Sebastian Vizcay
email: sebastian.vizcay@inria.fr

Panagiotis Kourtesis

Ferran Argelaguet

Claudio Pacchierotti

Maud Marchal

Design, Evaluation and Calibration of Wearable Electrotactile Interfaces for Enhancing Contact Information in Virtual Reality

Keywords: Electrotactile Feedback, Virtual Reality, Human Computer Interaction

A C T

Electrotactile feedback is a convenient tactile rendering method thanks to reduced form factor and power consumption. Yet, its usage in immersive virtual reality has been scarcely addressed. This paper explores how electrotactile feedback could be used to enhance contact information for mid-air interactions in virtual reality. We propose an electrotactile rendering method which modulates the perceived intensity of the electrotactile stimuli according to the interpenetration distance between the user's finger and the virtual surface. In a first user study (N=21), we assessed the performance of our method against visual interpenetration feedback and no-feedback. Contact precision and accuracy were significantly improved when using interpenetration feedback. The results also showed that the calibration of the electrotactile stimuli was key, which motivated a second study exploring how the calibration procedure could be improved. In a second study (N=16), we compared two calibration techniques: a non-VR keyboard and a VR direct interaction method. While the two methods provided comparable usability and calibration accuracy, the VR method was significantly faster. These results pave the way for the usage of electrotactile feedback as an efficient alternative to visual feedback for enhancing contact information in virtual reality.

Introduction

Visual feedback is particularly important for contact accuracy 5 and precision [3]. However, when kinesthetic feedback is not 6 available, if no other measures are adopted, the user's avatar 7 might interpenetrate the virtual content, which could have a 8 negative impact on the accuracy, precision, and the realism 9 of the interaction. To avoid such an undesired behavior and 10 facilitate mid-air interactions in VR, a popular technique is the use of the God-object Method, where the virtual hand is constrained by the collision with the virtual object(s) [START_REF] Zilles | A constraint-based god-object method for haptic display[END_REF][START_REF] Sagardia | A fast and robust six-dof god object heuristic for haptic rendering of complex models with friction[END_REF]. When using the God-object Method, there is a decoupling of the visual representation of the user's avatar (e.g., the virtual hand) from its actual position when the avatar is constrained on the virtual object's surface whereas the actual tracked position would be inside the object [START_REF] Prachyabrued | Design and Evaluation of Visual Interpenetration Cues in Virtual Grasping[END_REF]. Moreover, when using this popular technique, while the virtual hand is rendered on the collided object's surface, the user's physical hand is still able to move in the real environment unconstrained (i.e., penetrating the virtual object's coordinates), which results in failing to perceive the inaccuracy and imprecision of the contact [START_REF] Zilles | A constraint-based god-object method for haptic display[END_REF][START_REF] Sagardia | A fast and robust six-dof god object heuristic for haptic rendering of complex models with friction[END_REF].

A cost effective solution is to use tactile feedback to render the contact. Tactile feedback devices can provide vibrotac-tile, pressure, or skin stretch feedback sensations [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives[END_REF]. However, these displays need to embed one or more mechanical actuators that move an end-effector in contact with the user's skin, limiting their wearability, portability, and comfort [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives[END_REF]. In this respect, electrotactile haptic stimulation has been recently recognized as a promising technique to provide rich tactile sensations across the hand or arm through a single wearable actuator [START_REF] Chouvardas | Tactile displays: Overview and recent advances[END_REF]. Applying electrical stimulation to the skin elicits tactile sensations by directly activating the sensory nerves, de facto bypassing the skin mechanoreceptors. The electrical current produces a local depolarization near the skin, triggering an action potential. The current is generated by two or more electrotactile interfaces (electrodes). With respect to other tactile solutions, electrotactile stimulation only requires very thin electrodes placed at the sensation point (e.g., the fingertip), providing a wearable and comfortable solution to tactile haptics.

Nevertheless, despite its promising features, the benefits of electrotactile feedback in VR interactions are still underinvestigated. In a VR pilot study (N=3), electrotactile feedback provided haptic information pertinent to heat, jolt, and texture [START_REF] Pamungkas | Electro-tactile feedback system to enhance virtual reality experience[END_REF]. In a small size user study (N=10), electrotactile feedback was able to generate tactile sensations such as roughness, friction, and hardness [START_REF] Yem | Wearable tactile device using mechanical and electrical stimulation for fingertip interaction with virtual world[END_REF]. In a VR user study (N=19), electrotactile feedback was successful in improving grasping [START_REF] Hummel | A lightweight electrotactile feedback device for grasp improvement in immersive virtual environments[END_REF].

However, an inappropriate application of electrotactile feedback may elicit undesirable effects such as absence of sensation, skin irritation, burns, electric shock, and discomfort [START_REF] Kaczmarek | Electrotactile and vibrotactile displays for sensory substitution systems[END_REF].

A personalized calibration of electrotactile feedback, where the intensity of the electrotactile feedback is adjusted to the personal sensational and discomfort thresholds of the user, may prevent these adverse effects [START_REF] Stephens-Fripp | A review of non-invasive sensory feedback methods for transradial prosthetic hands[END_REF].

This paper presents the design and evaluation of an electrotactile feedback rendering method to enhance contact information for mid-air interactions with virtual objects in virtual reality. The proposed method modulates the perceived intensity of the electrotactile stimuli according to the interpenetration distance between the user's finger and the virtual surface (i.e., the distance between the real and the virtual hand). Moreover, as the calibration phase is a key element to provide compelling and effective feedback, this paper further explores the benefits of embedding the calibration procedures directly in VR to reduce the calibration time and increase the user's comfort. Precisely, we propose a calibration method that can be integrated directly into the virtual environment. In summary, the main contributions of our work are:

• The design of an electrotactile feedback technique for enhancing contact information in VR.

• A user study (N=21) for evaluating electrotactile interpenetration feedback's performance against no interpenetration feedback, a visual interpenetration feedback, and a visual-electrotactile interpenetration feedback.

• A user study (N=16) evaluating two different calibration procedures, a keyboard-based and a VR-based method, assessing the calibration time and the dynamic range.

The paper is structured as follows, Section 2 presents an overview of the state of the art on wearable haptics, electrotactile feedback and contact rendering in VR. Then, Section 3 describes the proposed electrotactile system for interpenetration 58 rendering. Section 4 describes an experiment assessing the ad-59 vantages and disadvantages of the proposed electrotactile sys-60 tem. Section 5 describes and evaluates a VR-based calibration 61 method conceived to speed up the calibration process. Finally, 62 the paper concludes with a global discussion and the concluding 63 remarks. Popular techniques to provide rich wearable tactile feedback 67 are through moving platforms, that can orient and/or trans-68 late on the skin, pin-arrays, shearing belts and tactors, pneu-69 matic jets, and balloon-based systems [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives[END_REF]. Frisoli et al. [START_REF] Frisoli | A fingertip haptic display for improving curvature discrimination[END_REF] 70 were among the first to present a fingertip tactile display for 71 improving curvature discrimination using a moving platform. 72 Their system was composed of a parallel platform and a serial 73 wrist. Gabardi et al. [START_REF] Gabardi | A new wearable fingertip haptic interface for the rendering of virtual shapes and surface features[END_REF] improved this device and applied it 74 in VR interaction. The pose of the user's finger was tracked 75 through external optical sensors and collisions between the fin-76 ger avatar and the virtual surface were rendered by the device. 77 Minamizawa et al. [START_REF] Minamizawa | A wearable haptic display to present the gravity sensation-preliminary observations and device design[END_REF][START_REF] Prattichizzo | Remotouch: A system for remote touch experience[END_REF] presented a wearable fingertip de-78 vice for weight rendering in VR. It consisted of two DC mo-79 tors moving a belt in contact with the user's fingertip. A sim-80 ilar device was also used in [START_REF] Pacchierotti | The hRing: a wearable haptic device to avoid occlusions in hand tracking[END_REF] for multi-finger manipulation 81 of objects in VR, in [START_REF] Aggravi | Design and evaluation of a wearable haptic device for skin stretch, pressure, and vibrotactile stimuli[END_REF] for controlling multi-robot systems 82 in VR, and in [START_REF] Salazar | Altering the stiffness, friction, and shape perception of tangible objects in virtual reality using wearable haptics[END_REF][START_REF] Tinguy | Enhancing the stiffness perception of tangible objects in mixed reality using wearable haptics[END_REF] for augmenting tangible objects in VR. 83 Similarly, Girard et al. [START_REF] Gosselin | Design and development of miniature wearable haptic interfaces for the fingertips[END_REF] developed a wearable fingertip de-84 vice capable of rendering 2-DoF skin stretch stimuli in VR. The 85 considered use cases comprised tapping on a virtual bottle and 86 feeling the texture and weight of a virtual object.

Electrotactile feedback 88

Due to the difficulty in designing effective interaction 89 paradigms, electrotactile interfaces have rarely been used in VR 90 scenarios. Jorgovanovic et al. [START_REF] Jorgovanovic | Virtual grasping: closed-loop force control using electrotactile feedback. Computational and mathematical methods in medicine[END_REF] evaluated the capabilities of 91 human subjects to control grasping force in closed loop using 92 electrotactile feedback. It was tested in an experiment of virtual 93 robotic grasping. More recently, a pilot study by Pamungkas 94 and Ward [START_REF] Pamungkas | Electro-tactile feedback system to enhance virtual reality experience[END_REF] used electrotactile stimulation on the hand to con-95 vey the sensation of contacts in VR. Use cases comprised play-96 ing with a virtual bouncing ball, setting up a camp fire, feel-97 ing different surface textures, and shooting a gun. Hummel et 98 al. [START_REF] Hummel | A lightweight electrotactile feedback device for grasp improvement in immersive virtual environments[END_REF] developed an electrotactile delivery system composed 99 of a small tactor with eight electrodes for each finger. They 100 tested it in three VR assembly tasks for remote satellite ser-101 vicing missions, which included pressing a button, switching a 102 lever switch, and pulling a module from its slot. In another pilot 103 study, Sato et al. [START_REF] Sato | Electrotactile display for integration with kinesthetic display[END_REF] combined electrotactile feedback with a 104 PHANToM Omni kinesthetic display for rendering spatial dis-105 tributed touch sensation. Finally, Yem et al. [START_REF] Yem | Effect of Electrical Stimulation Haptic Feedback on Perceptions of Softness-Hardness and Stickiness while Touching a Virtual Object[END_REF] employed elec-106 trotactile stimulation to elicit flexion/extension illusory move-107 ments to the user's fingertip. Doing so, the system was able to 108 induce haptic feedback sensations, providing information about 109 virtual objects' stiffness and stickiness properties.

110

A major challenge for electrotactile interfaces is the calibra-111 tion of the electrotactile parameters for a given user. A number 112 of studies have attempted to automate and improve the calibration process. Gregory et al. [START_REF] Gregory | Towards on-line fingertip bio-impedance identification for enhancement of electro-tactile rendering[END_REF] developed a circuit model for identifying and classifying the parameters of the skin-electrode interface. Similarly, Fadali et al. [START_REF] Fadali | Electro-tactile preference identification using fuzzy logic[END_REF] used a model with fuzzy logic for detecting preferences pertinent to tactile sensations. Also, a real-time feedback loop was developed by Kajimoto [START_REF] Kajimoto | Electrotactile display with real-time impedance feedback using pulse width modulation[END_REF], destined to monitor the skin's impedance in order to make the system regulate the electrotactile feedback's intensity. Comparably, Akhtar et al. [START_REF] Akhtar | The relationship between energy, phase charge, impedance, and perceived sensation in electrotactile stimulation[END_REF][START_REF] Akhtar | Controlling sensation intensity for electrotactile stimulation in human-machine interfaces[END_REF] delivered models for measuring the skin's impedance and adjusting the electrotactile feedback parameters. Rahimi et al. [START_REF] Rahimi | Non-Linearity of Skin Properties in Electrotactile Applications: Identification and Mitigation[END_REF][START_REF] Rahimi | Adaptive spatial mapping of electro-tactile threshold based on subdivision bio-impedance feedback[END_REF] implemented an automatic recurrent calibration process for legally blind users of a Braille text-reading assistive system. Finally, Isakovic et al. [START_REF] Isakovic | Optimization of Semiautomated Calibration Algorithm of Multichannel Electrotactile Feedback for Myoelectric Hand Prosthesis[END_REF] strived to offer an optimization of the calibration process for providing the users with a personalized electrotactile feedback.

Contact information in VR

In the last years, researchers focused on the sensation of making and breaking contact [START_REF] De Tinguy | Weatavix: Wearable actuated tangibles for virtual reality experiences[END_REF][START_REF] Chinello | A three revolute-revolute-spherical wearable fingertip cutaneous device for stiffness rendering[END_REF][START_REF] Chinello | A modular wearable finger interface for cutaneous and kinesthetic interaction: control and evaluation[END_REF][START_REF] Young | Compensating for fingertip size to render tactile cues more accurately[END_REF][START_REF] De Tinguy | Weatavix: Wearable actuated tangibles for virtual reality experiences[END_REF], as it is proven to be an important factor for immersion in VR. Kuchenbecker et al. [START_REF] Kuchenbecker | The touch thimble: Providing fingertip contact feedback during pointforce haptic interaction[END_REF] endowed a desktop kinesthetic interface with a passive tactile end-effector. The kinesthetic feedback provided by the desktop device bends the internal springs of the tactile end-effector and brings a shell in contact with the user's finger, providing the sensation of making/breaking contact with the virtual object. In a similar fashion, Gonzalez et al. [START_REF] Gonzalez | Smooth transition-based control of encounter-type haptic devices[END_REF] attached a ring of optical sensor to the end-effector, being able to measure the distance of the fingertip from the ring and adjust the transition between free space and contact. Finally, Prachyabrued and Borst [START_REF] Prachyabrued | Design and Evaluation of Visual Interpenetration Cues in Virtual Grasping[END_REF] evaluated the impact of visual feedback in pinch grasping a virtual object, where the best performance was obtained when showing both hand models (tracked and constrained) and when coloring the fingers of the object being grasped.

To the best of our knowledge, the effects of using electrotactile feedback for enhancing contact information in VR mid-air interactions has scarcely been studied.

Design of electrotactile interpenetration feedback

The tactile sensation elicited by electrotactile stimulation can be controlled by the parameters chosen for the design of the electrodes and the parameters of the delivered electrical signal [START_REF] Kaczmarek | Interaction of Perceived Frequency and Intensity in Fingertip Electrotactile Stimulation: Dissimilarity Ratings and Multidimensional Scaling[END_REF][START_REF] Folgheraiter | A multi-modal haptic interface for virtual reality and robotics[END_REF][START_REF] Kajimoto | Tactile feeling display using functional electrical stimulation[END_REF][START_REF] Lozano | Electrotactile stimulation on the tongue: Intensity perception, discrimination, and cross-modality estimation[END_REF]. Individual pads in an electrode can be disabled or enabled (enabled as either cathode or anode) meanwhile signal's intensity, pulse width and frequency can be increased/decreased to apply some modulation. Pad selection determines the location where the stimulus is going to be applied.

Changes in the current intensity is the most common way to increase/decrease the strength of the sensation, but the feeling is highly variable across subjects and relatively small increases can quickly elicit uncomfortable sensations. Changes in the pulse width and frequency can also elicit changes in the perceived strength of the sensation, although less significantly than when altering the current intensity [START_REF] Aiello | Multidimensional electrocutaneous stimulation[END_REF]. Changes in the frequency are also employed to increase/decrease the perceived speed of the stimulation.

Given the disadvantages of intensity modulation, we fixed the 56 intensity value for each participant, chosen after a brief calibra-57 tion so as to avoid any undesired uncomfortable/painful sensa-58 tion. We chose pulse width modulation to control the strength 59 of the sensation and frequency modulation to control its speed. 60 We chose to place the electrodes at the fingertip, as it is the area 61 of the body most often used for pointing, grasping, and manip-62 ulating objects [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives[END_REF]. To produce the stimulation at the center of 63 the finger pad, we select an anode-cathode configuration with 64 the widest possible dynamic range for the given electrode. As 65 mentioned before, we modulate the electrotactile interpenetra-66 tion feedback proportionally to the distance between the con-67 strained user's fingertip avatar (i.e., the object surface) and its 68 actual position as tracked by the system. In other words, both 69 the perceived intensity and speed of the electrotactile sensation 70 increase as the user's physical hand interpenetrates the virtual 71 object.

72

To achieve this effect, the pulse width is modulated linearly 73 from 200 µs to 500 µs. On the other hand, we considered the 74 perception of frequency to be logarithmic [START_REF] Varshney | Why do we perceive logarithmically?[END_REF] and we apply 75 a gamma correction so as to linearize how fast the tingles are 76 perceived. The proposed frequency modulation allows us to ex-77 plore a range of frequencies from 30 Hz to 200 Hz, which is the 78 maximum frequency of the device. Fig. 1 shows the two inputs 79 with respect to the normalized interpenetration (1: maximum, 80 0: zero, see subsection 3.2 for the details). Choices regarding 81 the range of stimulation and the active pads have been done 82 after a short preliminary study, so as to provide the most com-83 fortable tactile sensations to the finger pad. Our custom electrotactile stimulator has 32 channels, to 86 which up to 5 electrodes can be connected simultaneously. Each 87 channel may be defined either as a cathode or as an anode. The 88 stimulator produces a biphasic cathodic stimulation through 89 square waves. Electrical intensity and pulse width can be set 90 per each channel in the ranges of [0.1, 9] mA and [START_REF] Akhtar | Controlling sensation intensity for electrotactile stimulation in human-machine interfaces[END_REF]500] µs, 91 respectively. The stimulus frequency can be set in the range [1, 92 200] Hz.

93

We used electrodes whose cathodes are distributed in a ma-94 trix array of 2 rows by 3 columns, surrounded by two larger lat-95 eral anodes that are interconnected by a segment going through 96 both rows of cathodes (see the insets in the top-left corner 97 of Figure 2). This particular layout has been designed to widen 1 the dynamic range of sensations.

System design 3

The interpenetration of the finger avatar into the virtual con-4 tent drives our pulse width and frequency modulation. After a 5 series of pilot user studies, we determined that, for a cube of The position of the participant's hand is tracked using a HTC for the user to precisely assess the amount of interpenetration 37 between his/her finger and the virtual surface without any additional feedback.

Our main hypothesis is that additional interpenetration feedback, either visual and/or electrotactile, would increase the awareness of the user, effectively decreasing the amount of interpenetration. Yet, electrotactile interpenetration feedback will provide a more coherent experience. In addition to consider the electrotactile interpenetration feedback method presented in the previous section, for comparison purposes, we also modulated the availability of visual cues. First, we considered a visual interpenetration feedback technique. Second, we considered the interaction with two different virtual objects, a fully-opaque virtual cube and a wireframe-only cube. We considered the latter so as to limit the visual cues which could anticipate the contact with the virtual object.

Hence, the independent variable (IV) Interpenetration Feedback has four levels: 1) No Interpenetration Feedback; 2) Visual Interpenetration Feedback; 3) Electrotactile Interpenetration Feedback, 4) Visual-electrotactile Interpenetration Feedback (i.e., both interpenetration information is provided: visually and haptically). The four levels of the IV are examined in two object rendering methods: 1) fully-opaque and 2) wireframe-only. In the following, we detail how these techniques are implemented in our experimental study.

Experimental task

The task required participants to touch a virtual surface (a cube of size 15 × 15 × 15 cm) which was located on a virtual table (see Figure 3). Participants started the experience in a seated position in front of said virtual table. The cube was placed on the user's left side, while a resting area was located on the user's right side. For each trial, participants were asked to start with their right hand in the resting area. Then, they were asked to reach precisely with their index finger the top side of the virtual cube while keeping a steady contact for three seconds. Finally, they were notified that they should return their hand back to the resting area. Participants were instructed to minimize the interpenetration between the virtual surface and their real index finger while ensuring a continuous contact with the cube. To ensure that all participants kept a consistent timing, auditory feedback (a short beep sound) was used to notify the users when they had to start the trial and when the three seconds of contact were achieved. During the whole interaction, participants were asked to keep their hand in a closed fist, with the index finger fully extended for facilitating a similar posture and an approximate collocation between the physical and the virtual hand. The experimenter was prompting each participant to have this posture when a new block was starting, while during the breaks between the blocks, the participant could have a rest and move her/his hand and fingers freely or just relax, which assisted with avoiding a postural fatigue.

Electrotactile interpenetration feedback calibration

The calibration of the electrotactile interpenetration feedback is a key step to ensure that all participants perceived a consistent tactile feedback. As the calibration cannot be done automatically, participants were asked to calibrate the intensity of the electrotactile interpenetration feedback multiple times throughout the experiment. If the calibration is not done per each user, parameters such as the skin's conductivity and/or a tolerance could result in stimuli that are not perceived (i.e., too low intensity) or uncomfortable or even painful (i.e., too high intensity).

The right range of current intensity was determined using the method of limits. Starting from a low intensity value, participants increased the intensity by pressing a key in a keyboard using steps of 0.1 mA. This incremental procedure continued, step by step, until the participant confirmed that the electrotactile feedback was perceived, defining his/her sensation detection threshold. Then, the incremental approach continued until the participant confirmed that the electrotactile feedback caused discomfort, defining his/her pain/discomfort threshold.

Similarly, starting from a high intensity value, the intensity was decreased considering steps of 0.1 mA. This starting high intensity value was defined as the 3rd quartile of the range between the detection and pain/discomfort thresholds. This decremental procedure continued, step by step, until the participant confirmed that the electrotactile feedback was not perceived anymore.

During the entire calibration process, the signal frequency was set to 200 Hz and the pulse width to 500 µs. These values were chosen as they represent the strongest stimulation that could be achieved along the experiment at max finger interpenetration. The final intensity value that was used throughout the experiment was calculated from a linear interpolation between the detection and discomfort thresholds. We chose an intermediate value between these thresholds, as it would result in a perceivable yet comfortable stimulus. The VR application was built using Unity in conjunction with the SteamVR Unity plugin (see Figure 3). The collisions were directly handled by the SteamVR plugin and the Unity physics simulation. A blackboard was used for providing any critical information/instructions within the participant's field of view.

Participants and apparatus

User representation and visual interpenetration feedback

The user could only see a visual representation of their right hand (avatar). As stated earlier, the hand avatar cannot go through the virtual object so as to better mimic a real interaction. The hand is always kept in a closed fist, with the index finger fully extended, which is the same pose we asked participants to keep while interacting with the cube (see Figure 4). An outline effect was used as visual interpenetration feed-58 back (see Figure 4). Outline effects are commonly used to de-59 note interactivity or selection [START_REF] Zhao | SeeingVR: A set of tools to make virtual reality more accessible to people with low vision[END_REF][START_REF] Sidenmark | Outline Pur-75 suits: Gaze-assisted Selection of Occluded Objects in Virtual Reality[END_REF]. However, the imple-60 mented outline was dynamically rendered proportional to in-61 terpenetration's depth. The outline was parameterized using a 62 scale factor and the size of the border. The scale factor went 63 from ×1 (edge of 15 cm 3 ) to ×1.2 (edge of 18 cm 3 ). The border 64 varied between 1 and 5 pixels (see Figure 4).

65

When both electrotactile and visual interpenetration feed-66 backs are provided, a mismatch between the two modalities 67 may result in a haptics' uncanny valley effect, which compro-68 mises the performance [START_REF] Berger | The uncanny 78 valley of haptics[END_REF]. For this reason, the modification 69 of border size and width of the outline was determined through 70 a pilot study. The choice of these particular parameters aimed 71 to ensure that, comparably to the electrotactile interpenetration 72 feedback, the perception of the "intensity" of the visual feed-73 back is proportional to the size of the interpenetration. This study received the approval of the authors' institution 76 ethical committee. As it was carried out during the COVID-19 77 pandemic, a preventive hygiene and disinfection protocol was 78 implemented. Participants signed an informed consent form 79 prior to their participation and we briefly explained to them the 80 principle of how electrotactile feedback works, the type of sen-81 sations it can elicit and how the intensity needs to be calibrated. 82 The set up consisted of a VR area, a table, and a chair. The table 83 was co-located with the virtual table. A pre-exposure question-84 naire was filled to acquire demographic data. Participants went 85 through a tutorial for performing the experimental task. The 86 execution of the trials were divided into two halves by a recali-87 bration of the intensity. The experiment followed a latin square 88 design, 4 types of interpenetration feedback × 2 types of cube 89 shading × 2 experiment halves (i.e., 4 × 2 × 2). Each exper-90 iment's half had 4 blocks, where each block consisted of 12 91 repetitions. In total, each participant performed 96 repetitions 92 (i.e., 48 per experiment's half). In total, 3 calibrations were per-93 formed a) initial calibration: before first half; b) middle calibra-94 In order to answer the hypothesis of our experiment and con-6 sidering the experimental task, we measured the following met- and not oscillatory contact with the virtual surface (precision).

18

In this respect our hypotheses were: The sensation and discomfort thresholds (in mA) were obtained 30 during the three calibration processes. We expected that the 31 thresholds will vary due to changes in skin conductivity or due 32 to habituation. In this respect our hypothesis was: questions between the interpenetration feedback modalities. In this respect our hypotheses were:

• [H6] Electrotactile interpenetration feedback will be reported as useful and coherent.

• [H7] There will be no significant differences between visual and electrotactile interpenetration feedback in terms of usefulness, coherence, and/or resemblance.

Results

The homogeneity and normality assumptions were examined. The performance variables violated the normality assumption. The values were converted into logarithms since the variables' distributions were substantially positively skewed. No violation was then detected. The same amendments were made for the intensity values, which also violated the normality assumption. Finally, as the shading condition showed no significant results (which suggests the rejection of H3) and for the sake of clarity, the shading condition will not be considered in the results report. Thus, for the following analyses, the conditions were the type of interpenetration feedback and the "half" of the experiment (whether the trial was performed in the first half of the experiment, before the middle calibration, or after that in the second half).

A two-way repeated measures ANOVA was performed for each performance variable, as well as a post-hoc pairwise comparisons test respectively. When the sphericity assumption was violated, then the Greenhouse Geisser's correction was considered. Furthermore, a pairwise comparison was conducted to explore potential differences in the intensity values amongst the three calibrations (i.e., initial, middle, and final). Hedge's g and the ω 2 were preferred as they are more parsimonious and reliable metrics of effect sizes of the ANOVA and post-hoc comparisons respectively [START_REF] Lakens | Calculating and reporting effect sizes to facilitate cumulative 80 science: a practical primer for t-tests and anovas[END_REF]. Also, a Pearson's correlational analysis was performed to investigate the presence of relationships between the intensity values and the performance variables. Finally, the post-exposure self-reports (Likert scale) provided by the participants were explored. A non-parametric pairwise comparison was implemented to examine the presence of differences on the questionnaire's items. The Bonferroni correction was implemented accordingly to the number of comparison's pairs in each analysis to amend p-values' inflation due to multiple comparisons. The descriptive statistics for all performance variables and the intensities, as well as the results for the maximum interpenetration are all included in the supplementary material for completeness.

Index finger interpenetration

Average Index Interpenetration -Accuracy. The ANOVA's outcomes indicated that all effects were statistically significant. The type of feedback produced a main effect of F(1.97, 39.31) = 25.89, p < .001 postulating a substantial difference amongst the feedback types. In line with H1, ω 2 = 0.54, 95% CI[0.35, 0.66] suggests a very large effect of the type of feedback on average interpenetration (i.e., accuracy). In support of H4, the half of the experiment yielded an effect of F(1, 20) = 31.74, p < .001, suggesting a significant difference between the two halves of the experiment with a very The post-hoc pairwise comparisons are displayed in Figure 5.

The results support both H1 and H2: use of interpenetration feedback (visual or electrotactile) will increase accuracy, while the combination of them will improve it even more. In the 1 st half, the visual (g = 0.90, p < .001) and combined feedback (g = 1.10, p < .001) were substantially improved compared to the no-interpenetration feedback condition with a large effect in both comparisons. Also, the visual (g = 0.52, p = .026)

and combined feedback (g = 0.67, p = .002) were substantially better than the electrotactile condition, with a moderate effect size in both comparisons. In the 2 nd half, the visual (g = 1.10, p < .001), combined (g = 1.69, p < .001), and electrotactile interpenetration feedback (g = 1.10, p < .001), were significantly better compared to the no-interpenetration feedback condition, with a very large effect in every comparison. No further significant differences were detected in both halves. Furthermore, the electrotactile (g = 0.86, p < .001) and combined feedback (g = 0.69, p < .001) were significantly improved in the 2 nd half compared to the 1 st half, with a large and a moderate effect correspondingly. In contrast, the equivalent comparisons for the no-interpenetration feedback and visual interpenetration feedback were not statistically significant. Notably, only the size of change for electrotactile interpenetration feedback was significantly greater than the size of change for the no-interpenetration feedback (g = 0.64, p = .005) and visual interpenetration feedback (g = 0.60, p = .010), with a moderate effect size for both.

Standard Deviation Index Interpenetration -Precision.

The results of the ANOVA suggested statistically significant effects at .05 significance level. Supporting H1, the main effect of the the type of feedback on index oscillations (i.e., precision) yielded an effect of F(1.88, 37.69) = 28.92, p < .001, and of ω 2 = 0.57, 95% CI[0.39, 0.68] postulating significant differences between the diverse types of feedback with a very large effect size. Aligned with H4, the main effect for the half of experiment on the precision produced an F(1, 20) = 9.32, 42 p = .006, and of ω 2 = 0. The post-hoc pairwise comparisons are illustrated in Fig- 51 ure 6. The results appear to support both H1 and H2. In 52 the 1 st half of experiment, the visual (g = 1.06, p < .001) and 53 combined feedback (g = 1.109, p < .001) were founded sub-54 stantially greater than the no-interpenetration feedback condi-55 tion, with a very large effect in both comparisons. Also, the 56 visual (g = 0.79, p < .001) and combined feedback (g = 0.90, 57 p < .001) were found to be substantially better than the electro-58 tactile interpenetration feedback, with a large effect size in both 59 comparisons. In the 2 nd half of experiment, the visual (g = 1.32, 60 p < .001), combined (g = 1.71, p < .001), and electrotactile in-61 terpenetration feedback (g = 1.07, p < .001), were found to be 62 significantly better than the no-interpenetration feedback con-63 dition, with a very large effect in every comparison. No further 64 significant differences were detected in both halves. Further-65 more, only the electrotactile (g = 0.74, p < .001) was found to 66 be substantially improved in the 2 nd half compared to the 1 st 67 half, with a large effect. The equivalent comparisons for the 68 no-interpenetration feedback, visual interpenetration, and com-69 bined interpenetration feedback were not statistically signifi-70 cant. Importantly, the size of change for electrotactile interpe-71 netration feedback from the 1 st to the 2 nd half was significantly 72 larger than the size of change of the no-interpenetration feed-73 back (g = 0.54, p = .027) and visual interpenetration feedback 74 (g = 0.59, p = .012), with a moderate effect size in both com-75 parisons.

Subjective results

24

The descriptive statistics of the post-exposure self-reports are Moreover, the participants reported that the visual interpenetration feedback was useful and coherent, albeit that provided a feeling that is different from touching a real surface. Similarly, it was reported that the electrotactile interpenetration feedback was useful to very useful and coherent, albeit that provided a feeling that is different to very different from touching a real surface. Also, the self-reports suggested that the electrotactile interpenetration feedback provided neither a pleasant nor unpleasant sensation, as well as that it provided a frequent to very frequent perceptual update of pressing down the surface. Finally, the self-reports indicated that the combination of electrotactile and visual interpenetration feedback had a very coherent to completely coherent synchronization, and it was perceived as moderately similar as to touching a real surface.

Discussion

Our findings agree with previous studies, where bimodal feedback increased the accuracy and precision in contact tasks [3]. Also, our results are in accordance with a metaanalysis of user interaction studies, where the bimodal (i.e., visuohaptic) feedback was found to improve performance [START_REF] Burke | Comparing the effects of visual-auditory and visual-tactile feedback 84 on user performance: a meta-analysis[END_REF]. However, a haptic uncanny effect may substantially compromise the benefits of bimodal feedback on performance [START_REF] Berger | The uncanny 78 valley of haptics[END_REF]. In our study, the dynamic visual interpenetration feedback was matched to the varying intensities of electrotactile interpenetration feedback, which aligns with the suggestions to mitigate or evade a haptic uncanny effect [START_REF] Berger | The uncanny 78 valley of haptics[END_REF]. Hence, our results further support the importance of having matched feedback modalities, when implementing bimodal feedback. Furthermore, our quantitative and qualitative outcomes align with the qualitative results of Pamungkas, et al. [51], where participants reported that the electrotactile interpenetration feedback assisted them with performing a VR robotteleoperation task faster and more accurately. However, in our quantitative user study the benefits of providing electrotactile interpenetration feedback became apparent only in the 2 nd half of experiment, suggesting the presence of a learning effect. Also, the intensity values for providing electrotactile interpenetration feedback were substantially increased in the middle calibration, which were used in the 2 nd half of experiment. In conjunction, our findings postulate that the advantages of electrotactile interpenetration feedback may surface, when the user has been familiarized with it, and/or the intensity of feedback is well-adjusted to skin's conductivity changes and/or user's increased tolerance to the electrotactile interpenetration feedback.

However, the intensity values were not correlated with neither accuracy nor precision. Thus, the increased familiarity with the electrotactile interpenetration feedback that was inferred due to the observed learning effect, appears to better explain why the advantageous effects of electrotactile interpenetration feedback on performance were surfaced only during the 2 nd half of experiment.

It should be noted that the learning effect was not generally present. The learning effect was identified only for the bimodal visuotactile feedback regarding accuracy, as well as for the electrotactile interpenetration feedback regarding both accuracy and precision. These findings indicate that the learning effect was important only in conditions where the electrotactile interpenetration feedback was used. Also, the size of the improvement in the accuracy and precision from the 1 st to the 2 nd half of experiment was significantly greater for the electrotactile interpenetration feedback condition compared to the size of improvement for no-interpenetration feedback and visual interpenetration feedback conditions respectively. This finding also postulates that the learning effect was observed due to the novelty of the electrotactile interpenetration feedback, and not due to a practice effect related to the task. Nevertheless, the effects of the familiarity with electrotactile interpenetration feedback and the refined calibration on user's performance should be further scrutinized in prospective studies. interfere with the visualization of the internal organs. In contrast, the suggested electrotactile interpenetration feedback appears to facilitate multiple contact interactions, although this should be further examined. Thus, the presented electrotactile feedback system seems to be the most appropriate and effective choice for improving precision and accuracy of mid-air interactions in immersive VR. These findings can be applied in similar fields such as in tele-operation and for different interactions such as grasping, or finger sliding as the feedback enables precise contact while also providing in real-time rich tactile information.

As future work, it would be interesting to compare the precision and accuracy achieved when using a different type of tactile feedback such as finger pressure or vibrotactile feedback. For the particular case of vibrotactile feedback, based on the outcomes presented in [START_REF] Kourtesis | Action-specific perception & performance on a fitts's law task in virtual 94 reality: The role of haptic feedback[END_REF], vibrotactile feedback does not seem to improve performance as electrotactile does in a Fitts's Law selection task.

Nevertheless, as discussed above, the recurrent calibration, for adjusting the electrotactile feedback's parameters to the users' preferences, appears to play a central role for improv-ing users' performance. Currently, there is not a calibration 59 process that can be performed independently (i.e., by the users 60 themselves) while the users are immersed in the virtual environ-61 ment. In this paper, we therefore propose a calibration system 62 that is embedded in the virtual environment.

Calibration experiment 64

In the literature (see [54]), and as reviewed in Section 2.2, 65 there are a number of works that focused on the improvement 66 of the calibration of electrotactile feedback. However, these 67 methods still require manual adjustment of the intensity values 68 in order to achieve an optimal user experience. For example, a 69 number of electrical stimulators measure the impedance of the 70 skin in order to render a constant sensation, yet, users' opti-71 mal sensation level still requires to be calibrated [54]. Other 72 methods consider previously measured data to create an initial 73 rough calibration by extrapolation, yet, these values might re-74 quire further refinement to achieve optimal calibration values. 75 In overall, these methods follow strict rules, such as staircase 76 method, where each sensation value is played for fixed amount 77 of time, in which the user have a minimal control during the 78 calibration. In any case, the calibration must be validated by 79 the user and that could become a tedious and time consuming 80 procedure.

81

The previous experiment highlighted that calibration is a crit-82 ical part of the rendering of tactile sensations using electrotac-83 tile feedback and multiple calibrations might be needed to ac-84 count for the participant's adaptation to the stimulation. Thus, 85 we decided to explore alternative ways to calibrate the sys-86 tem. In an ideal calibration procedure, the user should be au-87 tonomous while performing the calibration without the need of 88 external support (e.g. experimenter). More importantly, the cal-89 ibration system needs to follow a number of safety rules in or-90 der to not let the user set unpleasant values by mistake. Fur-91 thermore, as the quality of the sensation depends on the contact 92 between the electrode and the skin, the input mechanism used 93 by the user should not interfere with it. For example, traditional 94 input methods (mouse/keyboard/controllers) are designed to be 95 used with the dominant hand which is also the target for render-96 ing tactile sensations. Based on this, mid-air interactions could 97 be of benefit for interacting with a calibration system when the 98 dominant hand is cluttered with the VR and electrotactile equip-99 ment (e.g. stimulator, electrodes, trackers). Moreover the con-100 tact between the electrode and the skin should not be altered by 101 a physical contact with the worn equipment. Finally, the system 102 should provide a fast but accurate calibration procedure, which 103 can be performed recurrently while the user is immersed in the 104 virtual environment.

Calibration in VR using mid-air interaction 106

Based on the lessons learned from our first experiment [START_REF] Vizcay | 101 Electrotactile Feedback For Enhancing Contact Information in Virtual Re-102[END_REF], 107 we proposed an interactive method to calibrate the intensity 108 of the electrical stimulation. In this method, we considered a 109 mid-air interaction technique in which the users could use their 110 virtual hand representation (index finger) to interact with a 3D 111 slider to adjust the intensity of the feedback. The slider has a total length of 1.76 m and consists of 88 slices (2 cm each), allowing exploring the full length from a seated position, and is located in front of the user (see Figure 8). The stimulation is only enabled when the finger of the participant is inside the virtual slider. The range of intensities goes from 0.2 mA to 9.0 mA, making the resolution of the slider match the resolution of the stimulator that we used (increments of 0.1 mA). Furthermore, to avoid sudden/unwanted changes on the value of the slider, the slider only changes by activating consecutive slices, i.e. participants need to drag the last active slice, so that they can not set a high value by mistake. This design avoided users making fast/unwanted motions that could increase the intensity of the stimulation beyond their discomfort threshold. This is an important aspect, as it ensures a safe calibration and subsequent safe electrotactile interaction.

Evaluation

This section describes a user study evaluating the proposed calibration method (3D slider in VR) against a baseline in which participants used a desktop-based method using a traditional physical keyboard.

Calibration using traditional keyboard

In the keyboard method, participants looked at a regular monitor displaying a fixed point of view of the scene with the slider at the center of the screen (see Figure 9). Participants could use the keyboard to interacted with the virtual slider. Pressing the left/right arrows of the numeric keyboard to decrease/increase the intensity (which will also turn the stimulation on), pressing the delete key of the numeric keyboard to stop the stimulation and pressing the insert key of the numeric keyboard to toggle the sensation on/off. The keyboard interaction was mapped to the visual slider, so each key-press event activated the immediate consecutive slice.

To make the slider advance farther, multiple key-presses were needed instead of going all the way up with a single long keypress.

In order to provide consistent feedback for both methods, when the stimulation was off, the slider had a gray color whereas when is on, the slider glowed with a light blue or an 42 orange color based whether the participant was calibrating the 43 sensation or discomfort threshold. For both conditions, the cal-44 ibration of the discomfort threshold was performed from the 45 previous value set as sensation rather than starting from zero.

Participants and apparatus

47

A total of 16 individuals [age: mean(SD) = 27.3(7.3); 48 range = 22 -52 years old; gender: 8 males; 8 females] were 49 recruited through an in-campus advertisement. All 16 parti-50 cipants were familiar with using VR HMDs, 12 had previous 51 experience with tactile devices and 7 had previous experience 52 with electrotactile feedback.

53

The equipment was the same as the one used in previous ex-54 periment. The calibration was performed only for the central 55 pad placed at the center of the finger pad with a fixed pulse 56 width of 150 µs and a frequency of 200 Hz.

Experimental protocol 58

At the beginning of the experiment, participants were in-59 formed about the nature of the experiment and were asked to 60 read and sign the informed consent form. After that, parti-61 cipants answered a pre-questionnaire where they answered 62 some demographic questions followed by questions assessing 63 their experience with VR, haptics and electrotactile equipment. 64 Then, we asked the participants to determine the sensation and 65 discomfort thresholds using both methods. Both shared the 66 same visual feedback which consisted of a 3D slider and a black 67 board for providing written instructions (see Figure 8). The or-68 der of the calibration method was counterbalanced. Moreover, 69 to test for potential learning effects, the calibration procedure 70 was performed twice. For example, participants performed the 71 calibration first with the keyboard method, then with the VR 72 method, and then repeated again. Participants performed the 73 calibration twice for each method. Before performing the cali-74 bration, participants had time to get familiarized with both inter-75 action methods (in the same order as in the experiment). During 76 this familiarization process, no tactile sensation was rendered so 77 they could focus only on the interaction.

78

Once the main task was over, participants answered a SUS-79 like questionnaire evaluating the usability of each interaction 80 method.

Dependent variables and hypotheses

Based on our hypotheses and the experimental task we measured the following metrics within each trial: sensation threshold, discomfort threshold, sensation dynamic range, intensity adjustments and calibration time. The sensation and discomfort thresholds were set directly by the participants using one of the calibration methods. The sensation dynamic range was calculated as the difference between the discomfort and the sensation thresholds. The intensity adjustments considered the amount of times that the intensity was updated. For each condition the intensity updates were discrete, either pressing a key or dragging the slider directly. The calibration time was measured starting at the first time the participant interacted with the system during the trial until the time when they finalised the calibration.

Sensation, discomfort and dynamic range are measured in milliamperes whereas the calibration time is measured in seconds.

At the end of the experiment, participants answered a modified version of the SUS questionnaire (see Table 2) composed of eight paired questions per condition, using a 5-Likert scale:

Strongly Disagree, Disagree, Neither, Agree, Strongly Agree.

The first six questions [Q1-Q6] were taken from the original SUS questionnaire which were applicable for our system comparison and the last two [Q7, Q8] were added with the intention to corroborate objective metrics with participants' perception.

In this respect our hypotheses were:

• [H1] When using the slider in VR as interaction method, the calibration time will decrease. Also, the calibration time will decrease as the experiment advances.

• [H2] The interaction method will not have an effect on the perceived intensity, producing similar sensation and discomfort thresholds under any interaction condition.

• [H3]

The VR slider calibration method will increase the interaction in terms of number of intensity adjustments. Also, the number of adjustments will decrease as the experiment advances.

Results

The homogeneity and normality assumptions were assessed.

The discomfort, dynamic range, and duration of the calibrations violated the normality assumption. The distributions were positively skewed. The values were then transformed using a logarithmic transformation. No further violations were detected after the logarithmic transformation of the data.

A two-way repeated measures ANOVA was performed for each continuous variable. The sphericity assumption was never violated in the ANOVA analyses. The ANOVA analyses were followed by post-hoc pairwise comparisons. Lastly, the participants' self-reports on each calibration system's usability (i.e., modified SUS questionnaire) were examined. Non-parametric pairwise comparisons were performed to scrutinize the reported usability aspects.

Calibration duration

In line with H1, the results of the ANOVA analysis revealed significant main effects for both calibration type and calibration's repetition. However, there was not a significant interaction effect between calibration type and calibration's repetition.

The calibration type had a main effect of (F(1, 14) = 13.89, 56 p = .002) indicating significant differences between the cal-57 ibration types. The calibration type had a large effect size 58 of (ω 2 = 0.11, 95% CI[0, 1]) on the duration of calibration. 59 Comparably, the calibration's repetition had a main effect of 60 (F(1, 14) = 34.61, p < .001) suggesting a substantial difference 61 between the 1 st and the 2 nd repetition. The produced effect size 62 was of (ω 2 = 0.14, 95% CI[0, 1]) indicating a large effect of the 63 repetition on the calibration's duration.

64

The post-hoc pairwise comparison are illustrated in Fig- 65 ure 10. The results strongly support both aspects of H1. The 66 VR slider calibration method was substantially faster than the 67 keyboard method, and the difference between them was of a 68 large effect size of (g = 0.61, p = .002). Similarly, the duration 69 of the 2 nd repetition, regardless of the calibration type, was sig-70 nificantly shorter than the 1 st repetition, and the effect size was 71 equally large (g = 0.78, p = .001). 72

Perceived intensity and thresholds

73

The ANOVA analyses for the sensation and discomfort 74 thresholds, respectively, did not indicate any significant main 75 effect of the calibration type on the sensation and discomfort 76 thresholds. These results align with the H2. However, a sig-77 nificant main effect (F(1, 15) = 15.59, p = .002) on sensation's 78 threshold was identified due to the calibration's repetition. Nev-79 ertheless, the effect size of the calibration's repetition on the 80 sensation threshold (ω 2 = -0.001, 95% CI[0, 1]) was extremely 81 small. Similarly, the non-significant effect size (ω 2 = -0.001, 82 95% CI[0, 1]) of calibration's repetition on discomfort thresh-83 old was equally small. Also, there was not any significant inter-84 action effect for both thresholds. Finally, none significant main 85 or interaction effect of calibration type and/or repetition on the 86 dynamic range of electrotactile feedback was detected.

87

The post-hoc comparisons between 1 st and 2 nd repetition are 88 displayed at Figure 11. The sensation threshold in the 1 st rep-89 etition was substantially smaller compared to the 2 nd one, and 90 the effect size was large (g = -0.86, p < .001). Also, a small 91 size effect (g = -0.20, p = .270) was seen in discomfort thresh-92 old, albeit the difference was not significant. Finally, as seen in 93 of discomfort threshold was wider, and the mean values much higher.

Thresholds adjustments

Regarding the number of adjustments of each threshold during the calibration process, the ANOVA analyses detected significant main effects of the calibration type on the adjustments of both thresholds. These main effects are in support of H3.

Specifically, the calibration type had a significant main effect (F(1, 15) = 14.29, p = .002) on the number of adjustments of sensation's threshold. The calibration type had a moderate to large effect size of (ω 2 = 0.08, 95% CI[0, 1]) on the adjustments of sensation's threshold. Comparably, calibration type had also a significant main effect (F(1, 15) = 7.84, p = .014) on the number of adjustments of discomfort's threshold. However, in this case, the effect size was small to moderate (ω 2 = 0.02, 95% CI[0, 1]).

The post-hoc comparisons for the number of adjustments of sensation and discomfort threshold respectively are displayed at Figure 12. Compared to the keyboard calibration system, the users explored substantially more intensity values for identifying their sensation threshold while using the VR slider calibration system, and the effect size of this difference was of medium size (g = -0.48, p = .001). Likewise, the users explored significantly more intensity values for identifying their discomfort threshold while using the VR slider calibration system. Equally, 25 the effect size of this difference was of medium size (g = -0.47, 26 p = .010). Finally, regardless the calibration type, compared to 27 the 1 st repetition, the users explored less values for identify-28 ing their discomfort threshold in the 2 nd repetition, and the ef-29 fect size of this difference was moderate (g = -0.42, p = .020). [START_REF] Akhtar | Controlling sensation intensity for electrotactile stimulation in human-machine interfaces[END_REF] These results are in line with the H3. 2. The VR interaction got a score of 87.5 ± 10.94 while 34 the score for the keyboard was of 82.62 ± 14.66 (max achiev-35 able score is 100). We analyzed the difference between the 36 scores using a two-sample Wilcoxon-test and this yielded no 37 significant difference. Then we explored potential differences 38 within questions using again a two-sample Wilcoxon-test. No 39 significant differences were detected, except for Q7 regarding 40 the speed of performing the calibration process. Based on 41 these self-reports, the VR slider was rated as substantially faster 42 (p = .005) than the keyboard-based calibration. This result fur-43 ther supports H1. ibration process agree with H1, i.e. participants performed the calibration significantly faster when using the VR interaction than when using the keyboard and this was actually perceived by them and reflected on their self-reports. These results were expected because we enforced multiple key-presses rather than a press and hold keyboard interaction for increasing the intensity. This imposition was added in order to provide a safe calibration procedure and this has also its counter-part in the VR condition where intensity increments need to be performed by activating slice by slice. Moreover, we found a reduction in the calibration time during the second repetition which turned out to be independent of the calibration method, i.e. participants performed the calibration faster during the second repetition (learning effect) but keeping the relative speed between the two calibration methods. This learning effect was expected for two reasons. Firstly, they knew by then how to perform the tasks more efficiently. Secondly, they had already figured out what were their sensation and discomfort thresholds from the previous iteration.

Regarding H2, the results confirmed that the calibration method would not have an impact on the calibration thresholds.

Participants managed to set the same values regardless of the interaction. We recall that both methods have the same resolution of 0.1 mA and it seems that the physical size chosen for the individual slices (2 cm), proposed no problem for the participants when it comes to precisely select them. The significant difference of sensation threshold between calibration's repetition agreed with the finding of our previous experiment, where participants required a higher intensity value in the second calibration to perceive the electrical stimulation. We suggest as one of the reasons the familiarization with the stimuli but this needs to be further examined. The fact that the difference was significant only for the sensation threshold and not for the discomfort could be due to the expected variance of both thresholds.

In general, both thresholds increased during the second repetition but these increments were compared to the each variances.

Participants answered less accurately whether a particular intensity value was uncomfortable or not; not so much being the case for the binary question whether they felt something or not.

Finally, our results surfaced an interesting difference between the two calibration methods regarding the number of adjustments. In line with H3, the results showed that the participants, while using the VR method, explored more intensity values (i.e., number of adjustments) in order to select their sensation and discomfort thresholds. Nonetheless, the VR calibration method was also performed faster by the participants.

This leads us to the conclusion that participants were exposed to a higher number of values in a shorter period of time which benefits calibration's efficiency. The results also confirmed that there is a decrease of number of adjustments during the second repetition, which we associate with a learning effect for similar reasons to H1. The participants had thus improved in performing the calibration, while they had previously identified the threshold that should strive to reach.

We should recall that in this experiment, all 16 participants had prior experience with VR technology, which might have had an effect on their performance as they were familiarized with the technology.

As future work, we should explore alternative mid-air inter-59 actions such as pressing virtual buttons for adjusting the inten-60 sity of the feedback and evaluate if the speed of the calibration 61 is comparable to the speed of using the virtual 3D slider. Haptic devices provide sensations and information crucial to 64 both presence and performance in VR [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives[END_REF]54,[START_REF] Maisto | Evaluation of wearable haptic systems for the fin-107 gers in augmented reality applications[END_REF]. However, the 65 wearability of haptic devices is a key component for their effec-66 tive implementation in VR [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: Taxonomy, review, and perspectives[END_REF][START_REF] Maisto | Evaluation of wearable haptic systems for the fin-107 gers in augmented reality applications[END_REF]. Electrotactile devices appear 67 promising for offering rich tactile sensations and an adequate 68 wearability [54]. In the 1 st experiment, our findings agree with 69 previous studies (e.g., [START_REF] Hummel | A lightweight electrotactile feedback device for grasp improvement in immersive virtual environments[END_REF][START_REF] Pamungkas | Electro-tactile feedback system to enhance virtual reality experience[END_REF]), where the electrotactile feedback 70 brought performance related benefits. However, as discussed 71 above, the recurrent calibration of the intensity is a key issue 72 for implementing electrotactile feedback in VR. In the 2 nd ex-73 periment, we delivered a calibration system in VR, which was 74 efficient, ergonomic, and fast. These outcomes further pave the 75 way for the implementation of electrotactile feedback in VR.

76

Specifically, in the 1 st experiment, we saw that the perfor-77 mance benefits surfaced in the 2 nd half, after the 2 nd calibra-78 tion. This was attributed to the familiarization of the parti-79 cipants to the electrotactile feedback and/or the corrective effect 80 of the 2 nd calibration to provide the users with more appropriate 81 electrotactile feedback's intensity. While in the 1 st experiment, 82 both sensation and discomfort thresholds were substantially in-83 creased, in the 2 nd experiment only the sensation threshold was 84 increased. This can be attributed to the prolonged exposure of 85 participants to the electrotactile feedback between the first two 86 calibrations of the 1 st experiment. In contrast, the participants 87 in the 2 nd experiment, went only through a calibration process 88 by using the other calibration method between the two calibra-89 tion's repetitions (e.g., 1 st VR slider -1 st Keyboard -2 nd VR 90 slider). Thus, the continuous exposure may have influenced the 91 increased values between the first two calibrations of the 1 st ex-92 periment.

93

However, in the 2 nd experiment, both thresholds were indeed 94 increased, albeit that only sensation threshold's increase was 95 significant. Nevertheless, the effect size of the calibration's 96 repetition on the sensation threshold was substantially small. 97 Hence, indeed, both thresholds in the 2 nd experiment were not 98 affected by the calibration's repetition, in contrast with the 1 st 99 experiment, where the effect size of calibration's iteration on the 100 thresholds was large. However, when comparing qualitatively 101 the results of the 1 st and 2 nd experiment, we observed certain 102 similarities. When considering the 3 rd calibration in the 1 st ex-103 periment and the mean values of the 2 nd repetition in the 2 nd 104 experiment, we observed comparable results. Sensation thresh-105 olds for both cases had mean values of 2.2 mA while the mean 106 discomfort thresholds where higher (4.2 mA for the first, and 107 4.9 mA for the second).

108

Considering that length of both experiments and the time 109 participants were exposed to electrotactile feedback, these re-110 sults seems to suggest that once the participants were used to 111 the calibration procedure, they were able to consistently cali-112 brate the system. For example, for the first calibration of the 1 st 113 experiment, participants were not always able to obtain optimal 114 calibration parameters, while this was the case even for the 1 st 1 repetition of the 2 nd experiment. In the second user study, we explored how the calibration 26 procedure for electrotactile feedback could be improved and in-27 tegrated directly within the virtual environment. The results

28

showed that users were able to perform faster calibrations with 29 a comparable accuracy using the VR calibration method.

30

Taken together, the reported results showed the potential of

1

  Immersive virtual reality (VR) is becoming a common plat-2 form for education and training, where precision and accuracy 3 during manipulation of virtual objects are key aspects [1, 2].

4

 4

  Wearable tactile feedback in VR 66

  87

Fig. 1 .

 1 Fig. 1. electrotactile interpenetration feedback modulation via pulse width (left) and frequency (right).

Fig. 2 .

 2 Fig. 2. Experimental apparatus. The electrical stimulator is attached to the forearm and the electrode is placed in contact with the finger pad. The two insets represent detailed views of the electrode. The user's hand is tracked by a HTC Vive Tracker.

  2

6 edge of 15

 615 cm, 3 cm represents the maximum interpenetration 7 achieved in most interactions. For this reason, we normalized

8

  the interpenetration d by this value, i.e., a normalized interpe-9 netration d of 1 means a true interpenetration into the virtual 10 object of 3 cm.

11

 11

12 Vive

 12 Tracker attached to the back of the hand. The physics-13 based hand avatar (physics-based as its interactions are handled 14 by the physics engine) collides with the other objects in the virtual environment while trying to follow the position indicated

A

  total of 21 individuals [age: mean(S D) = 25.67(2.74); range = 23 -33 years old; gender: 14 males, 6 females, and 1 non-binary] were recruited through an in-campus advertisement and a call on institutional email lists. 21 participants were familiar with using VR head-mounted displays (VR-HMDs), 10 participants had a previous experience with receiving tactile feedback in VR (predominantly vibrotactile), and only 2 had experienced electrotactile feedback in the past. An HTC Vive Pro HMD was used for immersion. The PC had an NVIDIA RTX 2070. An HTC Vive Tracker attached to the back of the palm (see Figure 2) and 2 Lighthouse base stations were used for tracking. See Figure 2 for the placement of electrotactile stimulator, which weighted 300 g. A Velcro strap was used to hold the electrode. Its tightness was adjusted to achieve a comfortable yet firm placement of the electrode.

Fig. 3 .

 3 Fig. 3. Depiction of the subjective view of the user during the experiment. The user could touch the virtual cube placed on the top of the table on the left. The semitransparent cube on the right side defines the resting area. The blackboard in front of the user provided general information during the experiment.

74 4 .

 4 1.5. Experimental protocol 75

Fig. 4 .

 4 Fig. 4. Visual shading conditions (left & right) and visual interpenetration feedback (right).

4 4

 4 .1.6. Dependent variables and hypotheses 5

7

  rics: average (avg d), standard deviation (std d) and maximum 8 (max d) interpenetration during the three seconds in which the 9 user was asked to remain in contact with the virtual cube sur-10 face. As we did not track the user's finger but the back of the 11 hand, the interpenetration was computed by measuring the dis-12 tance between the estimated position of the real fingertip in the 13 virtual environment and the position of the avatar fingertip con-14 strained on the surface of the cube. The interpenetration mea-15 sures provide information regarding the awareness of the real 16 interpenetration (accuracy) and their ability to keep a constant

17

 17

19 •

 19 [H1] The addition of interpenetration feedback (either vi-20 sual or electrotactile) will increase the precision and the 21 accuracy of the task. 22 • [H2] The combination of the visual and electrotactile inter-23 penetration feedback will result on the best precision and 24 accuracy.

25 •

 25 [H3] Precision and accuracy will be higher for the fully 26 shaded condition.

27 •

 27 [H4] Precision and accuracy will improve along the exper-28 iment due to learning effects.

29

 29

33 •

 33 [H5] Sensation and discomfort thresholds will monotoni-34 cally increase during the experiment.35Finally, the participants' subjective report were collected 36 through a post-exposure questionnaire. The questionnaire is in-37 cluded as supplementary material. The questionnaire encom-38 passed questions pertaining to the perceived usefulness, coher-39 ence, and resemblance with a real interaction of the electro-40 tactile interpenetration feedback, as well as some comparison 41

Fig. 5 .

 5 Fig. 5. Average Interpenetration in cm. Comparisons per Type of Feedback and Half of the Experiment. IF = Interpenetration Feedback.

Fig. 6 .

 6 Fig. 6. Index Oscillation in cm. Comparisons per Type of Feedback and Half of the Experiment. IF = Interpenetration Feedback.

76 4 .Fig. 7 . 6 cally greater than the equivalent intensities of initial calibration 7 (

 4767 Fig. 7. Intensity values in mA. Comparisons for each calibration.

23

 23

Finally, the results

  postulate the effectiveness of electrotactile and/or visual interpenetration feedback. However, the implemented visual interpenetration feedback requires constant visual focus, it could occlude other visual information, and it renders visual artifacts in a fully interactive virtual environment, which may reduce substantially the contact precision and accuracy. As an example, Qian et al. [52] proposed a VR training laparoscopic surgery simulator, where rendering of visual artifacts would decrease the reality of the simulator and would

  63

  105

Fig. 8 .

 8 Fig.8. Interface of the calibration experiment with participant adjusting the intensity using its index finger to drag a 3D slider in VR.

Fig. 9 .

 9 Fig. 9. Desktop-based calibration process using a keyboard. Participant needs to temporary lift the HMD to look at the monitor.

46

 46

  57

Figure 11 ,Fig. 10 .

 1110 Fig. 10. Duration of Calibration Process in secs. Comparisons between Repetitions (Left) and Calibration Types (Right).

Fig. 11 .

 11 Fig. 11. Sensation (Left) and Discomfort (Right) Thresholds. Comparisons between Repetitions.

31 5 .

 5 3.4. SUS questionnaire 32The descriptive statistics of the questionnaire are shown in 33 Table

45 Fig. 12 .

 4512 Fig. 12. Number of Adjustments of Sensation (Left) and Discomfort (Right) Thresholds. Comparisons between Repetitions (Top) and Calibration Types (Bottom).

3

  In this paper, we proposed an electrotactile rendering al-4 gorithm to enhance contact information in a virtual environ-5 ment based on the modulation of the pulse width and frequency 6 of the electrical signal and explored alternative ways to im-7 prove the calibration procedure of the electrotactile feedback 8 which was found key for the optimal perception of the tac-9 tile sensations. In order to explore the benefits and limitations 10 of the interpenetration feedback method, we first conducted a 11 user study evaluating the performance in touching accurately 12 and precisely virtual rigid objects with various interpenetration 13 feedback. The results showed that participants achieved signif-14 icantly better performance in terms of accuracy and precision 15 when visual and/or electrotactile interpenetration feedback was 16 provided. More importantly, there were no significant differ-17 ences between visual and electrotactile interpenetration feed-18 back when the proper intensity was used and once the user was 19 familiarized with the sensation of electrotactile feedback. Con-20 sidering that visual discrimination is dominant in such scenarios 21 and a visual interpenetration feedback renders visual artifacts, 22 the findings indicate a promising future for electrotactile-based 23 systems for improving contact precision and accuracy in inter-24 active VR systems.

25

 25

31 wearable electrotactile devices for eliciting tactile sensations in 32 a

 3132 virtual reality context. Nevertheless there are still a number 33 of future works that are still required. For example, there is 34 the need to explore other alternatives for the modulation and 35 location of the electrotactile feedback or consider other tactile 36 actuators. In addition, in our experiment, the user could not 37 interact freely with his/her fingers as we asked them to keep a 38 fixed hand pose, which could potentially modulate the tactile 39 perception. More complex interactions such as grasping or in-40 teractions with dynamic objects (e.g. pushing a virtual object) 41 need to be explored. Finally, the calibration of systems with a 42 higher number of pads still remains an open research question.

16 by the tracker. As described at the beginning of section 3, this avatar resolves all virtual collisions and avoids any undesired 18 virtual interpenetration. Whenever it comes into contact with a 19 virtual object, its motion is constrained to stay on the object's 20 surface, regardless of how much the user's hand moves into the

	21
	22	object. As detailed above, this discrepancy between the user's
	23	real hand and its avatar drives our electrotactile interpenetration
	24	feedback.
	25	4. Contact experiment
	26	4.1. Evaluation
	27	This section describes a user study evaluating the proposed
	28	electrotactile interpenetration feedback system. Our main ob-
	29	jective was to assess the potential advantages and disadvantages
	30	of using electrotactile interpenetration feedback while perform-
	31	ing a task requiring a high level of accuracy and precision. In
	32	particular, we focused on a task in which the user is asked to
	33	contact a virtual surface with his/her index finger while mini-
	34	mizing the amount of interpenetration between the virtual sur-
	35	face and the real index finger. In such a task, when the virtual
	36	hand avatar cannot interpenetrate virtual surfaces, it is difficult

  27, 95% CI[-0.01, 0.54] suggesting 43 a significant difference between the two halves of the exper-44 iment with a large effect. The interaction among the diverse 45 pairs derived from the halves of the experiment and the types of 46 feedback yielded an interaction effect of F(2.38, 47.66) = 4.30, 47

p = .014, and of ω 2 = 0.13, 95% CI[-0.03, 0.29] postulating 48 significant difference between the diverse pairs with a large ef-49 fect size.

Table 1 .

 1 However, in the same question, there was no significant difference between visual and electrotactile interpenetration feedback suggesting a balanced preference. Self-reports on Electrotactile Interpenetration Feedback.

	25
	26	displayed in Table 1, which support H6 (electrotactile feedback
	27	will be reported useful and coherent). In support of H7, the
	28	Wilcoxon signed rank test yielded no significant differences in
	29	the comparisons between the visual and electrotactile interpene-
	30	tration feedback pertaining to usefulness (i.e., how useful was
		the feedback for the task's completion), coherence (i.e., how

31

much coherent was the feedback with touching the surface), 32 and resemblance (i.e., how much the feedback resembles touch-33 ing a real surface). The Wilcoxon rank sum test, for the ques-34 tion pertaining to the combined feedback condition, indicated a 35 significant difference p = .024 between electrotactile and com-36 bined feedback, postulating that the participants reported that 37 they relied significantly more on the electrotactile interpenetra-38 tion feedback rather than both interpenetration feedbacks (i.e., visual and electrotactile).

Table 2 .

 2 Usability questionnaire administered. The last columns present the obtained results for each condition (Median [IQ1-IQ3]).

	ID	Question

Preprint Submitted for review / Computers & Graphics (2023)

Acknowledgments 44 This work was supported by the European Union's Horizon

research and innovation program under grant agreement 46

No. 856718 (TACTILITY).