auditory vection have been reviewed extensively (see Britton & Arshad, 2019; Dichgans & Brandt, 1978; Hettinger et al., 2014; Lappe et al., 1999; Väljamäe, 2009) and Harris et al. (2002) briefly discuss the relation of gravitoinertial forces and proprioception to vection. Additionally, the works of Amemiya (2018) and Lécuyer (2017) contain a discussion on the utility of tactile stimulation in vection research, however, the content is brief and mainly focussed on the research output by their respective groups. Lastly, Hettinger et al. (2014) discussed the use of haptic and tactile cues in the genesis of vection, however, it comprised of only one page. Thus, to the best of our knowledge, no extensive review is present in literature on tactile-mediated vection. The aim of the current article is to review the literature on the methodologies around tactile stimulation in vection research. Furthermore, we aim to qualitatively and quantitively, through a meta-analysis, assess the outcomes of tactile stimulation in vection research. The article is structured as follows: our research questions, search methodology and statistical methods are detailed in section 2, in section 3 the studies identified from our literature search are presented along with specific topics relevant to the research questions as well as the results of the meta-analyses, section 4 discusses potential answers to the research questions using information gathered through the systematic review and meta-analyses as well as limitations and general recommendations for future vection research, and, lastly, in section 5 we offer concluding remarks and recommendations for tactile-mediated vection research.

2 METHODS We based our review methodology on the PRISMA statement (Moher et al., 2009) and derived our search strategy from the systematic review conducted by Grassini and Laumann (2020). Moreover, we performed our meta- analysis in a similar fashion to Cummings and Bailenson (2016).

2.1 Research Questions We reviewed the literature with the aim to identify the methodology and outcome of the use of tactile stimulation in vection research. As such, we focussed on how tactile stimulation was used and what the sizes of the effects were with the following questions in mind:

• RQ1 – How is tactile stimulation employed in vection research? • RQ2 – Does tactile stimulation, in general, positively contribute to participants’ vection? • RQ3 – Which parts of the body are most and least suitable for tactile stimulation to enhance vection? • RQ4 – What is the most and least effective form of tactile stimulation to enhance vection?

2.2 Literature Search Strategy We searched EBSCOhost, Scopus, and Web of Science for scientific articles. In EBSCOHost we used a combined search for title, abstract OR subject terms in all its databases. In Scopus we used the basic search function for title, abstract OR keywords. For Web of Science, we used a combined search for title, abstract, keyword OR author keywords. The search was conducted using the following keyword combination:

((self AND (motion OR movement) AND (perception OR illusion*)) OR vection) AND ((somatosensory OR cutaneous OR tactile OR vibrotactile OR haptic*) AND (vibration* OR perturbation* OR stimul* OR feedback OR induc*))

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Lefthanded truncation was not utilised as it is not compatible with abstract or keyword searches in Web of Science. The results (i.e., authors, title, year of publication, publication source and DOI) were combined into a single Excel file. The Excel file was read by a custom written MATLAB script which filtered out non-unique titles. The resulting set of unique articles was saved in a new Excel file, which was then used as a reference tool to label the articles according to their suitability. The Excel files and the MATLAB script are available via the link provided in the Data Availability Statement. Titles and abstracts of the unique set of articles were screened for suitability according to the following inclusion criteria. Firstly, we only included peer-reviewed articles or conference proceedings. Secondly, the articles had to be written in English. Thirdly, the article was only included if it contained an empirical study wherein tactile stimulation was presented to human participants and evaluated in relation to vection. Tactile stimulation was defined as stimulations which are applied to the skin to sensitize the mechanoreceptors by means of vibrations, wind, or forces. Vection was defined as a subjective experience of self- motion and therefore studies investigating self-motion through methods such as distance estimation without evaluating participants experience were not included. Furthermore, we did not limit our search by any timeframe. The articles that passed the title and abstract screening had their full text screened using the same inclusion criteria.

Figure 1: Results from keyword search in EBSCOHost, Scopus and Web of Science (WoS). Ir = Irrelevant, NE = No Experiment Detailed, NF = Not Found, NT = No Tactile Stimulation, NV = No Vection Detailed.

2.3 Literature Search Results Figure 1 shows the screening process used for this literature review. A total of 732 entries were identified from the databases. After checking for duplicates, 465 unique citations remained. Through the screening of titles and abstracts, 435 entries were excluded. The remaining 30 entries had their full text screened. Subsequently, 16 articles were excluded because they did not meet the inclusion criteria, however, 9 additional articles were obtained. The 23 remaining articles from our literature survey are summarized in a tabular format. Please note that the literature screening process was solely conducted by the primary author. Therefore, we cannot exclude

4 that the systematicity our review process might be limited by a degree of subjectivity in the formulation of the in/exclusion criteria and in the study selection phase of the review.

2.4 Meta-Analysis Procedure We screened the 23 articles identified through our literature review for effect sizes on measures of vection intensity and convincingness. Intensity measures were defined as any measure where participants rated the ‘strength’ of their self-motion sensation and convincingness measures were defined as any measure where participants rated either the ‘convincingness’, ‘compellingness’ or ‘realism’ of their self-motion sensation. The studies by Hayashizaki et al. (2015) and Rupert and Kolev (2008) did not contain sufficient information to compute effect sizes. Furthermore, Farkhatdinov et al. (2013) employed a two-alternative forced choice task without having a reference condition in which tactile stimulation was absent. Matsuda et al. (2020, 2021) and Nilsson et al. (2012) did not employ a control condition in which tactile stimulation was absent. Therefore, these studies were omitted from the meta-analyses. From the remaining 17 articles 44 effect sizes were obtained. We obtained effect sizes (r) in one of three ways. We either computed Cohen’s d from the means and standard deviations reported in the studies and converting them using the formula described in Rosenthal and DiMatteo (2001). Otherwise, if t-test information was present, we derived the effect sizes from the t-statistic and the degrees of freedom (Rosenthal & DiMatteo, 2001). If ANOVAs were reported, we computed Cohen’s f using an effect size calculator (https://effect-size-calculator.herokuapp.com/) and converted Cohen’s f to Cohen’s d, and then into effect size r. We performed multiple analyses using five factors. Firstly, we performed a meta-analysis on the effect of using tactile stimulation on general vection. General vection was defined as either the subjective measure of vection intensity or convincingness, or the average of vection intensity and convincingness if both measures were reported concurrently in the study. If a study contained multiple experiments wherein they measured vection intensity/convincingness, we treated each experiment as a separate entry into the meta-analysis (Cummings & Bailenson, 2016). Secondly, we investigated the effect of adding tactile stimulation to the stimulation of other sensory modalities on general vection. We grouped effect sizes based on whether tactile stimulation was added to visual (VT), auditory (AT) or visual-auditory stimulation (AVT). If multiple types of stimulations were used, we computed separate effect sizes for each combination of stimulation type. For example, if participants were exposed to visual, audio, visual-tactile and audio-tactile stimulation, we derived two effect sizes (i.e., VT and AT). If a study contained multiple forms of tactile stimulation as well as other forms of stimulation, we computed separate effect sizes for each combination and averaged the effect sizes based on their sensory modality (e.g., visual-tactile, audio-tactile). In case a study reported that participants wore headphones that played white noise to block out the sounds of actuators, it was considered a study without the use of auditory stimulation since the sounds did not contain any motion information. Thirdly, we investigated the effect of different types of tactile stimulation on general vection by grouping the effects of tactile stimulation on vection in the factors forces, vibrations, and wind. Fourthly, we investigated the effect of different vibrational stimulation frequencies on general vection. The mechanoreceptors of the skin have different optimal signalling frequencies. For example, Merkel cells, Meissner corpuscles, and Pacinian corpuscles have a frequency range of 0 to 100 Hz, 1 to 300 Hz, and 5 to 1000 Hz, respectively, whilst the optimal signalling frequency is 5, 50, and 200 Hz, respectively (Gardner & Kenneth, 2000). Therefore, we decided to group effect sizes in frequency ranges 0-15 Hz, 16-100 Hz and 100+ Hz. Lastly, we performed meta-analyses on the effect of tactile stimulation on different body parts on general vection. We factorized studies based on the location to which they applied tactile stimulation, namely the face, the feet, the torso, the lower back and buttocks, and the lower extremities. If studies applied stimulation to two parts of the body (e.g., face and torso), they were included in both factors. We used the conventional interpretation of effect sizes suggested by Cohen (2013), namely that small, medium, and large effects are reflected by r = .10, r = .30 and r = .50, respectively. The resulting effect-size for each factor was subjected to a chi-squared test to assess the homogeneity of the results included in the analysis. If the chi- squared test returns a significant result, it is likely that the variance in effect sizes across the studies is due to moderating variables rather than sampling error. However, as the chi-squared test has a low power to detect homogeneity when the number of studies analysed is low, we also computed I2 which reflects the variance in

5 effect estimates due to heterogeneity in percentages (Higgins et al., 2003). Higgins et al. (2003) suggested threshold values of 25, 50 and 75% as indicators of low, moderate, and high heterogeneity, respectively. The meta-analysis was performed in Excel using the steps denoted in Field (1999) for the random-effects model. The Excel sheet is available via the link provided in the Data Availability Statement.

3 RESULTS The information we obtained from the included articles regarding the methodology and outcomes of the use of tactile stimulation in vection research has been detailed in Table 1. Furthermore, Table S1 in the supplementary material details all the effect sizes we derived from the articles to perform the meta-analyses.

3.1 Tactile stimulus type, characteristics and location of application From the 23 articles we found through our literature search, we identified that the application of tactile stimuli varied from blowing wind (Feng et al., 2016; Murata et al., 2014; Seno et al., 2011; Yahata et al., 2021), the application of forces to the body (Murovec et al., 2021; Oishi et al., 2016) to the application of vibrational stimulation to various body parts, as detailed in the tactile section of the ‘Stimuli’ column in Table 1. Vibrational stimulation was applied to the dorsal side of the body (Lind et al., 2016), feet (Farkhatdinov et al., 2013; Feng et al., 2016; Hayashizaki et al, 2015; Kitazaki et al., 2019, 2016; Kruijff et al., 2016; Matsuda et al., 2020, 2021; Nilsson et al., 2012; Nordahl et al., 2012; Riecke et al., 2005b; Väljamäe et al., 2006; Väljamäe et al., 2009), the lower back and buttocks (Riecke et al., 2005b; Riecke et al., 2009; Soave et al., 2020 Väljamäe et al., 2006; Väljamäe et al., 2009), torso (Rupert & Kolev, 2008) and waist (Tinga et al., 2018). Figure 2 displays some tactile stimulation devices used in the studies we identified from our review. Wind stimulation was directed to the face (Feng et al., 2016; Seno et al., 2011) or to the front (Murata et al., 2014; Yahata et al., 2021), right or back side of the participant (Murata et al., 2014). In the study by Murovec et al. (2021) participants pressed their fingers on a polystyrene ring that rotated around them. Overall, participants passively experienced the stimuli except in the experiments by Feng et al., (2016) where participants moved in a virtual environment using a controller, by Kruijff et al. (2016) where participants controlled the movement of a virtual avatar by either leaning forward or by moving a joystick, by Murata et al. (2014) where participants balanced themselves on a swaying horse-riding machine, by Oishi et al. (2016) where participants controlled the forward movement of a virtual car by pushing a pedal with their feet, and by Tinga et al. (2018) where participants walked forward whilst blindfolded. The frequency, amplitude and duration of the tactile stimuli used in each study is denoted in the fourth column of Table 1. The system used by Oishi et al. (2016) pulled backwards on the shoulder part of participants clothes with a force of up to 18 N. The force increased proportionally to the velocity of the vehicle which the participants controlled. Murata et al. (2014) used a fan to blow wind with a constant speed at participants whilst they sat on a horse-riding machine which swayed back and forwards and changed the direction of the wind between conditions. Seno et al. (2011) used a bladeless fan blowing at a constant speed to stimulate participants’ faces. Similarly, Yahata et al. (2021) blew either hot or normal temperature air at a constant speed to stimulate the frontal part of participants’ body. Feng et al. (2016) used a series of fans arranged in a circle around the participant to provide tactile cues in the form of movement and directional wind. The speed of the movement wind was proportional to the velocity of the participant in the virtual environment, whereas directional wind was blowing at a constant speed, but changed direction proportional to the participants’ orientation in the virtual environment. Additionally, participants were subjected to periodical foot vibrations derived from audio recordings of a real footstep. The vibrational stimulation patterns used in the experiments by Hayashizaki et al. (2015), Kitazaki et al. (2016, 2019) and Matsuda et al. (2020, 2021) were also derived from audio recordings of footsteps. Hayashizaki et al. (2015) and Kitazaki et al. (2016) presented the vibrations only in synchrony with the foot strikes of the visual stimuli. However, in the experiments by Kitazaki et al. (2019) and Matsuda et al. (2020, 2021) the vibrations were presented either synchronously or asynchronously to the foot strikes of the visual stimulus. Moreover, Hayashizaki et al. (2015) and Kitazaki et al. (2016) presented stimulations through one actuator situated at the heel of participants, whereas Kitazaki et al. (2019) and Matsuda et al. (2020, 2021) presented participants with tactile flow stimuli using actuators located at the heel and forefoot. Tactile flow was also utilized by Rupert and Kolev (2008) who administered 40 Hz vibrations to participants’ torso, either clockwise or counterclockwise, by means of a custom garment containing 40 pneumatic stimulators.

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Table 1: Results from the literature review Authors Stimuli Tactile Frequency Actuator N (M, F) Vection measure Outcome stimulation Amplitude Age (SD) Visual Audio Tactile Other location Duration Age band Farkhatdinov Linear Optic N.D. Constant None Feet Sine: 90 Chirp: Pink Custom-Designed 6 (5, 1). Intensity: 2AFCT POS et al. (2013) flow vibrations Hz 70-110 Noise: Electromagnetic N.D. Onset: BP. Hz N.D. Haptuator 27-40. N.D. Feng et al. Virtual Footsteps Air flow and None Wind Vibrations Wind Vibrations Wind Exp 1 Exp 2 Motion sensation: MIX (2016) walking constant vibrations Face Feet 0-4 m/s N.D. 120mm DC fan 24 (21, 3) 16 (9, 7) Ratings (1 - 6) and N.D. N.D. Vibrations 21 (3.58) 25 (4.25) torso N.D. N.D. Buttkicker LFE 18-31 19-34 Hayashizaki First person N.D. Tactile flow None Feet 120 Hz sound signal Acouve Lab 10 (N.D.). Intensity: Ratings POS et al. (2015) perspective of N.D. VP408 vibro- (0-100) someone 150 ms transducers walking Kitazaki et al. First person N.D. Tactile flow None Feet 120 Hz sound signal Acouve Lab Exp 1 Exp 2 Intensity: VAS POS (2016) perspective of N.D. VP408 vibro- 10 (N.D.). 15 someone 150 ms transducers N.D. (N.D.). walking N.D. N.D. N.D. Kitazaki et al. First person White noise Tactile flow None Feet 240 Hz sound signal. Acouve Lab Exp 1 Exp 2 Intensity: VAS POS (2019) perspective of N.D. VP408 vibro- 15 (15, 0). 15 (14, someone 200 ms transducers 21.35 1). walking (0.88). 20.7 N.D. (1.3). N.D. Kruijff et al. Virtual Gravel & Tactile flow None Feet N.D. 1 bass modulator, 12 (11, 1). Intensity: Ratings (0 POS (2016) walking wood N.D. 1 loudspeaker, 8 29 (N.D.). - 10) N.D. vibrotactors per 25-48. foot

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Authors Stimuli Tactile Frequency Actuator N (M, F) Vection measure Outcome stimulation Amplitude Age (SD) Visual Audio Tactile Other location Duration Age band Lind et al. Virtual Bird sounds Constant and None Posterior side of Constant: Gravel: Fine ButtKicker 17 (14, 3). Intensity: Ratings (0 MIX (2016) sandboarding dynamic body 75 Hz 20-50 Sand: Advance BK4-4 24.9 (2.6). - 100). vibrations N.D. Hz 50- audio transducer 21-31. Compellingness: N.D. N.D. 100 Ratings (0 - 100). N.D. N.D. Hz Matsuda et al. Virtual White noise Synchronous or None Feet N.D. Acouve Lab 20 (19, 1). Intensity: VAS POS (2020) walking asynchronous N.D. Vp408 21.95 tactile flow. 300 ms (N.D.). 21-23. Matsuda et al. First and third White noise Synchronous or None Feet N.D. Acouve Lab Exp 1 Exp 2 Intensity: VAS POS (2021) person asynchronous N.D. Vp408 20 (19,1) 20 (20,0) perspective of tactile flow. 300 ms 21.95 21.65 virtual (0.50). (1.11) walking 21-23 19-24 Murata et al. None White noise Air flow Body Anterior, right 5.5 m/s FIR401, Pieria 13 (5,8) Intensity: Ratings POS (2014) sway lateral and posterior N.D. Corporation N.D. (0-5) verbal. side of face and N.D. 21-43 torso. Murovec et al. Rotating 360- Fan, printer, Circular tactile None Fingers 45 deg/s Polystyrene tactile 24 (8,16) Intensity: Ratings POS (2021) degree image Telephone stimulation N.D. ring 25.46 (0-10) verbal. of an office rotating with 45 s (3.64)a Duration: Ratings space. image. N.D. (0-100%) verbal. Nilsson et al. Virtual lift, Sound of a Constant vibration None Feet S.T. 50 Hz Electromagnetic 18 (15, 3). Onset: Verbal MIX (2012) train, fan N.D. Haptuator 25.8 (5.4). Compelligness: bathroom and 60 s 19-40. Ratings (0-5) darkness verbal. DE: metres, verbal Nordahl et al. Virtual Sound of Constant vibration None Feet W.N. S.T. W.N.+ Electromagnetic 28 (22, 6). Onset: Verbal POS (2012) elevator moving N.D. 50 Hz S.T. Haptuator 25.0 (3.1). elevator N.D. N.D. N.D. 21-33.

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Authors Stimuli Tactile Frequency Actuator N (M, F) Vection measure Outcome stimulation Amplitude Age (SD) Visual Audio Tactile Other location Duration Age band 60 s 60 s N.D. Compellingness: 60 s Ratings (0-5) verbal. DE: metres, verbal Oishi et al. A car driving N.D. Traction force None Torso 0.1 Hz Maxon motor with Exp 2 Intensity: Ratings NULL (2016) simulation from pulls on their 18 N gear head, gear 6 (N.D.) (1-7) (Exp 2). clothes. N.D. ratio 19:1 N.D.(N.D.) 20-24. Riecke et al. Rotating 360- Flowing Vibrations None Lower back, 15-90 Hz Force transducers Exp 3 Onset: Joystick. MIX (2005b) degree image water. proportional to buttocks, and feet. N.D. 24 (N.D.). Intensity: Joystick of a market. angular velocity 84 s N.D. Build-up time: rotating image N.D. Joystick Convincingness: Ratings (0-100%) Riecke et al. None Rotating Constant vibration None Lower back and 7 Hz Motor with Exp 1 Intensity: Ratings POS (2009) sounds buttocks via chair N.D. eccentric weight 14 (9, 5). (0-100%) 99 s 25.8 (N.D.). Realism: Ratings 18-51 (0-100%) Rupert and Rotating N.D. Clockwise and None Torso 40 Hz Pneumatic tactile 12 (N.D.) Optokinetic eye NEG Kolev (2008) random dot counterclockwise N.D. stimulators N.D. movements. pattern tactile flow. 30 s N.D. Velocity: verbal

m Seno et al. Contacting Fan noise Air flow None Face 6.37 /s Dyson, AM01 18 (N.D.) Onset: BP. MIX (2011) and expanding N.D. N.D. Duration: BP. linear optic 50 s N.D. Intensity: Ratings flow. (0-100) Soave et al. Cockpit of a N.D. Constant vibration None Lower back and N.D. Lofelt L5 12 (6, 6). Intensity: Joystick POS (2020) virtual train buttocks N.D. 29 (4.2). position. N.D. N.D.

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Authors Stimuli Tactile Frequency Actuator N (M, F) Vection measure Outcome stimulation Amplitude Age (SD) Visual Audio Tactile Other location Duration Age band Tinga et al. None Pink noise Clockwise and PP Waist 158 Hz Elitac Belt 40 (20, 20). Intensity: Ratings (0 NULL (2018) and 2-back counterclockwise walked. N.D. 52.3 (6.13). – 5). task. tactile flow. 306ms per actuator 40 - 60 Deviation angle of 2 s total duration walking path. Väljamäe et None Moving Constant vibration None Lower back, Shakers Subwoofer Custom shaker 23 (13,10) Intensity: Ratings (0 MIX al. (2006) electrical buttocks, and feet. 40 Hz 40 Hz and subwoofer 24.5 (4.8) - 100). cm 2 cart. 2.6 / 4.9 /s 60 / 66 dB N.D. Convincingness: 0.3 s bursts 67 s Ratings (0 - 100). Väljamäe et None Rotating Constant vibration None Lower back, 10 – 15 Hz Phillips GM 5532 16 (8, 8). Intensity: Ratings (0 NULL cm 2 al. (2009) market buttocks, and feet Max 5 /s Shaker. 24 (2). - 100). environment N.D. N.D. Convincingness: Ratings (0 - 100).

m Yahata et al. Linear optic White noise Normal (18.6◦C) None Face and torso 2 /s Dyson Pure Exp 1 Exp 2 Intensity: Ratings (0 POS (2021) flow from and hot (35.7◦C) HP00IS 15 (N.D.) 16 (N.D.) - 100). moving airflow N.D. N.D. through virtual N.D. N.D. corridor Note: 2AFCT = Two-Alternative Forced Choice Task, BP = Button Press, DE = Distance Estimation, Exp 1 = Experiment 1, Exp 2 = Experiment 2, M = Male, F = Female, N.A. = Not Applicable, N.D. = Non-Disclosed, PP = participants, S.T. = Saw Tooth, VAS = Visual Analogue Scale, VR = Virtual Reality, W.N. = White Noise. The outcomes of studies were categorized as following: POS = Positive effects, meaning tactile stimulation enhanced vection operationalized by an increase in all vection measures. MIX = Mixed effects, meaning the effect and its direction of tactile stimulation differed between vection measures. NULL = Null effect, meaning tactile stimulation had no positive or negative effect on vection measures. NEG = Negative effect, meaning tactile stimulation decreased vection. a computed grand mean (SD) from data in paper.

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Similarly, Tinga et al. (2018) provided participants with circumferential vibrational stimulation around the waist using a belt, which had 13 vibrational elements oscillating at 158 Hz for 308ms each. There was a 154ms overlap between the actuators so that the total vibration lasted for about 2s. Tactile stimulation to the feet was administered via either one (Hayashizaki et al., 2015; Kitazaki et al., 2016), two (Farkhatdinov et al., 2013; Kitazaki et al., 2019; Matsuda et al., 2020,2021) or four actuators (Nilsson et al., 2012; Nordahl et al., 2012) per foot while participants were standing or seated. Alternatively, vibrational feedback was provided by the oscillation of the floorboards or platform on which the participants were resting their feet (Farkhatdinov et al., 2013; Feng et al., 2016; Riecke et al., 2005b; Väljamäe et al., 2006, 2009). Participants in the study by Farkhatdinov et al. (2013) had their feet placed on a platform actuated by custom-designed electromagnetic actuators. The authors utilized four different signals in their study: 1) a sinusoidal signal with a frequency of 90 Hz, a chirp signal with a varying frequency from 70 to 100 Hz, a pink noise signal or no signal at all. The custom-built, box-like system used by Kruijff et al. (2016), shown in Figure 2 (right), consisted of two loudspeakers, two bass-shakers and sixteen actuators. The placement of the actuators was based on foot-pressure distributions of a standing person. The vibrational patterns used by Kruijff et al. (2016) were inspired by literature and were synchronized to the velocity of the visual stimulus. Nordahl et al. (2012) presented participants with four different tactile stimulation patterns: white noise, a 50 Hz sawtooth, a combination of white noise and the 50 Hz sawtooth or no stimulus at all. Nilsson et al. (2012) used a 50 Hz sawtooth stimulation pattern which, according to the results of Nordahl et al. (2012), positively mediated vection intensity and convincingness. In both studies, a 5-second attack and decay of the tactile stimulation pattern was used at the start and end of the experimental conditions, respectively.

Figure 2: Tactile stimulation devices. Left: Device used by Soave et al. (2020). Image provided by courtesy of Francesco Soave. Right: Device used by Kruijff et al. (2016). Image provided by courtesy of Ernst Kruijff.

An alternative form of increasing and decreasing the tactile stimulation pattern can be found in the studies by Murovec et al. (2021), Riecke et al. (2005b) and Väljamäe et al. (2009). Riecke et al. (2005b) applied vibrations ranging from 15 to 90 Hz to the seat and floor plate proportional to the angular velocity of the visual stimulus, whereas Väljamäe et al. (2009) linearly increased and decreased the vibrations applied to the seat and floorplate along with the acceleration and deceleration phase of the auditory stimulus. Moreover, Väljamäe et al. (2009) varied the amplitude of the vibrational stimulus proportional to the different auditory angular velocities which were used between experimental conditions. Similarly, Murovec et al. (2021) accelerated and decelerated the rotation of the polystyrene ring that participants were touching so that its velocity profile matched that of the visual and auditory stimuli. Väljamäe et al. (2006) created an acceleration phase in their tactile stimulus concurrently to the acceleration phase of the auditory stimulus by gradually decreasing the silent periods between the sinusoidal burst vibrations. The vibrational stimulus at constant velocity comprised of 0.3s bursts at 40Hz intermitted with 0.1 s silent periods which were presented to participants via a shaker mounted underneath the participants’ chair. Lind et al. (2016) varied the tactile stimulation frequency depending on the virtual surface participants were traversing and proportional to the participants’ virtual velocity. Participants were presented with either constant vibrational stimulation of 75Hz or dynamic stimulation varying between 20 to 100 Hz. Riecke et

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al. (2009) applied constant tactile stimulation by attaching an actuator with an eccentric weight that vibrated at 7Hz to the frame of a hammock chair. Soave et al. (2020) applied vibrotactile feedback to participants through a chair equipped with eight Lofelt haptic actuators, as shown in Figure 2 (left), however no information regarding the stimulation frequency, amplitude or duration was provided.

3.2 Concurrent Stimulation of Other Sensory Modalities In 18 of the 23 studies found, tactile stimulation was presented concurrently with visual stimulation as can be seen from the ‘Stimuli’ column in Table 1. Figure 3 exemplifies some of the forms of visual and auditory feedback which participants received. Visual stimuli were presented to participants either on a computer screen (Farkhatdinov et al., 2013), a projector screen (Murovec et al., 2021; Riecke et al., 2005b; Seno et al., 2011), a physically moving surrounding (Rupert & Kolev, 2008), or via an HMD (Feng et al., 2016; Hayashizaki et al., 2015; Kitazaki et al., 2019, 2016; Kruijff et al., 2016; Lind et al., 2016; Matsuda et al., 2020, 2021; Nilsson et al., 2012; Nordahl et al., 2012; Oishi et al., 2016; Soave et al., 2020; Yahata et al., 2021). Visual stimuli comprised either of optic flow patterns (Farkhatdinov et al., 2013; Rupert & Kolev, 2008; Seno et al., 2011) or the first- person perspective of being on cart or train moving through a tunnel (Nilsson et al., 2012, see Figure 3C; Soave et al., 2020), moving through a corridor (Yahata et al., 2021), being seated in a moving car (Oishi et al., 2016, see Figure 3B), standing in an elevator (Nilsson et al., 2012; Nordahl et al., 2012), standing in a bathroom (Nilsson et al., 2012), a person or avatar walking (Feng et al., 2016; Kitazaki et al., 2019, 2016; Kruijff et al., 2016; Matsuda et al., 2020, 2021, see Figure 3A) or sandboarding down a dune (Lind et al., 2016).

A B D

C

Figure 3: Examples of additional stimuli used concurrently to tactile stimuli. A: Walking avatar used by Matsuda et al. (2020). Image retrieved from Matsuda et al. (2021). B: Set-up used by Oishi et al. (2016). Image provided by courtesy of Hiroyuki Kajimoto. C: Train environment used by Nilsson et al. (2012). Reprinted by permission from Springer Nature Customer Service Centre GmbH: Springer Nature, Haptics: Perception, Devices, Mobility, and Communication. Haptically Induced Illusory Self-motion and the Influence of Context of Motion, Nilsson, N. C., Nordahl, R., Sikström, E., Turchet, L., & Serafin, S. (2012). https://doi.org/10.1007/978-3-642-31401-8_32 D. Auditory stimulation used by Riecke et al. (2009). Image provided by courtesy of Bernhard Riecke.

When visual stimulation was absent, participants were blindfolded (Murata et al., 2014; Riecke et al., 2009; Tinga et al., 2018; Väljamäe et al., 2006, 2009). Riecke et al. (2009) presented four different sound objects to the participants through the headphones they wore, as illustrated in Figure 3D. Similarly, participants in the experiment conducted by Väljamäe et al. (2006) wore headphones and were presented with approaching sounds of a barking dog and bus on idle to elicit linear auditory vection. Väljamäe et al. (2009) presented participants with sounds of moveable objects, such as footsteps, as well as auditory landmarks, such as the sound of a fountain. In some studies, tactile stimulations were accompanied by both visual and auditory stimulation. Murovec et al. (2021) presented participants with sounds of a ringing telephone, a rotating fan and the sounds of a printer, which rotated around the participant congruently to their position in the 360-degree image. Kruijff et al. (2016) presented the sound of footsteps on wood and gravel from within the box that generated tactile stimulation on which participants were standing. Participants in the experiments conducted by Lind et al. (2016) wore a pair of headphones that played friction sounds of a board on sand and gravel as well as the sound of birds chirping to

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present an auditory landmark. To reduce the possibility of distracting participants with the sounds of the actuators, experimenters presented participants with noise sounds (Kitazaki et al., 2019; Matsuda et al., 2020, 2021; Nilsson et al., 2012; Riecke et al., 2005b; Tinga et al., 2018; Yahata et al., 2021). For example, participants in the study by Tinga et al. (2018) wore headphones which presented them with an auditory 2-back task with pink noise as a background sound whereas in the study by Riecke et al. (2005b) participants were presented with the sounds of flowing water through noise-cancelling headphones. However, in some studies it was not disclosed either why participants were wearing headphones, whether auditory feedback was present or what the content of the auditory feedback was (Farkhatdinov et al., 2013; Hayashizaki et al., 2015; Kitazaki et al., 2016; Oishi et al., 2016; Rupert & Kolev, 2008; Seno et al., 2011; Soave et al., 2020). Vestibular stimulation was not controlled for in some experiments (Oishi et al., 2016; Murata et al., 2014; Kruijff et al., 2016; Tinga et al., 2018). In these experiments, participants’ heads could move due to either their self-initiated movement (e.g., leaning forward or walking) or due to the experimental stimulations (i.e., pulling on clothes, sway of the horse-riding machine). Lastly, participants in three studies were presented with a condition in which only tactile stimulation was presented (Murata et al., 2014; Murovec et al., 2021; Nilsson et al., 2012). Murata et al. (2014) presented blindfolded participants with either front, right side or back-facing winds without the presence of body sway. The study by Murovec et al. (2021) contained trials wherein participants sat in complete darkness and touched the rotating ring. The only sound that was present was the sound of the actuator driving the ring. Nilsson et al. (2012) included a condition in which participants were visually presented with a completely dark environment through the HMD they were wearing. Additionally, a sound loop of a spinning fan was played through the headphones participants were wearing to mask out the sound of actuators that provided the tactile stimulation.

3.3 The Effect of Tactile Stimulation on Vection: Meta-Analysis Results In general, tactile stimulation had a medium effect on general vection, as can be seen in Table 2. The addition of tactile stimulation to either auditory, visual, or visual-auditory stimulation showed a medium effect on general vection with the addition of tactile stimulation to visual stimulation showing the largest effect. However, the heterogeneity among effect estimates was the highest (I2 = 70%) for the VT factor, whereas lower, but still moderate, heterogeneity was found for the AT and AVT factors. A slightly larger effect (r = .442) of wind stimulation on general vection was found compared to vibrational stimulation (r =.437), however, both factors contained moderate to high heterogeneity. Furthermore. the Wind factor contained a relatively small number of studies compared to the Vibrations factor. Although the use of Forces appeared to have a large effect, the number of studies included in this factor was extremely low. High frequency vibrations (i.e., 100+ Hz) resulted in the largest effect on general vection compared to the other two factors, however, the interpretation of these effect sizes is limited due to the low number of studies in each factor (i.e., 5 and lower). The effect of stimulating different body parts on general vection varied from small to large, where stimulation of the lower extremities appeared to be the least effective whereas stimulating the feet the most. Nonetheless, the number of studies included in the factor ‘Feet’ was three times larger than the number of studies in the ‘Lower Extremities’ factor. Additionally, there was high heterogeneity in the ‘Feet’ factor. The I2 of the lower extremities factor was set to zero as it was negative (Higgins et al., 2003). The studies contained in the factor ‘Face’ were the same as in the factor ‘Wind’. Lastly, the factor ‘All Studies’ showed that substantial heterogeneity was present (i.e., 77%). The individual factors were not accountable for the variance found as almost all factors contained significant levels of heterogeneity, except for the ‘Lower Extremities’ factor.

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Table 2: Results of meta-analysis on general vection with tactile stimulation and individual factors. K r 95% Confidence N χ2 p I² Interval All Studies 22 .444 .237 .651 387 73.83 <.001 69% Modality AT 4 .360 -.112 .832 77 12.95 .005 61% VT 11 .478 .162 .794 184 40.03 <.001 70% AVT 8 .414 .074 .755 141 25.34 .001 64% Tactile type Forces 2 .524 -.440 1.489 36 8.13 .004 63% Vibrations 16 .437 .189 .686 289 57.04 <.001 70% Wind 5 .442 .009 .874 86 15.47 .004 61% Intensity 0-15 Hz 2 .355 -.436 1.147 30 5.89 .015 49% 16-100 Hz 4 .310 -.007 .626 92 8.16 .043 39% 100+ Hz 5 .543 -.014 1.101 95 24.42 <.001 75% Location Face 5 .442 .009 .874 86 15.47 .004 61% Feet 9 .574 .146 1.003 143 44.38 <.001 77% Lower back & 2 .434 -.409 1.277 26 5.67 .017 47% buttocks Lower extremities 3 .168 -.099 .435 63 1.92 .384 0% Torso 6 .420 .042 .798 120 19.15 .002 63% General vection was derived as either an effect on vection intensity or convincingness, or the average effect of vection intensity and convincingness if both variables were reported in the study. Studies included in the factor ‘Wind’ were the same as the studies included in the factor ‘Face’. I2 in factor ‘Lower extremities’ was set to 0% as it was negative. K = Number of studies. N = Cumulative sample size. Statistically significant p-values are indicated in bold font.

3.4 The Effect of Tactile Stimulation on Vection: A Study-based Assessment Meta-analyses provide a general indication on the size and direction of certain effects, however, not every study we included in our systematic review contained sufficient information to be included in the meta-analyses. Therefore, we assessed the outcomes of each study in a qualitative manner based on the reported effect tactile stimulation had on vection. The outcomes were categorized as either negative, positive, mixed, or null effects and are listed in the last column in of Table 1. A negative effect indicated that tactile stimulation reduced participants’ vection, a positive effect indicated that tactile stimulation enhanced participants’ vection, a mixed effect indicated that tactile stimulation had a different effect on individual subjective measures of vection, and a null effect indicated that tactile stimulation had no significant effect on subjective measures of vection.

3.4.1 Negative Effects All participants in the study by Rupert and Kolev (2008) reported they perceived a reduction in circular vection velocity when tactile stimulation was applied. Moreover, six subjects showed either a decrease in the magnitude or a change in the frequency of their slow-phase eye movements.

3.4.2 Positive Effects Farkhatdinov et al. (2013) identified from then results of the two-alternative forced choice task that a sinusoidal vibrotactile stimulation pattern elicited stronger vection compared to random or no vibrotactile stimulation. The results from the study by Hayashizaki et al. (2015) showed that participants rated vection to be more intense when feet vibrations were presented concurrently to visual stimulation compared to visual stimulation alone. Similarly, participants in the study by Kitazaki et al. (2016) rated vection to be more intense when vibrations were present than when they were absent. Kitazaki et al. (2019) found that adding synchronized vibrations resulted in higher vection intensity ratings compared to random and no vibrations. Moreover, the authors found that delaying the tactile stimulus with 0.25 or 0.5 phase with respect to the moment foot strikes occurred in the visual stimulus reduced vection intensity. In the same vein, Matsuda et al. (2020, 2021) found that self-motion perception for synchronized vibrations was rated higher than asynchronized vibrations. Kruijff et al. (2016) found that

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vibrotactile feedback increased vection intensity ratings when it was combined with visual feedback. Vection intensity ratings obtained in the study by Murata et al. (2014) were higher when tactile stimulation in the form of wind was combined with body sway compared to wind stimulation or body sway alone. Moreover, frontal winds elicited higher vection ratings compared to side and back-facing winds. Murovec et al. (2021) found that the presence of tactile cues increased vection intensity ratings compared to conditions in which they were absent. Nordahl et al. (2012) found that sawtooth vibrations resulted in the highest vection compellingness and the largest self-reported distance travelled, which was significantly different to the condition where there was no vibrotactile feedback. Participants in the study by Riecke et al. (2009) rated vection intensity and realism higher when jitter vibrations were present compared to when they were absent. Soave et al. (2020) found a significant positive effect of the addition of audio and tactile feedback on vection intensity compared to the visual-only condition. Lastly, Yahata et al. (2021) found that adding hot wind (35.7C) to visual feedback display forward and backward movement through a corridor of fire significantly increased participants’ vection intensity rating compared to conditions in which wind was absent. Furthermore, participants rated vection to be more intense in conditions where they perceived virtual movement through a corridor of cubes combined with either normal (18.6C) or hot wind compared to no wind. However, vection intensities for hot wind were, on average, rated lower than normal wind.

3.4.3 Mixed Effects Feng et al. (2016) identified that feet vibrations did not significantly increased vection intensity whereas winds simulating forward movement (i.e., ‘movement winds’) did. The results from the study by Lind et al. (2016) showed that vibrotactile feedback did not affect vection intensity but did increase vection compellingness. Moreover, there results indicated that adding constant vibrations to the visual-auditory stimuli was more compelling than the addition of dynamic vibrations to visual-auditory stimuli. Nilsson et al. (2012) found that tactile stimulation resulted in substantially different reports on distance travelled between virtual environments: participants rated they travelled further on a train as compared to the other environments. However, differences were observed between environments in terms of vection compellingness. Participants in the study by Riecke et al. (2005b) rated vection compellingness higher when vibrations were presented compared to when they were absent, but no such differences were found for vection intensity. The addition of airflow to expanding optic flow in the study by Seno et al. (2011) increased participants’ vection intensity whereas its addition to contracting optic flow decreased vection intensity ratings. Väljamäe et al. (2006) identified that the vibrations created by a shaker and a subwoofer marginally increased participants’ vection intensity, but no such effect was present for vection compellingess.

3.4.4 Null Effects Participants in the study by Oishi et al. (2016) did not rate their vection intensity to be significantly higher when traction forces were applied to their body compared to visual stimulation alone. Moreover, participants commented that the force felt unnatural as it was not synchronized with visual acceleration but with velocity instead. Tinga et al. (2018) found that neither the addition of clockwise nor counterclockwise circular tactile stimulation substantially increased subjective vection intensity ratings compared to when they were absent. Results from the study by Väljamäe et al. (2009) showed that the addition of vibrational stimulation to auditory vection stimuli did not substantially increase participants’ vection intensity or convincingness ratings.

3.5 General Characteristics of Studies Participants in the studies included in our literature review were between 18 to 60 years of age, with an average age of 26.1 years. However, five studies did not report on any age characteristics of their participant sample, as can be seen from the sixth column in Table 1. Tinga et al. (2018) was the only study wherein a primarily older participant sample was utilized. Furthermore, of the 459 unique participants in the studies, 99 were female and 235 were male. Six studies did not disclose the gender of their sample leaving the gender of 94 participants in the sample as unidentified. Of the 23 studies included in our review, 13 studies were published in conference proceedings and 10 studies were journal publications.

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4 DISCUSSION Although classically referred to as a visual illusion, the recent development on the definition of vection has laid a foundation for researchers to investigate the multisensory influence on (illusory) human self-motion perception. The use of multisensory stimulation in vection research (e.g., combinations of visual, auditory, and tactile feedback) is becoming more evident in literature. Research on multisensory vection can further enhance our understanding about how sensory systems are involved in human motion perception and utilize this information to increase simulator fidelity while reducing the probability of eliciting human discomfort such as motion or cybersickness. However, a review on the methodology and efficacy of tactile-mediated vection appeared to be missing from literature. Such a review could help researchers in identifying the appropriate stimulation characteristics as well as the appropriate stimulation location and help avoid reinventing the wheel. Herein, we reviewed studies on tactile-mediated vection we found through the EBSCOHost, Scopus and Web of Science literature databases, and discussed their methodologies and outcomes. Through our review and meta-analysis, we sought answers to four questions. We discuss the potential answers to each of these questions in the following sections.

4.1 How is tactile stimulation employed in vection research? We identified that tactile stimulation has been applied to a wide variety of body parts, namely the face, feet, fingers, lower back and buttocks, lower extremities, and the torso. Furthermore, the effect of stimulating of large sections of the body, such as the anterior (ventral), right lateral and posterior (dorsal) side of the body, on vection has also been investigated. The feet were the most stimulated body part of all studies reviewed, as can be seen from Table 1. Stimulation to the feet was mostly applied in the form of vibrations to enhance the sensation of virtual locomotion using vibrotactile transducers, such as the Haptuator or Acouve Lab VP408. Alternative forms of vibrational stimulation were administered using audio transducers, such as the Buttkicker LFE or Phillips GM 5532, mounted underneath chairs or platforms which required the use of amplifiers to pass the audio signal to the transducer to generate the vibrational stimulus. The duration and frequency of the vibration signals used varied between 150ms to 99s and between 7Hz to 240Hz, respectively. Furthermore, researchers generated tactile stimuli using either forces (i.e., traction) or by blowing wind. Forces were presented to participants by either pulling on the shoulder part of clothes using a pulley system or by letting participants press their fingers onto a rotating polystyrene ring. Wind stimulation was administered using either a single fan blowing at a constant speed, such as the Dyson AM01, or via an array of fans located around the participant which could present dynamic stimulation by changing the fan speed proportional to participants’ virtual velocity. Tactile stimulation was mostly presented concurrently to the stimulation of other sensory modalities, such as the visual or auditory system, however, in some studies the presence of vestibular stimulation cannot be ruled out due to the possibility that participants could move their heads.

4.2 Does tactile stimulation, in general, positively contribute to participants’ vection perception? Through our meta-analyses and qualitative appraisal of the outcome of the studies retrieved via our systematic literature review, we identified that tactile stimulation generally increases participants’ sensation of vection. However, it appears that unisensory tactile stimulation is not an effective method to elicit veciton. We identified three studies (Murata et al., 2014; Murovec et al., 2021; Nilsson et al., 2012) which incorporated tactile-only conditions in their experiments, and all three studies showed minor to no effects from unisensory tactile stimulation on vection. For example, participants in the study by Nilsson et al. (2012) rated the intensity of unisensory tactile stimulation lower compared to conditions combining visual and tactile stimulation. Moreover, vection onset latency in the unisensory condition was the highest compared to the other visuotactile conditions. Similarly, Murovec et al. (2021) found that vection intensity ratings from unisensory tactile stimulation did not differ substantially from no stimulation at all. The results from the study by Murata et al. (2014) show that participants’ vection intensity ratings from wind-only conditions were relatively small (i.e., approximately 0.4 on a 0 to 5 scale) and did not differ between conditions with different wind directions. Furthermore, Seno et al. (2011) concluded that vection could not be elicited through the application of tactile stimulation via wind on its own, however, no corroborative data was presented in the article.

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The utility of tactile stimulation apparently lies in a mediating role since most of the reviewed studies reported either positive effects or a mix of positive and null effects on vection when tactile stimulation complemented different sensory stimuli. The positively mediating effect of tactile stimulation on vection in these studies can, in part, be explained by multisensory integration. To perceive our own movement, the integration of multisensory information, such as visual, vestibular, and somatosensory cues, occurs for us to accurately estimate self-motion parameters, such as travelled distance (Churan et al., 2017; Harris et al., 2000). For example, participants in the study by Harris et al. (2000) received either visual, vestibular, or combined sensory cues regarding linear forward self-motion and had to indicate how far they perceived they had travelled. Results showed that when multiple cues were presented, participants indicated their perceived travelled distance more accurately to the actual distance travelled compared when unisensory stimulation was presented. Since vection entails the subjective experience of self-motion (i.e., “did I feel that I was moving?”, “How intense was my sensation of moving?”) and self-motion perception is modulated by multisensory input, it is likely that the presentation of multisensory, temporally correlated signals positively affects vection. There are two reasons why multisensory integration may play a role in enhancing vection, namely 1) the positive effect of sensory cue combinations on vection and 2) the reduced effect of cue combinations on vection when cue conflicts are presented. Firstly, the results of our meta-analysis show that, in general, the addition of tactile stimulation to audio, visual or audio-visual stimuli had a moderate-to-large positive effect on general vection compared. The positive effect of congruent sensory cue combinations can best be exemplified by the results from Murovec et al. (2021). The vection intensity ratings obtained by Murovec et al. (2021) for unisensory conditions show that vection was elicited more prominently by visual stimuli, followed by auditory and tactile stimuli. However, regardless of which sensory systems were conjointly stimulated, vection intensity ratings were higher when multiple sensory cues were presented compared to the respective unisensory conditions. Secondly, multiple studies identified that participants sensation of vection was lower when sensory cue conflicts were presented. When a conflict is presented between two sensory cues, multisensory integration is altered and when the conflict is substantial the integration process could break down (Greenlee et al., 2016). Correlation detection between sensory signals has a fundamental role in multisensory processing and optimal multisensory integration occurs when sensory signals are temporally correlated (Parise & Ernst, 2016). In most studies, the characteristics of the tactile stimulation were temporally aligned with the stimulation characteristics of other sensory modalities (Feng et al., 2016; Hayashizaki et al., 2015; Kitazaki et al., 2019,2016; Kruijff et al., 2016; Lind et al., 2016; Matsuda et al., 2020, 2021; Murovec et al., 2021; Riecke et al., 2005b; Väljamäe et al., 2006, 2009). For example, in the study by Murovec et al. (2021) the angular velocities of the visual, auditory, and tactile stimuli were identical and presented without delay. Similarly, Riecke et al. (2005b) increased the frequency of the vibrational stimulus proportional to the angular velocity of the visual stimulus. However, when researchers in the studies we reviewed presented sensory cue conflicts to their participants, subjective vection ratings in those trials were, on average, lower compared to trials where sensory stimulation across the modalities was coherent. For example, Kitazaki et al. (2019) manipulated the delay between the moment footstrikes occurred in the visual stimuli and the moment participants’ feet received the tactile stimulus. The authors varied the delay between 0, 0.25 and 0.5 phase, which approximated to a 0ms, 250ms and 500ms delay, respectively. Vection intensity ratings were significantly lower when either the 0.25 or the 0.5 phase delay was presented compared to baseline. Similarly, Matsuda et al. (2020, 2021) presented vibrotactile stimuli to participants feet either synchronously to the footstrikes of the virtual avatar or asynchronously by presenting them in a randomized fashion. Vection intensity ratings were significantly lower in asynchronous condition compared to synchronous condition. Lastly, it appears that there is a fine balance between the positive effects of cue combinations and the negative effects of cue conflicts. Participants in the study conducted by Feng et al. (2016), did not, on average, rate vection intensity differently when tactile stimulation in the form of movement winds was combined with feet vibrations compared to the condition with tactile stimulation from movement winds alone. Additionally, the condition with tactile stimulation through feet vibrations alone was, on average, rated lower. It could be that the vibrotactile and wind stimuli were not optimally correlated and as such the combination of tactile cues did not enhance participants’ vection. Similarly, Väljamäe et al. (2006) presented participants with two different types of vibrotactile stimulations, namely low frequency vibrations (LFVs) through a 40Hz stationary tone using a subwoofer and mechanical vibrations (MVs) through 40 Hz bursts lasting 0.3s using a custom shaker. The authors found that

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complementing auditory stimulation with MVs, on average, increased vection intensity and convincingness compared to auditory stimulation alone, whereas adding LFVs, on average, reduced vection intensity and convincingness. Furthermore, the combined presentation of audio, LFVs and MVs resulted, on average, in lower vection intensity and convincingness ratings compared to the condition in which only audio and MVs were presented. Interestingly, participants’ presence ratings, on average, appeared to increase with the number of sensory cues presented. Future research should incorporate unisensory and multisensory conditions, as well as multisensory conditions in which systematic delays are introduced between sensory cues to further our understanding on how multisensory integration affects vection.

4.3 Which parts of the body are most suitable for tactile stimulation to enhance vection perception? The results from our meta-analyses show that the most effective body part to stimulate to enhance general vection are the feet (r = .574), however, we also identified a substantial level of heterogeneity (I2 = 77%) amongst the studies included in this factor. The variation in effects can, in part, be explained by the fact that vibrational frequencies utilized in these studies varied from 10 Hz to 240 Hz. Within this frequency band, different mechanoreceptors in the foot would be activated. For example, Strzalkowski et al. (2018) reviewed the innervation density of various mechanoreceptors on the foot sole and found that the Meissner corpuscles were the most abundant and had the largest innervation area. Meissner corpuscles are most sensitive to vibrations between 10 to 50 Hz (Piccinin et al., 2021), and therefore one would expect the stimulation frequencies to lie within that range if the goal of the stimulation is merely to generate a cutaneous sensation of walking. Furthermore, frequencies of approximately 80 Hz are known to generate the proprioceptive illusion of movement (i.e., kinaesthesia; see Roll & Vedel, 1982; Seizova-Cajic et al., 2007). Thus, the use of higher frequencies might have induced a compound effect of cutaneous and kinaesthetic sensations which could have affected vection. It is noteworthy that tactile stimulation of the torso was the only application site of which the effects on vection were either negative (Rupert & Kolev, 2008), positive (e.g., Murata et al., 2014; Yahata et al., 2021) or null (Oishi et al., 2016; Tinga et al., 2018). The disparity in results could, in part, be explained either due to differing stimulation types, locations or due to variations in the temporal alignment of the multisensory stimuli. Firstly, the torso was the only location on which all three tactile stimulation types were used. Secondly, the exact stimulation location varied between studies. For example, Rupert and Kolev (2008) applied vibrational stimulation across the full length of the torso, whereas the tactile stimulation applied by Tinga et al. (2018) was limited to the area around the waist. Lastly, Oishi et al. (2016) applied traction forces to the shoulder area of the torso. Furthermore, sensory cue conflicts might have played a role in the negative and null effects found (also, see section 4.2). All participants in the study conducted by Rupert and Kolev (2008) reported a reduction in vection velocity when tactile stimulation was presented concurrently to the visual stimulus of points on a rotating sphere. Since there were no other sensory cues present, there could have been a discrepancy between the velocity of the tactile flow and the angular velocity of the visual stimulus which might have caused a cue conflict and degraded participants’ sensation of vection. Furthermore, some participants reported that, upon the application of the tactile stimulus, the rotation of the sphere halted momentarily. It is possible that these participants have perceptually switched to the temporal characteristics of the tactile stimulation and suppressed their visual input and as such lost their vection perception. The suppression of visual perception by tactile stimulation was also found by Ide and Hidaka (2013), who identified that the performance of participants visuospatial discrimination substantially degraded when the presentation of the visual stimulus was preceded by a 460Hz sinusoidal vibration applied for 200ms to participants’ fingertip that was congruent to the side on which the visual stimulus appeared. Nonetheless, the article of Rupert and Kolev (2008) did not report on any characteristics of the tactile stimuli other than its frequency. Additionally, the results did not discuss separate effects from clockwise and counterclockwise stimulation on participants’ vection sensation which could have given an insight as to what caused the degradation of participants’ vection sensation. The tactile stimulus characteristics and the separate effects from clockwise and counterclockwise stimulation were presented in the study by Tinga et al. (2018). It is most likely that the tactile stimulus was ineffective in enhancing participants’ vection since it travelled across participants’ circumference while they walked in a linear path. Specifically, the information from the proprioceptive and vestibular system, as well as the efferent copy, indicated that the participant was moving linearly whereas the tactile cue suggested rotation. Therefore, the tactile

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cue might have been perceived as incongruent and subsequently ignored due to the presence of sufficient congruent sensory information. Lastly, the null effects found by Oishi et al. (2016) were discussed by the authors themselves. The traction varied proportionally to the velocity of the virtual vehicle and participants reported that the sensation felt unnatural as the traction was not coupled to the acceleration of the virtual velocity. Based on these varying results, we would recommend further investigation into the effect of tactile stimulation of the torso on vection.

4.4 What is the most and least effective form of tactile stimulation? The results from our meta-analyses indicate that the application of forces is the most effective (r = .524) form of tactile stimulation, followed by wind (r = .442) and vibrational (r = .437) stimulation. However, through our qualitative analysis of study outcomes, we identified that one of the studies (i.e., Oishi et al., 2016) included in the factor Forces contained a null effect. Therefore, the effect of this factor should be interpreted with some caution. Although wind stimulation had a relatively larger effect than vibrations, the number of studies included in the Wind factor was rather low (N = 5) compared to the Vibrations factor (N = 16). Furthermore, both factors had substantial variance between effects, which can, in part, be explained by the stimulus characteristics and locations. For example, in the Wind factor static wind speeds varied between 2 m/s to 6.37 m/s and only one study used dynamic wind speeds varying between 0 to 4 m/s. Similar variance was evident among the vibrational frequencies: frequencies varied from 7 Hz to 240 Hz and were either static or varied proportional to participants virtual velocity. Furthermore, wind stimulation was generally applied to the face and upper body whereas vibrational stimulation locations varied from the feet, waist, dorsal body side to the lower back and buttocks. As such, it appears that tactile stimulation using vibrations and wind are equally effective, however, force stimulation requires further scientific scrutiny.

4.5 Limitations and Outlook The most prominent limitations are that the number of studies included in most factors of the meta-analyses was low and the heterogeneity in each factor was high. The high heterogeneity can, in part, be explained by the fact that the studies in our analysis used varying measures of vection intensity and convincingness. For example, Feng et al. (2016) asked participants to rate on a 5-point scale to what extent they experienced movement sensation, whereas participants in the study by Kitazaki et al. (2019; 2016) used a visual analogue scale to rate whether they felt their whole body moving forward. The lack of a singular, robust measure of vection has been highlighted previously (Väljamäe, 2009; Berti & Keshavarz, 2020). Berti and Keshavarz (2020) identified by reviewing the literature on neurophysiological studies on visually induced vection that nine different methods or scales were used to assess vection intensity in more than half of the studies included in their review. Similarly, Table 1 shows a wide variety in the scales used to assess vection intensity or convincingness between studies. We identified six studies (Lind et al., 2016; Nilsson et al., 2012; Nordahl et al., 2012; Riecke et al., 2005b; Väljamäe et al., 2006, 2009) that implemented vection intensity and convincingness ratings concurrently1. We would advocate the concurrent measurement of these two statements along with a statement rating self-motion velocity. For example, when a researcher is interested in comparing participants vection perception between single sensory stimulation and multisensory stimulation, participants may not perceive vection to be more intense, as such they would feel to strong forms of acceleration or large perturbations. However, participants may feel more convinced to be moving due to the multisensory feedback. Conversely put, a participant might not perceive through a combination of visual, auditory, and tactile feedback that virtually moving at a slow pace is intense, however, they could be more convinced of the illusory form of self-motion due to the multiple forms of feedback. Complementing the intensity and convincingness ratings with a self-motion velocity rating (e.g., see Riecke et al., 2009) would allow researchers to identify 1) to what extent participants were convinced they were moving, 2) how intense they experienced the motion and 3) quantify how fast they perceived to be moving. Another factor which may have played a part in the high heterogeneity could be the definition of vection used by researcher and subsequently participants’ task instructions. Most of the reviewed articles presented the definition of vection as an illusory visual perception of self-motion (e.g., Kitazaki et al., 2019, 2016; Lind et al.,

1 Of note, Nilsson et al. (2012) and Nordahl et al. (2012) reported on vection compellingness and intensity, however, intensity was defined and reported on as an estimation of distance in metres.

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2016; Nilsson et al., 2012; Nordahl et al., 2012; Riecke et al., 2009; Väljamäe et al., 2009), whilst investigating the effect of multisensory stimulation on vection. Additionally, only 3 out of 23 articles provided an explicit description in the manuscript on how the definition, or concept, of vection was explained to the participants. For example, Riecke et al. (2009) exemplified vection by physically rotating each participant four times whilst playing the auditory stimuli in synchrony with the physical rotations. Kitazaki et al. (2019) instructed the participants that they experienced a self-motion sensation if they felt they were passively moving. Tinga et al. (2018) provided participants with written instructions to assist participants in quantifying the subjective measures of self-motion. The instructions detailed the train illusion (see Introduction) as well as a description of the illusory motion after- effect that is experienced after being rotated on a desk-chair However, Soave et al. (2020) identified from their post-experiment qualitative survey that participants generally did not understand the concept of vection and some reported that the description of the train illusion was incoherent to a self-motion sensation. The conflicting appraisal of vection by researchers could be transferred onto participants when participants are explained that vection is experienced as a visual illusion, while being subjected to multisensory stimulation. Thus, there is a clear need for qualitative studies (e.g., see Soave et al., 2021) in vection research, as their results can be used to improve participants’ task instructions as well as the terminology that is used to assess vection to mitigate heterogeneity. It seems pertinent for future research to define standardized, unambiguous statements regarding vection intensity and convincingness, along with appropriate unambiguous anchors, which participants can use to subjectively rate their self-motion perception.

5 CONCLUSIONS Herein we reviewed the scientific literature on the methodology and efficacy of tactile stimulation in vection research. Tactile stimulation has mostly been applied in the form of vibrations to the feet. However, alternative stimulation forms, such as wind stimulation and the application of forces, on various body parts have shown promising results in enhancing vection. The authors conclude that the application of tactile stimulation to the torso deserves further scientific scrutiny due to the disparity between study outcomes. Overall, tactile stimulation as a unisensory stimulus does not appear to be an effective method to elicit vection, but tactile stimulation is an effective, positive mediator to vection when it is presented concurrently to other sensory stimuli and the temporal characteristics of the stimuli are aligned.

DATA AVAILABILITY The data generated during and/or analysed during the current study will become available upon publication in the DRO repository.

ACKNOWLEDGMENTS This research was supported by the Australian Research Council (ARC) (Project ID: DE210101623) as well as by the Institute of Intelligent Systems Research and Innovation (IISRI). The authors would like to thank A/Prof. Alexander Mussap for his insights during various discussions on the topic of vection and his suggestions on the statistical steps of the meta-analysis. The authors would like to acknowledge that the research for this manuscript was conducted on the land of the Woi Wurrung and Wadawurrung people of the Kulin Nation, the traditional owners of the lands, and we would like to pay our respect to their Elders past and present and emerging. This is a pre-print of an article published in [insert journal title]. The final authenticated version is available online at: https://doi.org/[insert DOI].

CONFLICTS OF INTEREST The authors have no conflicts of interest to declare that are relevant to the content of this article.

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Appendix A

Table S1: Effect sizes and variables from studies used in meta-analysis. Author r 95% Confidence Interval N Variable Stimulus Location Stimulus type Intensity Additional Stimuli Test Feng et al. (2016) 0.246 -0.18 0.67 24 Intensity Face, Arms, Feet Audio, Vibration, Wind 4 Visual MM Feng et al. (2016) 0.143 -0.28 0.57 24 Intensity Feet Vibration ND Visual VT Feng et al. (2016) 0.041 -0.39 0.47 24 Intensity Feet Vibration ND Audio-visual AVT Feng et al. (2016) 0.298 -0.13 0.73 24 Intensity Face, Arms Wind 4 Visual VT Feng et al. (2016) 0.298 -0.13 0.73 24 Intensity Face, Arms Wind 4 Audio-visual AVT Feng et al. (2016) 0.149 -0.28 0.58 24 Intensity Face, Arms, Feet Wind, Vibration 4 Visual VT Kitazaki et al. (2016) 0.801 0.06 1.54 10 Intensity Feet Vibration 120 Visual VT Kitazaki et al. (2016) 0.546 -0.01 1.13 15 Intensity Feet Vibration 120 Visual VT Kitazaki et al. (2016) 0.508 0.09 0.93 25 Intensity Feet Vibration 120 Visual VT Kitazaki et al. (2019) 0.709 0.14 1.28 15 Intensity Feet Vibration 240 Visual VT Kitazaki et al. (2019) 0.438 -0.13 1.00 15 Intensity Feet Vibration 240 Visual VT Kruijff et al. (2016) 0.483 -0.17 1.14 12 Intensity Feet Vibration ND Audio-visual AVT Kruijff et al. (2016) 0.737 0.08 1.39 12 Intensity Feet Vibration ND Audio-visual AVT Kruijff et al. (2016) 0.746 0.11 1.41 12 Intensity Feet Vibration ND Audio-visual AVT Lind et al. (2016) 0.381 -0.14 0.90 17 Intensity Dorsal Vibration 75 Audio-visual AVT Lind et al. (2016) 0.458 -0.07 0.98 17 convincingness Dorsal Vibration 75 Audio-visual AVT Murata et al. (2014) 0.327 -0.29 0.95 13 Intensity Face, Torso Wind 5.5 wind direction AVT Murata et al. (2014) 0.408 -0.21 1.03 13 Intensity Face, Torso Wind 5.5 Body sway AVT Murovec et al. (2021) 0.339 -0.09 0.77 24 Intensity Fingers Friction 45 deg/s none T Murovec et al. (2021) 0.423 0.00 0.85 24 Intensity Fingers Friction 45 deg/s General Effect AVT Murovec et al. (2021) 0.516 0.09 0.94 24 Intensity Fingers Friction 45 deg/s Audio AT Murovec et al. (2021) 0.056 -0.37 0.48 24 Intensity Fingers Friction 45 deg/s Visual VT Murovec et al. (2021) 0.082 -0.35 0.51 24 Intensity Fingers Friction 45 deg/s Audio-visual AVT Nordahl et al. (2012) 0.373 -0.02 0.76 28 Intensity Feet Vibration 50 Audio-visual AVT Nordahl et al. (2012) 0.390 0.00 0.78 28 convincingness Feet Vibration 50 Audio-visual AVT Oishi et al. (2016) 0.624 -0.03 1.28 12 Intensity Torso Pressure ND Visual VT

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Riecke et al. (2005) 0.045 -0.38 0.47 24 Intensity Lower extremities Vibration 15-90 Visual VT Riecke et al. (2005) 0.417 0.00 0.85 24 convincingness Lower extremities Vibration 15-90 Visual VT Riecke et al. (2009) 0.619 0.03 1.21 14 Intensity Lower extremities Vibration 7 Audio AT Riecke et al. (2009) 0.662 0.07 1.25 14 realism Lower extremities Vibration 7 Audio AT Seno et al. (2011) 0.368 -0.14 0.87 18 Intensity Face Wind 6.37 Visual VT Soave et al. (2020) 0.152 -0.50 0.80 12 Intensity Lower extremities Vibration ND Audio-visual AVT Tinga et al. (2018) 0.093 -0.23 0.41 40 Intensity Waist Vibration 158 Biomechanical BMT Tinga et al. (2018) 0.098 -0.22 0.42 40 Intensity Waist Vibration 158 Biomechanical BMT Tinga et al. (2018) 0.098 -0.22 0.42 40 Intensity Waist Vibration 158 Biomechanical BMT Valjamae et al (2006) 0.353 -0.08 0.79 23 Intensity Lower extremities Vibration 40 Audio AT Valjamae et al (2006) -0.058 -0.50 0.38 23 convincingness Lower extremities Vibration 40 Audio AT Valjamae et al (2006) 0.056 -0.38 0.49 23 convincingness Lower extremities Vibration 40 Audio AT Valjamae et al (2006) 0.067 -0.37 0.51 23 convincingness Lower extremities Vibration 40 Audio AT Valjamae et al. (2009) 0.000 -0.54 0.54 16 Intensity Lower extremities Vibration 15 Audio AT Valjamae et al. (2009) 0.000 -0.54 0.54 16 convincingness Lower extremities Vibration 15 Audio AT Yahata et al. (2021) 0.375 -0.19 0.94 15 Intensity Face, Torso Wind 2 Visual VT Yahata et al. (2021) 0.596 0.03 1.16 15 Intensity Face, Torso Wind 2 Visual VT Yahata et al. (2021) 0.428 -0.12 0.97 16 Intensity Face, Torso Wind 2 Visual VT Note: AT = effect on vection of adding tactile stimulation to auditory stimuli. AVT = effect on vection of adding tactile stimulation to audio-visual stimuli. BMT = effect on vection of adding tactile stimulation to biomechanical stimulation. MM = effect on vection of adding multiple forms of tactile and auditory stimulation to visual stimuli. ND = Not Disclosed. VT = effect on vection of adding tactile stimulation to visual stimulation.

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