# Perceptual Dimensions of Physical Properties of Handheld Objects Induced by
Impedance Changes

Takeru Hashimoto, Shigeo Yoshida, Takuji Narumi

###### Abstract

Haptics in virtual reality is the emerging dimension after audiovisual
experiences. Researchers designed several handheld VR controllers to simulate
haptic experiences in virtual reality environments. Some of these devices,
equipped to deliver active force, can dynamically alter the timing and
intensity of force feedback, potentially offering a wide array of haptic
sensations. Past research primarily used a single index to evaluate how users
perceive physical property parameters, potentially limiting the assessment to
the designer’s intended scope and neglecting other potential perceptual
experiences.

Therefore, this study evaluates not how much but how humans feel a physical
property when stimuli are changed. We conducted interviews to investigate how
people feel when a haptic device changes motion impedance. We used thematic
analysis to abstract the results of the interviews and gain an understanding
of how humans attribute force feedback to a phenomenon. We also generated a
vocabulary from the themes obtained from the interviews and asked users to
evaluate force feedback using the semantic difference method. A factor
analysis was used to investigate how changing the basic elements of motion,
such as inertia, viscosity, and stiffness of the motion system, affects haptic
perception. As a result, we obtained four critical factors: size, viscosity,
weight, and flexibility factor, and clarified the correspondence between these
factors and the change of impedance.

###### Index Terms:

Perception, Haptic Feedback, Handheld Object, Dynamic Touch

##  I Introduction

Haptics is increasingly recognized as a crucial dimension in the realm of
virtual reality, alongside the well-established audiovisual aspects. In recent
years, researchers have been exploring various handheld VR controllers to
express haptic sensations to users within virtual environments. Among these,
active haptic interfaces stand out as promising methods capable of dynamically
shaping the user’s haptic experiences by actively modulating the force
feedback they provide.

In active haptic interfaces, the key variable is not a static physical
property but a time-varying relationship between the force input by the user
and the corresponding reaction force from the device. However, it’s essential
to recognize that the fidelity of forces produced by such devices, while
accurate, may not replicate the richness of information present in the real
world. This discrepancy arises due to the mechanical nature of force
generation and the intricate relationship between physical phenomena and human
perception.

Assessing human perception in the context of haptic devices often relies on
psychophysical experiments that allow researchers to gauge how well a haptic
device can convey specific physical properties or sensations. However, the
limitation of such experiments lies in their inherently one-dimensional
nature, determined by the experimenter’s predefined criteria. For instance,
asking participants to evaluate force feedback as an object’s “weight”
confines the assessment to a single aspect of haptic perception, potentially
neglecting other sensations like “stickiness” or “stiffness.” This limitation
reflects an inherent top-down imposition of “reality” onto the user’s sensory
experience.

Therefore, we need to investigate the possible correspondences between the
physical and perceptual phenomena that can be represented by the device. This
investigation will not only allow us to explore the representational
possibilities of the various haptic devices that have been created, but also
to determine how independently each representation can be controlled.
Regarding cutaneous sensation, some studies have investigated the
correspondence between the physical properties of surfaces and human
perception. They have extracted independent and significant factors related to
tactile perception and construct perceptual dimensions of tactile surface
texture [1, 2]. The correspondence in proprioceptive sensation should also be
investigated for the future design of haptic devices.

In particular, our study focuses on the relationship between the impedance
control parameters of a force feedback device and the perception of physical
properties associated with a handheld object. By using a single haptic device
using gyro moment, we aim to demonstrate how active force feedback affects
human haptic perception and to clarify the relationship between the physical
and perceptual domains.

By conducting this study, we hope to contribute to the broader field of haptic
technology by gaining insights into the intricacies of human haptic perception
and advancing the design and utilization of haptic interfaces for a more
immersive and sensory-rich virtual reality experience.

##  II Related Work

This article draws inspiration from various studies in haptic feedback for
representing object properties, evaluating human perception of material, and
ecological psychology.

###  II-A Dynamic Touch

In ecological psychology, research has extensively explored how humans
perceive the properties of handheld objects through haptic perception. These
studies have demonstrated the critical role of haptic sensation in perceiving
various properties of handheld objects, including length, width [3], and
three-dimensional shape [4]. As the term “dynamic touch ” [5] suggests, this
wealth of information is acquired through dynamic manipulation of the object
rather than static handling. Humans infer a plausible object shape from the
forces applied to tendons and muscles in the arm and the skin deformation on
the palm, achieved through various interactions with the object.

###  II-B Haptic Exploration of Objects

Haptic exploration is a pattern of behavior that individuals intentionally
engage in to characterize surfaces and objects, a spontaneous pattern that
optimizes the uptake of information. Lederman et al. described a series of
specialized search patterns called exploratory procedures (EPs) [6]. Among
EPs, unsupported holding is particularly effective in acquiring information on
the properties of the handheld object. While their paper discussed only weight
as an associated property, later experiments showed that humans could perceive
various object properties by unsupported holding, in their words, dynamic
touch [7]. Turvey et al. focused on information obtained from grasping and
swinging. The properties of an object obtained by swinging include length,
weight, width, shape of the object tip, and direction of the hand relative to
an object. This information is derived from the sensitivity of body tissues to
the values of rotational force (torque) and rotational dynamics.

###  II-C Relationship between Physical Properties and Perception

Many studies have explored the connection between materials and perceptual
information using cutaneous touch [8, 2, 1]. For instance, in a study using a
multi-dimensional scaling method on 124 material samples, researchers
identified that humans rely on four primary factors to assess material quality
[2]. The extent to which each physical quantity affects the sensation scale
has also been investigated through multivariate analysis [1]. In contrast,
limited research has been conducted to evaluate the relationship between the
properties of handheld objects and the perceptual information acquired through
dynamic touch. As mentioned in the introduction, one-dimensional measurements
have shown that the moment of inertia and rotational dynamics correspond to
the perception of length and width [3, 4, 9]. However, they do not guarantee
that other factors are unaffected.

In the context of dynamic touch, it is crucial to examine the connection
between physical properties and perceptual information. This correspondence
can be used as an indicator to determine which physical properties should be
manipulated to achieve the desired perceived information. In addition, only by
understanding the correspondence between physical properties and perceptions
will it be possible to conduct psychophysical experiments that will yield as
much information as possible.

###  II-D Passive Haptic Interfaces

To represent various physical properties of a handheld object, researchers
have developed a variety of haptic interfaces. In this section, we will focus
on the category known as “passive haptics.” This method represents the
physical properties of a handheld object by changing the physical properties
of the interface itself. There is research on haptic proxies, which create
virtual objects by combining small artifacts or adjusting the weight position
[10, 11, 12, 13]. However, these require reassembling the proxies each time
the virtual object changes. On the other hand, the field also explores dynamic
passive haptic interfaces. These devices incorporate multiple actuators within
a single unit to modify the center of gravity [14, 15, 16], inertia [15, 16],
shape [17], drag [18, 19], stiffness [20, 21, 22], and other physical
properties of the interface itself. Unlike haptic proxies, these devices do
not require reassembly. However, these devices are often specialized for
rendering a specific physical property, and the number of actuators increases
when we want to change multiple properties simultaneously.

###  II-E Ungrounded Active Haptic Interfaces

This study focuses on active haptic interfaces, devices that employ actuators
to generate force output directly. Active haptic interfaces are categorized
based on where the reactive force to the generated force is received:
environment-grounded, body-grounded, and ungrounded. We focus on the
ungrounded category, which is most closely related to our research. Ungrounded
haptic interfaces vary in the methods they employ to achieve force feedback.
Some devices utilize the force of propeller rotation to push air [23, 24, 25]
or the reaction force of compressed air release [26, 27]. However, these
methods often suffer from disadvantages such as force output delay and
imprecise force output. On the other hand, devices that utilize the gyro
effect to output force have also been studied [28, 29, 30, 31, 32, 33]. Those
methods have a slight delay and are characterized by rotational force output
rather than translational force.

Instead of generating actual force, researchers have found that stimulating
muscles with electrical stimulation can be used to generate force feedback
[34, 35]. While EMS devices are small and lightweight, they are challenging to
control force precisely. Researchers have demonstrated the use of rapidly
moving weights to simulate force output [36] or the use of asynchronous
periodic oscillation to create the sense of pulling or pushing due to the
nonlinear nature of our haptic perception [37].

Consequently, a wide array of haptic devices has been developed, each with
advantages and disadvantages. While this paper employs a haptic device
utilizing gyro-moments, the impedance control method employed here can be
adapted to haptic devices using alternative methods. Thus, the insights into
the haptic dimension gained in this study have broader applicability across
various systems.

##  III Implementation of A Haptic Device

We aim to consider the design requirements for a device necessary to
investigate the dimensions of property perception of the handheld object. The
design requirements are as follows:

  1. 1.

Having a mechanism capable of ungrounded force output.

  2. 2.

Capable of low-latency force feedback and impedance control synchronized with
human movements.

The necessity of ungrounded characteristics, as stated in 1), is crucial. In
scenarios involving shaking or manipulating an object, the ability of a force
feedback device to output force without grounding is highly significant. In
contrast to traditionally grounded manipulators, ungrounded devices possess
higher back-drivability, allowing free movement without restricting the
workspace. Grounded manipulators tend to have lower back-drivability,
necessitating expensive torque sensors for unrestricted human movement. Hence,
ungrounded is immensely beneficial in the property perception of a wielded
object. The rationale for the essentiality of low latency, as mentioned in 2),
is expounded. The impedance control utilized in this study demands immediate
force feedback based on the angular acceleration and velocity of the device
resulting from human body movements. In a control system with significant
delays in force output, users would find it challenging to infer the
relationship between their movements and the force feedback. Therefore, low-
latency characteristics play a vital role in unraveling the dimensions of
property perception of a wielded object.

To meet the aforementioned requirements, We employ gyroscopic moment as the
force feedback method. As discussed in section II, gyroscopic moment
facilitates ungrounded and low-latency force output. The rotational force
output generated by this device aligns well with human perceptual
characteristics, as humans perceive properties of a wielded object by inducing
rotational movements.

We built a wearable haptic device that consists of mechanisms to output torque
by tilting the spinning flywheel called control moment gyroscopes (CMG) based
on a previous study [33]. Figure 1 shows mechanism models and specifications
of the device. Weight is an important form factor in wearable devices. After
repeated prototyping, the final weight was set to $350\text{\,}\mathrm{g}$.

Figure 1: The device consists of two CMGs attached to a base component, and it
can be worn on the body using a pair of intersecting Velcro tapes.

###  III-A Hardware Implementation

####  III-A1 Flywheel

The flywheel is fabricated from stainless steel to ensure high density, and it
possesses a diameter of $40\text{\,}\mathrm{m}\mathrm{m}$, a mass of
$30\text{\,}\mathrm{g}$, and a moment of inertia around the rotational axis of
$1.27\text{\times}{10}^{-5}\text{\,}\mathrm{k}\mathrm{g}\mathrm{m}^{2}$. A
brushless DC motor is employed to spin the flywheel, which consistently
rotates around $8000\text{\,}\mathrm{r}\mathrm{p}\mathrm{m}$.

####  III-A2 Gimbal Mechanism

We utilized a Pololu 63:1 geared DC motor and its encoder to drive the
rotation of the gimbal mechanism. A slip ring was installed on the motor’s
opposite side to prevent cable entanglement.

####  III-A3 Structure

The flywheel and gimbal bases are constructed from aluminum for strength and
lightness, while the part worn on the hand is 3D-printed using PLA. The device
can be securely attached to a user’s hand by two intersecting Velcro tapes.

####  III-A4 IMU

The device is equipped with an Inertial Measurement Unit (IMU) to monitor
angular velocity and orientation, and angular acceleration is calculated by
differentiating the measured angular velocity from the IMU.

###  III-B Torque Calculation

The torque output $\tau$ in CMG systems is determined by the angle $\phi$ and
angular velocity $\dot{\phi}$ of the gimbals. Our device uses a scissored
paired CMG configuration, where two CMGs are positioned in parallel, with each
gimbal rotating in opposite phases. That is, the angle of each gimbal is
represented as $(\phi_{1},\phi_{2})=(\phi,-\phi)$, and the torque output is
$\tau=(0,0,-2\sin\phi)^{T}\dot{\phi}$. The velocity of the gimbal $\dot{\phi}$
to obtain the desired torque $\tau$ is calculated from the inverse problem of
this equation.

The concept of impedance control is to represent an object’s static properties
as force information. This concept was proposed so that multi-axis robot arms
can output an appropriate force when they come into contact with humans [38].
Prior studies have considered inertia and damping coefficients as impedance
control variables when they represent the properties of handheld objects [32].
However, there are several examples of varying stiffness in prior cases [20,
21, 22]. In extending impedance control to elastic terms, the restoring force
is expressed for displacement from the initial posture of an object. In the
case of rigid objects, movement is completely synchronized between the
object’s tip and base. However, when the atomic bonds are weak, resulting in
low rigidity, the movement becomes elastic. In other words, restoring force
acts on the displacement from the initial bending state.

The model of two masses adopted in the Elastick [20] represents the
restorative force. Specifically, we define orientations for the two masses,
base and tip, and implement the restorative force generated by the difference
in orientations. This allows us to capture the time lag between the motion at
the base and the tip. The algorithm for calculating the torque $T_{e}$ due to
the restorative force is presented in Algorithm 1. In this algorithm, $k_{r}$
represents the constant of the restorative force applied to the rotational
displacement, while $c_{r}$ is the damping coefficient applied to the
difference in rotational velocity. $I$ represents the overall moment of
inertia. Additionally, $\theta_{1}$ and $\theta_{2}$ denote the orientations
of each mass.

Figure 2: Bending restorative force model. Algorithm 1 Simulation of torque
from elastic object.

${\theta_{1,2},\dot{\theta}_{1,2},\ddot{\theta}_{1,2}}=0\in\mathbf{R}^{3\times
1}$

$k_{r},c_{r},I=\mathbf{const}.$

while simulation running do

#STEP 1: updating the state of the grip

${\ddot{\theta_{1}}}[t]=\ddot{\theta}_{imu}$

${\dot{\theta}_{1}}[t]+={\ddot{\theta_{1}}}[t]\Delta
t~{}~{}~{}{\theta_{1}}[t]+={\dot{\theta}_{1}}[t]\Delta t$

#STEP 2: calculating bending of the virtual rod

$\Delta\theta=\theta_{2}-\theta_{1}~{}~{}~{}\Delta\dot{\theta}=\dot{\theta}_{2}-\dot{\theta}_{1}$

#STEP 3: calculating bending torque

$T_{e}=-k_{r}\Delta\theta-c_{r}\Delta\dot{\theta}$

#STEP 4: updating the state of the tip object

${\ddot{\theta_{2}}}[t]=I^{-1}T_{e}$

${\dot{\theta}_{2}}[t]+={\ddot{\theta_{2}}}[t]\Delta
t~{}~{}~{}{\theta_{2}}[t]+={\dot{\theta}_{2}}[t]\Delta t$

end while

Based on the above, the impedance control of the handheld object in this paper
can be expressed by the equation 1 and 2. Here, $\Delta I$ represents the
difference in inertia, $\Delta D$ represents the difference in damping
coefficient, and $\omega$ is the angular velocity of the device. It should be
noted that the inherited damping coefficient $D$ and restorative force $k_{r}$
in the motion are assumed to be very close to zero.

$I\dot{\omega}=\tau_{h}+\tau_{gen}$ (1) $\tau_{gen}=-\Delta
I\dot{\omega}-\Delta D\omega-T_{e}(k_{r},c_{r})$ (2)

In summary, while previous studies have primarily focused on inertia and
damping coefficients, this study explores the incorporation of elastic forces
into impedance control, providing a more comprehensive framework for
understanding object dynamics.

##  IV Measurement of Generated Torque

We conducted the torque measurement to verify whether the desired torque
calculated by Equation (2) could be output through the gimbal drive, based on
the previous study [32].

###  IV-A Measurement Setup

Because the proposed system outputs torque in response to human motion, we
measured the torque generated when the device was swung by a human. Figure 3
shows the device attached to the body with the torque sensor. A collaborator
performed the swing movement in the direction of wrist flexion and extension,
x-axis in Figure 3. The variables for impedance under each condition were set
as shown in Table I. Regarding the exclusion of the “elasticity decrease”
condition, the low elasticity condition ensures that the object’s tip remains
in sync with the base’s movement, eliminating noticeable lag. Thus, the
effects of an “elasticity decrease” are inherently accounted for within the
“increased inertia” condition. Consequently, considering “elasticity decrease”
as a separate condition was unnecessary.

As defined in algorithm 1, there are two variables that influence the
stiffness of the object. One is the spring coefficient restoring force
proportional to the displacement of the virtual mass, and the other is the
damping force proportional to the velocity of the virtual mass. The
oscillation of an object is determined by these two variables, where a higher
spring coefficient leads to higher-frequency vibrations and a higher damping
coefficient results in faster convergence of vibrations. Of course, these
combinations can represent a variety of vibrations, but this paper focuses on
one of them.

Figure 3: haptic device with the torque sensor was attached to the participant’s hand. Participants performed a swing movement around the x-axis. TABLE I: Impedance parameters in each condition. Condition | $\Delta I$ | $\Delta D$ | $(k_{r},c_{r})$
---|---|---|---
increased inertia | 0.002 | 0 | (0, 0)
decreased inertia | -0.002 | 0 | (0, 0)
damping increase | 0 | 0.02 | (0, 0)
damping decrease | 0 | -0.02 | (0, 0)
elasticity increase | 0 | 0 | (0.2, 0.001)

###  IV-B Measurement Result

Figure 4 shows the temporal variations of the desired torque and the actual
output torque when the virtual moment of inertia is increased or decreased. In
a single swinging motion, the system accelerates at the beginning and
decelerates when it comes to a stop. Thus, the desired torque exhibits a
waveform resembling one period of a sine wave with changes from positive to
negative or negative to positive within a single swinging motion. These
sections represent the swinging motion, and it is evident that the actual
torque generally follows the desired torque during those periods.

Figure 4: The measured torque and the desired torque for $\Delta
I=0.002,-0.002$. Figure 5: The measured torque and the desired torque for
$\Delta D=0.02,-0.02$. Figure 6: The measured torque and the desired torque
for $(k_{r},c_{r})=(0.2,0.001)$.

Figure 5 shows the temporal variations of the desired torque and the actual
output torque when the virtual viscous damping is varied. In the conditions
with positive changes in viscous damping, it can be observed that the actual
torque closely tracks the desired torque. Moreover, for conditions with
viscous damping changes of $\Delta D=-0.02$, the system successfully produces
the desired torque for swinging motion. In the original motion system, viscous
damping, a force proportional to velocity, is nearly negligible. Consequently,
the overall viscous damping of the motion system represented by $\Delta D<0$
becomes negative, enabling the system to represent behaviors that are rarely
observed in everyday life.

Figure 6 shows the temporal variations of the desired torque and the actual
output torque when the virtual stiffness is varied. The graph shows that
oscillatory torque is generated during a single swinging motion. Note that the
swing motion occurs at $t=0.5$. In this condition, the oscillation converges
in approximately 2 seconds within the range of $t=0.5$ to $3.0$, resulting in
a frequency of approximately 1/0.5 = 2 Hz. In summary, in each of the five
conditions tested, it is evident that the system consistently and accurately
tracks the desired torque.

##  V Interview for haptic perception

In a prior study, we used virtual reality to show how impedance control, which
uses force feedback, alters the perception of inertia and resistance during
swinging [32]. Feedback from user descriptions and conference demos revealed
variations in how people respond to the same force feedback. These disparities
may arise from a fundamental mismatch between real-world physics and sensory
perception. Consequently, our study delves into how different physical
parameters affect human perception.

Material perception is about how people sense an object’s surface. We perceive
an object’s physical properties as property perception. We employed factor
analysis using the semantic differential method (SD method), a valuable tool
for identifying crucial factors in perceptual experiences. Nevertheless, it
comes with limitations, including the potential for capturing only some
aspects and variations due to vocabulary differences. As a result, it is
essential to explore the vocabulary used to describe these experiences
initially.

This section explores how users perceive alterations in properties when
employing a haptic device. Our emphasis lies in understanding the how of this
perception rather than the extent, which we aim to comprehend through user
interviews. The insights gathered from these interviews will be incorporated
into the vocabulary used in the analysis conducted using the semantic
differential method.

###  V-A Interview Design

In order to investigate what kind of experiences can be imagined through
different haptic stimuli created by the force-feedback device, we interviewed
three researchers specializing in haptic research, assuming they have a rich
imagination linked to haptic sensations. We asked each researcher to
experience the five different haptic stimuli and describe as many phenomena as
they could imagine arising from them. Additionally, to examine whether the
haptic information could be attributed to the handheld tool, we conducted
interviews on whether the sensations changed when holding something versus
not.

####  V-A1 Selection of Participants

We conducted interview surveys with three researchers engaged in haptic
research: P1, an assistant professor at a university (33 years old); P2, a
research scientist at a company (31 years old); and P3, another research
scientist at a company (34 years old). Note that P3 is the second author of
this paper.

####  V-A2 Presentation of Stimuli

We presented five haptic stimuli to the interviewees: “increased inertia,
decreased inertia, increased damping, decreased damping, and decreased
stiffness.” The variables for impedance under each condition were set as shown
in Table I.

Each participant experienced the stimuli while blindfolded to minimize the
influence of visual information. We only instructed them on the direction
(pitch direction) of hand movement without specifying the speed or manner.
They were advised to improvise the movement based on the sensation of the
stimuli.

####  V-A3 Procedure

As participants experienced each stimulus, we encouraged them to describe as
many phenomena and associations as possible. We also inquired whether their
sensations changed when gripping a handle or not gripping anything.
Participants spent approximately five minutes experiencing and verbalizing
their thoughts for each stimulus. The total time for the experiment and
interview was around 30 minutes.

###  V-B Thematic Analysis

We performed thematic analysis on the transcripts created from the recorded
interview data [39]. First, the author read the transcripts, divided them into
semantic units (codes), and grouped units with the same label. From the
smallest codes, common abstract codes were extracted, and new codes were
created. This process was repeated until no commonalities among the higher-
level codes were found. The resulting higher-level codes were identified as
themes.

###  V-C Themes Obtained for Force Feedback

In the following, we discuss the two main themes identified: “Changes in the
physical properties of handheld object” and “Changes related to bodily
sensations” while citing statements made during the interviews. Statements are
followed by (participant ID, condition) to clarify which participant made the
statement under which force feedback condition.

####  V-C1 Changes in the physical properties of a handheld object

The changes in the physical properties of held objects extracted from
statements can be divided into four categories: rigidity, shape, weight, and
viscosity.

##### Rigidity

Under conditions of reduced rigidity, the virtual weight attached to the tip
lags behind the motion displacement, exhibiting a swaying behavior when
brought to a halt. Statements regarding the rigidity of held objects, such as
feeling pulled, a sense of delayed response, swaying, a yo-yo sensation, and a
rubber-like displacement, were obtained in response to reduced rigidity
conditions. P3 expressed this sensation as follows:

> “After moving, there’s a slight delay, and then, the force feedback arrives,
> as if it’s lagging. Maybe the timing isn’t quite spot-on. There’s a feeling
> of swaying after I move like the force is being applied later.” (P3, Reduced
> Rigidity)

Additionally, P1 described the swaying and delayed phenomenon as resembling
yo-yo motion.

> “It’s like I’m playing with a yo-yo. But, it’s not like I’m swinging it
> downward, but more in a forward direction. I like the fact that it feels
> like a yo-yo because I can feel the force after swinging it, like it is
> being pulled forward.” (P1, Reduced Rigidity)

From expressions like “being pulled” or “lagging behind,” it can be inferred
that the participants expected instantaneous force feedback in response to
their movements but instead experienced delayed feedback, perceiving a
structure that does not immediately follow their motion between their hands
and the held object’s tip.

##### Shape

Many descriptions of the held object’s shape changing were observed. P3
reported feeling as if they were fanning under increased damping conditions
and also associated it with holding something wide.

> “If I had to describe it in some way, this is a fan. Something broad.” (P3,
> increased damping)

When moving a thin, wide object like a folding fan, the viscous resistance
component becomes dominant even in the air. This implies that an increase in
viscous resistance evokes such a phenomenon in reality, inducing an image of
holding a wide-shaped object. Moreover, P2 envisioned an expanded circular
shape under increased damping conditions, which is consistent with P3’s
impression of a “board object.”

> “I definitely feel like the tool is stretching. In terms of shape, it’s a
> circle.” (P2, increased damping)

Conversely, P2 reported that the object felt elongated under reduced inertia
conditions.

> “With this, it’s a stick, like a really long, slender stick. So, it’s
> incredibly strange that it doesn’t hit the table.” (P2, Reduced Inertia)

Ideally, decreased inertia should result in the object being perceived as
shorter. Despite this, the object was reported as feeling longer, possibly
because the acceleration felt when swinging the object downward was larger
than expected. As a result, participants may have inferred that the object was
longer than its actual size, as longer objects would be expected to have a
higher acceleration when swung downward.

##### Weight and Heaviness

Participants also reported changes in the perceived weight and heaviness of
held objects. For instance, P3 described an increase in perceived weight
during the increased inertia condition:

> “It feels a bit heavier. It feels like I’m holding something heavier than
> before.” (P3, Increased Inertia)

Conversely, P3 reported a decrease in perceived weight under the decreased
inertia condition:

> “When I drop it, it feels incredibly light, but when I lift it, it feels
> somewhat heavy. (Omitted) It should be heavy, but it feels light. It’s like
> I can’t feel the weight of this device, which gives it a very peculiar
> sensation.” (P3, Decreased Inertia)

It is interesting to note that participants perceived changes in the object’s
weight even though the object’s mass remained constant. This may be due to the
changes in the moment of inertia affecting the force feedback and participants
interpreting this as a change in weight.

##### Viscosity

Participants sometimes attributed the force feedback not to the properties of
the held object but to environmental factors. In particular, descriptions
related to viscosity were frequently mentioned under the increased damping
condition.

> “It feels like I’m in mud. I feel a strong resistance. The movement is
> delayed. It feels slimy.” (P2, increased damping)

Moreover, P1 used the term “viscosity” in both the increased inertia and
increased damping conditions. While they recognized differences between the
two experiences, they still described both using the term “viscosity.” This
demonstrates that phenomena that can be distinguished at the sensory level can
sometimes be represented with similar expressions at the conceptual level.

> “It feels like air rather than water. The viscosity has changed. And it
> feels like there’s air resistance or something like that. And also, it feels
> like my hand has become heavier.” (P1, Increased Inertia)

> “And this one is more like being underwater than the previous one. The
> previous one felt like air, but this one has very high viscosity. It feels
> quite heavy.” (P1, increased damping)

####  V-C2 Changes related to bodily sensations

##### Body image and abilities

Contrary to the author’s expectations, descriptions were found not only about
the handheld tools but also about changes in their body image. P1 reported a
sensation of changes in the shape of their fingers and entire hands. It is
uncertain whether the increase in viscosity, for example, can be attributed to
the viscosity of the environment or to the properties of one’s own body.

> “When I tried to swing, I suddenly felt the torque, and I also thought that
> there was a feeling that my fingers were stretching. I think this is largely
> due to the fact that it becomes difficult to understand the position of my
> fingers and hands, and I think it is related to that. In the end, I felt
> that the delayed torque force was stretching my body.” (P1, reduced
> stiffness)

> “It feels like there’s something like cloth on my hand. It feels like I have
> fins attached and receiving resistance and swelling up.” (P1, increased
> damping)

Moreover, P2 imagined that their physical abilities had improved. The
acceleration of their movement due to decreased inertia can be attributed to
enhancing their physical abilities.

> “It feels light because of the feedback. And I feel like my strength has
> increased a lot. I’m not doing it now, but if I were to push something, I
> feel like I could push it really hard.” (P2, inertia reduction)

> “Also, I feel my body light. It’s more like my body is light rather than
> what I’m holding.” (P3, viscosity reduction)

##### Body position

In addition to changes in body shape, there were reports of feeling as if the
position of their body was misaligned. This was often seen during the
increased damping condition, where the force feedback from moving their hand
was greater than expected, causing a sensation of delayed force, and the
temporal misalignment was interpreted as spatial misalignment. It is possible
that the reverse phenomenon of perceiving force by inserting temporal or
spatial delays into movement is occurring and that the occurrence of force is
causing the perception of spatial or temporal misalignment.

> “I feel like my hand is growing or the position of my hand is somehow
> misaligned. That’s probably because the movement is delayed by one tempo, so
> the body image becomes misaligned, I think.” (P2, increased damping)

> “I don’t necessarily feel like my hand is in the place where this resistance
> is felt, but it’s true that it’s a bit out-of-body-like, so I think it’s
> interesting to create such an effect. I think the influence of the vibration
> is quite significant, and because of that, my sense of position around my
> hand becomes a bit vague.” (P1, increased damping)

##### Sense of agency

There were also many descriptions regarding the sense of agency, whether they
were initiating the movement or not. P1 mentioned that although the decision
to initiate the movement was their own intention, they did not feel like they
were driving the movement afterward. This can be attributed to the fact that
the feedback proportional to the angular acceleration causes the entire
movement system to move at a speed beyond their prediction, making them feel
as if they cannot control it.

> “There is a slight sense of incongruity in accelerating, not like being
> pushed a little, but more like a clear sense of being moved. It’s that
> strong. Although I’m only pulling the initial trigger, I don’t have much
> awareness that I’m driving the movement afterward. Also, I’m not really
> conscious of stopping it.” (P1, inertia reduction)

On the other hand, P1 described a sense of being able to control the movement
under the viscosity reduction condition.

> “If I want to stop, it stops there, or rather, it feels like it won’t
> accelerate further, so there is a sense of agency. I can tell it’s my
> movement.” (P1, viscosity reduction)

Moreover, they mentioned that after a few swings, their prediction model
changes, and they feel like they can control the movement. This suggests that
feedback proportional to velocity may be easier to adapt to than feedback
proportional to acceleration.

> “As I get used to it, I feel like I can stop it where I want to stop. It
> takes some effort, but the response is better than before (inertia
> reduction).” (P1, viscosity reduction)

###  V-D Discussion

Surpassing our expectations, we discovered that various phenomena could be
evoked through haptic stimulation. The results regarding the user’s perception
of object properties and interactions with the environment were largely as
anticipated. When force was exerted in the direction of increasing inertia,
objects became more tough to move, their lengths seemed longer, and the
sensation of holding a larger object arose. Similarly, when force was applied
in the direction of increasing viscosity, objects became more tough to move,
and a more viscous, sticky sensation was often reported. However, these
“difficult to move” sensations were frequently confounded, with reports of
increased viscosity under increased inertia or increased object size under
conditions of increased viscosity. Further investigation through quantitative
experiments is necessary to determine how much each force presentation
influences human representations, such as “size” and “stickiness.”

Moreover, it was found that under conditions of reduced rigidity, expressions
of “flexibility” and “springiness” were possible. It was also revealed that
under conditions of decreased rigidity, phenomena were more difficult to
associate with something specific than conditions of inertia or viscosity
changes. This difficulty might be attributed to predicting motion based solely
on force feedback. In the other four conditions, there was feedback on
velocity and acceleration at each point in time, resulting in high
reproducibility of movement. In contrast, conditions of reduced rigidity
involved simulating specific object movements, which led to more complex
behavior and made it harder to imagine the nature of the motion. This
difficulty in imaging and predicting motion can be inferred from the tendency
to repeat swinging motions multiple times before verbalizing the phenomenon
under conditions of decreased rigidity. On the other hand, the diversity of
experienced images will change according to the given language. It may be
necessary to investigate how various motion-describing vocabularies relate to
different representations.

In conditions of accelerating motion with decreased inertia and viscosity,
there were fewer opinions attributing the experience to the properties of the
handheld object, with more reports attributing the experience to the
transformation of one’s own body. This may be due to the behavior of objects
appearing to have negative inertia when attempting to express smaller inertia
than the handheld object’s inherent inertia. In reality, objects that behave
as if they have negative inertia (starting to move on their own when trying to
accelerate) do not exist. To interpret such unlikely phenomena, the
possibility of attributing them to changes in one’s body’s properties (e.g.,
lighter hands, stronger force) rather than the tool itself may arise.
Additionally, it was found that the experience of bodily transformation is
more likely to be attributed to a relaxed state than holding or grasping an
object.

###  V-E Conclusion of Interview Study

In this section, researchers experienced various haptic stimuli to investigate
what impressions force feedback could evoke regarding handheld objects. As a
result, it was confirmed that perceptions of size, weight, and environmental
viscosity change depending on the type of haptic stimulation. From these
results, it was determined that to attribute the information from each force
feedback to the physical properties of the handheld object, it is advisable to
perform movements while the user imagines holding something and to consider
the device’s inherent physical properties. In the following section, based on
the various impressions evoked by the force feedback obtained from this
interview, an investigation will be conducted to determine how much each force
feedback technique influences each impression.

##  VI Evaluation of haptic perception and impedance change

In the previous section, a qualitative investigation explored the potential
associations between varying types of force feedback and their resulting
perceptions. This allowed for a certain degree of prediction regarding the
perceptions evoked by the proposed device’s motion intervention experiences.
However, the extent to which each perception is linked to changes in
individual impedance cannot be determined solely through qualitative research.

Therefore, this section aims to clarify the necessary parameter adjustments to
evoke each perception by investigating the degree to which individual
impedance changes affect the various perceptions obtained through qualitative
research using experiments with human participants. As an experimental method
to identify the main factors contributing to perceptual experiences, the
previous section mentioned factor analysis on data obtained through the
“semantic differential” method (SD method), which involves evaluating a single
stimulus using various adjective pairs. The advantage of this method lies in
its ability to extract dimensions of the space representing human dynamic
touch perceptions of physical properties (material sensations) through
multivariate analysis.

###  VI-A Selection of Word Pairs for Property Perception Evaluation

In this section, we select adjective pairs for evaluation in the experiment.
We selected adjectives corresponding to themes and categories obtained from
the interviews in the section V. Since it may be difficult to describe some
types of force feedback using adjectives, we also selected words that include
verbs and nouns frequently used by participants for such stimuli. In addition,
we selected words from the obtained themes related to the sensations of the
handheld object itself and the interaction between the handheld object and the
environment, such as “changes in the physical properties of the held tool,”
“interactions occurring between the environment,” and “changes in motion when
moving the arm.”

In word selection, it is crucial to strike a balance. We aim to represent
various aspects while keeping the burden on participants low and avoiding word
interactions. We chose words with low similarity, limiting the evaluation
words to a maximum of 10, resulting in 8 words. Here are the selected words
related to changes in the physical properties of the held tool and
interactions occurring between the environment: Long – Short, Wide – Narrow,
Thick – Thin, Hard – Soft, Heavy – Light, Stiff – Flexible and Sticky –
Smooth.

###  VI-B Experiment

Using the word list selected in the section VI-A, we investigated to
understand how the proposed device’s motion intervention produces various
sensations in humans.

####  VI-B1 Participants

The participants were 16 people aged 21 to 24 (1 female, 15 males), with an
average age of 22.75 (standard deviation 1.06 years).

####  VI-B2 Haptic stimuli used in the experiment

As in the section IV, five types of haptic stimuli were prepared. The stimuli
were “increased inertia, decreased inertia, increased damping, decreased
damping, and decreased stiffness.”

####  VI-B3 Procedure

Participants wore the haptic device on their right hand and experienced haptic
stimuli. To minimize the influence of the device’s movement and the sound
emitted, the participants placed their arms behind a partition, as shown in
Figure 7, and performed swinging motions. In addition, participants wore
noise-canceling headphones, and white noise was played to prevent them from
hearing the sounds emitted by the device. Participants could experience force
feedback while moving their right hand. While performing swinging motions,
they evaluated how well the haptic stimuli corresponded to the words selected
in the previous section using a tablet. The evaluation was conducted using a
7-point Likert scale. After evaluating all words for one stimulus, the screen
switched to a waiting screen. Participants could rest until their arm fatigue
subsided and proceed to the next trial at their own pace. They repeated the
evaluation three times for all five experimental stimuli. The experiment took
approximately 45 minutes, including the explanation. Participants were
rewarded with an Amazon gift card worth $6 as compensation.

Figure 7: Participants are wearing noise-canceling headphones and a haptic
device. The participant evaluates on a tablet while shaking their wrist.

###  VI-C Data Analysis

Since evaluations for the five types of stimuli were repeated three times for
13 words, we averaged the evaluated values for each stimulus. As it is highly
likely that the pairs of words are correlated, we attempt to extract lower-
dimensional factors through factor analysis.

Figure 8 shows the scree plot of the factor analysis. We chose the number of
factors as 4, where the second-largest change in the slope of the broken line
occurred. To make the four factors more comprehensible, we apply varimax
rotation to the results. The heatmap of loadings after the rotation is shown
in Figure 9. The squared factor loadings, the contribution rates of each
factor, and the cumulative contribution rates are shown in Table II. The four
factors can explain 75.8 % of the data. In studies on the extraction of haptic
dimensions, factors and their cumulative contribution rates are often around
79 % [40]. Compared to those studies, the contribution rate by factors in this
study is slightly lower. Several causes can be considered for this. First, in
the extraction of haptic dimensions using conventional haptic stimuli,
evaluations are conducted on existing objects, so the participants are more
likely to have touched those objects before. In contrast, in this study, the
expressions of simulated material properties are conveyed through a haptic
device, making it challenging to represent the complete information as when
swinging real objects. Additionally, some experiences were not grounded in
words, such as negative inertia and negative viscosity, which cannot be
experienced with objects in the real world. Therefore, individual differences
among participants in attributing these experiences to specific material
properties may have increased, leading to a lower contribution rate explained
by the factors.

Figure 8: Scree plot depicting eigenvalues for principal components. The plot
illustrates the diminishing contribution of each component to the total
variance in the dataset. Figure 9: Heatmap of Word-Factor Associations. TABLE
II: Sum of Squared Loadings and the factor’s contribution

| Factor 1 | Factor 2 | Factor 3 | Factor 4
---|---|---|---|---
Sum of Squared Loadings | 2.283029 | 1.221785 | 0.982619 | 0.821623
% of Variance | 0.326147 | 0.174541 | 0.140374 | 0.117375
Cumulative % | 0.326147 | 0.500688 | 0.641062 | 0.758437

Figure 11 and 11 show the arrangement of each stimulus in the factor score
space. A small marker represents each data point, and each arrow indicates
what words are associated with each factor.

Figure 10: bi-plot between factor 1 and factor 2 dimension

Figure 11: bi-plot between factor 3 and factor 4 dimension

###  VI-D Discussion

####  VI-D1 Property perception dimensions

From the results of the factor analysis, it is considered that the factors of
the material perception of the handheld object by the proposed method are
mainly: “size factor”, “viscosity factor”, “weight factor”, and “flexibility
factor”.

For the first factor, “size factor”, it can be seen that words such as “long”,
“thick”, “wide”, and “hard” are well connected. This factor can be inferred to
be strongly associated with objects like long, thick, and rigid cubes, like a
rod. In this experiment, the participants were asked to perform pitch-swinging
motions. As revealed in experiments by Turvey [7] and Zenner [15], the
perception of an object’s size is influenced by the principal moment of
inertia around the rotation axis. The object’s length and thickness determine
the principal moment of inertia in the pitch direction and is not much related
to width $(I=\frac{1}{3}m(l^{2}+d^{2}))$. Nevertheless, the inclusion of the
component “wide” may be influenced by the factor of spatial spread, such as
length and thickness.

The second factor, “viscosity factor”, was strongly associated with words such
as “sticky” and “thick”. As hypothesized, the viscosity factor in the
environment appeared due to the force proportional to velocity. However, it
was unexpected that it was associated with “thickness,” which is the spatial
spread of the object. Instead, if one were to predict the spatial spread of
the object from the viscosity factor, one would imagine a thin object like a
fan so that the thinness factor would become stronger. Contrary to this, it is
suggested that users imagined a thick object in a high-viscosity environment.
By the way, the feeling of stickiness was expressed as Sticky–Smooth, and
thickness as Thick-Thin. However, the term “thick liquid” is sometimes used to
describe a high-viscosity liquid. The word “thick”, describing the density of
the liquid, and the word “thick”, describing the spatial spread, may be
connected in the brain, possibly drawing out the correlation between the two
in a top-down manner.

The third factor, “weight factor”, had a strong association with words such as
“heavy” and “hard”. While it may seem that spatial spread and the weight of an
object are, of course, correlated in reality (indeed, larger objects are more
likely to be heavier), this analysis resulted in a separate independent
factor. This is also consistent with Turvey et al.’s claim that the weight of
an object does not affect the perception of spatial spread through dynamic
touch [3]. However, it should be noted that the word “heavy” includes not only
the properties of the object but also the lightness and heaviness of one’s
movement, so it may not purely describe the weight of the object.

The fourth factor, “flexibility factor”, had a strong association with words
such as “flexible”. This corresponds to the flexibility of the object. Also,
this flexibility factor has a weak correlation with words such as thickness
and width. In terms of thickness, it may be since one cannot feel something
like bending unless the object has a certain thickness. Regarding width, there
were reports that people imagined objects with flexibility, like fans or
placemats, when experiencing flexibility. There is also a similar term,
“hardness,” but the impact of this term on the flexibility factor was small.
This is probably due to the distinction between the flexibility and softness
of the object. Flexible objects are those with a core and do not sag under
their weight when held, while soft objects easily deform under their weight.

Examples of object properties and environmental properties that change with
these factors are shown in Figure 13. For the spatial spread factor, the size
of the object changes. For the viscosity factor, the difference in viscosity
in the environment when swinging the object is represented. From the weight
factor, the weight of the object itself and the difficulty of motion change.
From the flexibility factor, one can imagine objects made of rubber-like
materials that are flexible to hard objects.

####  VI-D2 Relationship between impedance and property factors

Figure 12: Mean of factor scores in each impedance change.

Now that we have extracted the factors by motion intervention, let us see how
the impedance is related to each factor. Figure 12 shows the mean of factor
scores calculated for each impedance change.

In the increased inertia condition, an increase in size factor and weight
factor is observed. This shows that the increase in the moment of inertia in
the motion enlarges the perception of spatial spread and further increases the
perception of weight. Also, it does not have much effect on viscosity and
flexibility.

In the decreased inertia condition, there is a tendency for all factors to
decrease moderately overall. It is assumed that the perception of size,
viscosity, and weight decreased as the motion accelerated. It is also related
to the image of being rigid, which may be due to the agility of the movement.
The motion of a flexible object gives the impression of being vibrational and
slow-moving. In contrast, the motion of a rigid object gives the impression of
being linear and fast-moving, which is thought to be related to rigidity.

In the increased damping condition, in contrast to the increased inertia
condition, it is found to affect Factor 2 and Factor 4, stickiness, and
flexibility. The perception of stickiness increases as the increased dampings.
In addition, there is a positive correlation with the perception of
flexibility. It was a surprising result that flexibility was also associated
with increased viscosity. One possible reason for this is that the words
flexibility were projected as a result of trying to attribute the force, like
viscosity during motion, to the properties of the tool. It is known that
objects with high flexibility are more affected by viscous resistance than
those with low flexibility (results of multi-particle simulations). A high
viscous resistance may lead the user to infer that the object is flexible.

In the decreased viscosity condition, a similar tendency to the decreased
inertia condition was observed, but the extent was greater than that of the
decreased inertia. This is because the feedback in the direction of
accelerating the movement causes acceleration even with a slight movement by
the user, and the sensation of being accelerated is stronger than during the
decreased inertia. It is known that the sensation of moving by oneself is
smaller during the decreased viscosity. As a result, the perception of size,
viscosity, and weight has decreased. Regarding rigidity, as in the case of
decreased inertia, rigidity is imagined from the speed of movement.

For the decreased stiffness condition, a positive correlation was observed for
all factors. Regarding the size factors, the score is somewhat high due to the
prediction that the object must be somewhat long for elastic motion to occur.
It would be difficult to feel the flexibility when shaking a short object.
Also, regarding viscosity, as in the case of increased damping conditions, the
flexibility of the object is more likely to occur in a high-viscosity
environment. The magnitude of viscosity and the magnitude of flexibility can
be perceived as linked. Lastly, regarding weight, the force stimulus is
delayed in the initial movement under the increased elasticity condition
compared to other conditions. This temporal delay is thought to evoke the
image of an object with a weight at the tip, increasing the perception of the
object’s weight.

It is also worth mentioning the differences between the conditions. Both the
increased inertia condition and the increased damping condition produce forces
that hinder movement. In the experiment, there were reports that it was
difficult to express the difference between these two in words, but they could
be understood. However, the results showed that the increased inertia affected
the perception of the object’s weight and size. In contrast, the increased
damping condition affected the environmental viscosity and flexibility,
resulting in independent effects. This indicates that people can not only
distinguish these two stimuli but also treat them separately at the layer of
meaning attribution.

Figure 13: Examples of object properties and environmental properties for each
factor.

We must also mention the non-linearity between the impedance change and the
factors. The size and weight factors increased under conditions of increased
inertia, whereas all four factors tended to decrease under conditions of
decreased inertia. Similarly, the flexibility and viscosity factors increased
under increased damping, while all factors tended to decrease under decreased
viscosity. We suspect this nonlinear relationship for the same impedance is
due to the rarity of sensory information. The experience of increased inertia
and viscosity can be felt in everyday life by holding and shaking a tool or
stirring water with one’s hands. Therefore, it is easy to attribute the
increase in inertia or viscosity to a specific element. On the other hand, we
rarely experience a decrease in inertia or viscosity. This makes the
connection to a specific property weak, and it is possible that we can
attribute any phenomenon to any property.

##  VII Conclusion

The objective of this paper was to elucidate the dimensions present in the
haptic experiences that alter with the impedance of motion and to investigate
the extent of influence each impedance alteration exerts on these dimensions.
Through evaluations employing pairs of phrases, we derived four dimensions:
size (perception related to the size and shape of an object) weight
(perception of an object’s weight) viscosity (perception of the viscosity
around an environment) flexibility (perception of an object’s flexibility)
Furthermore, we clarified the extent of influence each impedance change has on
these four dimensions.

However, it is essential to note that more than this paper is needed to
provide a complete understanding of how perceptions might manifest when
various methods are combined. Whether the combination of these perceptions can
effectively express each dimension requires further investigation.

The accomplishments obtained from this experiment imply that changes in each
impedance do not independently trigger alterations in perception but rather
invoke various phenomena. This poses a challenge that conventional
psychophysical experiments, which often focus on averages, cannot address.
Particularly in the realm of haptic phenomena, where diversity in perception
is expected, it is essential to engage in not only discussions of classical
averages but also qualitative research to discern this diversity.

With these findings in mind, future research in the haptics field should
undertake a more detailed analysis of the impact of impedance changes on
perceptual dimensions and explore the interactions between these dimensions.
Furthermore, conducting verification in real-world scenarios, such as
incorporating visual stimuli, to establish the relationship between impedance
changes and perceptual dimensions and subsequently connecting this to
practical applications is an anticipation for future study.

## References

  * [1] H. Shirado and T. Maeno, “Modeling of human texture perception for tactile displays and sensors,” in _First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics Conference_ , Mar. 2005, pp. 629–630.
  * [2] W. M. Bergmann Tiest and A. M. L. Kappers, “Analysis of haptic perception of materials by multidimensional scaling and physical measurements of roughness and compressibility,” _Acta Psychol._ , vol. 121, no. 1, pp. 1–20, Jan. 2006.
  * [3] M. T. Turvey, G. Burton, E. L. Amazeen, M. Butwill, and C. Carello, “Perceiving the width and height of a hand-held object by dynamic touch,” _J. Exp. Psychol. Hum. Percept. Perform._ , vol. 24, no. 1, pp. 35–48, Feb. 1998.
  * [4] G. Burton, M. T. Turvey, and H. Y. Solomon, “Can shape be perceived by dynamic touch?” _Percept. Psychophys._ , vol. 48, no. 5, pp. 477–487, Nov. 1990.
  * [5] M. T. Turvey, “Dynamic touch,” _Am. Psychol._ , vol. 51, no. 11, pp. 1134–1152, Nov. 1996.
  * [6] S. J. Lederman and R. L. Klatzky, “Hand movements: A window into haptic object recognition,” _Cognitive psychology_ , vol. 19, no. 3, pp. 342–368, 1987.
  * [7] M. T. Turvey and C. Carello, “Dynamic touch,” _Perception of space and motion_ , 1995.
  * [8] M. Hollins, R. Faldowski, S. Rao, and F. Young, “Perceptual dimensions of tactile surface texture: a multidimensional scaling analysis,” _Percept. Psychophys._ , vol. 54, no. 6, pp. 697–705, Dec. 1993.
  * [9] C. Park, J. Kim, and S. Choi, “Visuo-haptic crossmodal shape perception model for Shape-Changing handheld controllers bridged by inertial tensor,” in _Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’23, no. Article 699. New York, NY, USA: Association for Computing Machinery, Apr. 2023, pp. 1–18.
  * [10] E. Fujinawa, S. Yoshida, Y. Koyama, T. Narumi, T. Tanikawa, and M. Hirose, “Computational design of hand-held VR controllers using haptic shape illusion,” in _Proceedings of the 23rd ACM Symposium on Virtual Reality Software and Technology_. ACM, 2017, p. 28.
  * [11] K. Zhu, T. Chen, F. Han, and Y.-S. Wu, “HapTwist: Creating interactive haptic proxies in virtual reality using low-cost twistable artefacts,” in _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’19, no. Paper 693. New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–13.
  * [12] Y.-W. Chen, W.-J. Lin, Y. Chen, and L.-P. Cheng, “PneuSeries: 3D shape forming with modularized Serial-Connected inflatables,” in _The 34th Annual ACM Symposium on User Interface Software and Technology_ , ser. UIST ’21. New York, NY, USA: Association for Computing Machinery, Oct. 2021, pp. 431–440.
  * [13] M. Feick, S. Bateman, A. Tang, A. Miede, and N. Marquardt, “Tangi: Tangible proxies for embodied object exploration and manipulation in virtual reality,” in _2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)_ , 2020, pp. 195–206.
  * [14] C. Swindells, A. Unden, and T. Sang, “TorqueBAR: an ungrounded haptic feedback device,” in _Proceedings of the 5th international conference on Multimodal interfaces_ , ser. ICMI ’03. New York, NY, USA: Association for Computing Machinery, Nov. 2003, pp. 52–59.
  * [15] A. Zenner and A. Krüger, “Shifty: A Weight-Shifting Dynamic Passive Haptic Proxy to Enhance Object Perception in Virtual Reality,” _IEEE Transactions on Visualization and Computer Graphics_ , 2017.
  * [16] J. Shigeyama, T. Hashimoto, S. Yoshida, T. Narumi, T. Tanikawa, and M. Hirose, “Transcalibur: A weight shifting virtual reality controller for 2D shape rendering based on computational perception model,” in _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’19, no. Paper 11. New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–11.
  * [17] J. F. Gonzalez Avila, J. C. McClelland, R. J. Teather, P. Figueroa, and A. Girouard, “Adaptic: A shape changing prop with haptic retargeting,” in _Proceedings of the 2021 ACM Symposium on Spatial User Interaction_ , ser. SUI ’21, no. Article 4. New York, NY, USA: Association for Computing Machinery, Nov. 2021, pp. 1–13.
  * [18] A. Zenner and A. Krüger, “Drag:on: A virtual reality controller providing haptic feedback based on drag and weight shift,” in _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’19, no. Paper 211. New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–12.
  * [19] Y. Liu, T. Hashimoto, S. Yoshida, T. Narumi, T. Tanikawa, and M. Hirose, “ShapeSense: a 2D shape rendering VR device with moving surfaces that controls mass properties and air resistance,” in _ACM SIGGRAPH 2019 Emerging Technologies_ , ser. SIGGRAPH ’19, no. Article 23. New York, NY, USA: Association for Computing Machinery, Jul. 2019, pp. 1–2.
  * [20] N. Ryu, W. Lee, M. J. Kim, and A. Bianchi, “Elastick: A handheld variable stiffness display for rendering dynamic haptic response of flexible object,” in _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_. New York, NY, USA: Association for Computing Machinery, Oct. 2020, pp. 1035–1045.
  * [21] H.-R. Tsai, C.-W. Hung, T.-C. Wu, and B.-Y. Chen, “ElastOscillation: 3D multilevel force feedback for damped oscillation on VR controllers,” in _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’20. New York, NY, USA: Association for Computing Machinery, Apr. 2020, pp. 1–12.
  * [22] N. Ryu, H.-Y. Jo, M. Pahud, M. Sinclair, and A. Bianchi, “GamesBond: Bimanual haptic illusion of physically connected objects for immersive VR using grip deformation,” in _Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’21, no. Article 125. New York, NY, USA: Association for Computing Machinery, May 2021, pp. 1–10.
  * [23] S. Heo, C. Chung, G. Lee, and D. Wigdor, “Thor’s hammer: An ungrounded force feedback device utilizing Propeller-Induced propulsive force,” in _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’18, no. Paper 525. New York, NY, USA: Association for Computing Machinery, Apr. 2018, pp. 1–11.
  * [24] S. Je, M. J. Kim, W. Lee, B. Lee, X.-D. Yang, P. Lopes, and A. Bianchi, “Aero-plane: A handheld Force-Feedback device that renders weight motion illusion on a virtual 2D plane,” in _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology_ , ser. UIST ’19. New York, NY, USA: Association for Computing Machinery, Oct. 2019, pp. 763–775.
  * [25] T. Sasaki, R. S. Hartanto, K.-H. Liu, K. Tsuchiya, A. Hiyama, and M. Inami, “Leviopole: Mid-air Haptic Interactions Using Multirotor,” in _ACM SIGGRAPH 2018 Emerging Technologies_ , ser. SIGGRAPH ’18. New York, NY, USA: ACM, 2018, pp. 12:1—-12:2. [Online]. Available: http://doi.acm.org/10.1145/3214907.3214913
  * [26] Y.-W. Wang, Y.-H. Lin, P.-S. Ku, Y. Miyatake, Y.-H. Mao, P. Y. Chen, C.-M. Tseng, and M. Y. Chen, “JetController: High-speed ungrounded 3-DoF force feedback controllers using air propulsion jets,” in _Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’21, no. Article 124. New York, NY, USA: Association for Computing Machinery, May 2021, pp. 1–12.
  * [27] C.-Y. Tsai, I.-L. Tsai, C.-J. Lai, D. Chow, L. Wei, L.-P. Cheng, and M. Y. Chen, “AirRacket: Perceptual design of ungrounded, directional force feedback to improve virtual racket sports experiences,” in _CHI Conference on Human Factors in Computing Systems_ , ser. CHI ’22, no. Article 185. New York, NY, USA: Association for Computing Machinery, Apr. 2022, pp. 1–15.
  * [28] K. N. Winfree, J. Gewirtz, T. Mather, J. Fiene, and others, “A high fidelity ungrounded torque feedback device: The iTorqU 2.0,” _World Haptics 2009_ , 2009.
  * [29] J. M. Walker, H. Culbertson, M. Raitor, and A. M. Okamura, “Haptic orientation guidance using two parallel Double-Gimbal control moment gyroscopes,” _IEEE Trans. Haptics_ , vol. 11, no. 2, pp. 267–278, Apr. 2018.
  * [30] N. Nakamura and Y. Fukui, “An innovative non-grounding haptic interface’GyroCubeSensuous’ displaying illusion sensation of push, pull and lift,” in _ACM SIGGRAPH 2005 Posters_. ACM, 2005, p. 92.
  * [31] H. Yano, M. Yoshie, and H. Iwata, “Development of a non-grounded haptic interface using the gyro effect,” in _11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. HAPTICS 2003. Proceedings._ , mar 2003, pp. 32–39.
  * [32] T. Hashimoto, S. Yoshida, and T. Narumi, “MetamorphX: An ungrounded 3-DoF moment display that changes its physical properties through rotational impedance control,” in _Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology_ , ser. UIST ’22, no. Article 72. New York, NY, USA: Association for Computing Machinery, Oct. 2022, pp. 1–14.
  * [33] T. Hashimoto, S. Yoshida, and T. Narumi, “SomatoShift: A wearable haptic display for somatomotor reconfiguration via modifying acceleration of body movement,” in _ACM SIGGRAPH 2023 Emerging Technologies_ , ser. SIGGRAPH ’23, no. Article 17. New York, NY, USA: Association for Computing Machinery, Jul. 2023, pp. 1–2.
  * [34] P. Lopes, S. You, L.-P. Cheng, S. Marwecki, and P. Baudisch, “Providing Haptics to Walls & Heavy Objects in Virtual Reality by Means of Electrical Muscle Stimulation,” pp. 1471–1482, 2017.
  * [35] P. Lopes, A. Ion, and P. Baudisch, “Impacto: Simulating p hysical i mpact by combining tactile stimulation with electrical mu scle stimulation,” _UIST; Proceedings of the Annual ACM Symposium on User Interface Software and Technology_ , pp. 11–19.
  * [36] S. Shimizu, T. Hashimoto, S. Yoshida, R. Matsumura, T. Narumi, and H. Kuzuoka, “Unident: Providing impact sensations on handheld objects via High-Speed change of the rotational inertia,” in _2021 IEEE Virtual Reality and 3D User Interfaces (VR)_ , Mar. 2021, pp. 11–20.
  * [37] T. Amemiya and T. Maeda, “Asymmetric oscillation distorts the perceived heaviness of handheld objects,” _IEEE Transactions on Haptics_ , vol. 1, no. 1, pp. 9–18, 2008.
  * [38] N. Hogan, “Impedance control: An approach to manipulation: Part II—Implementation,” _J. Dyn. Syst. Meas. Control_ , vol. 107, no. 1, pp. 8–16, Mar. 1985.
  * [39] V. Braun and V. Clarke, “Using thematic analysis in psychology,” _Qualitative research in psychology_ , vol. 3, no. 2, pp. 77–101, 2006.
  * [40] H. Shirado and T. Maeno, “Modeling of texture perception mechanism for tactile display and sensor,” _Transactions of the Virtual Reality Society of Japan_ , vol. 9, no. 3, pp. 235–240, 2004.

##  VIII Biography Section

|  Takeru Hashimoto is currently a project assistant professor at the Cyber
Interface Laboratory in The University of Tokyo in Japan. He received his
Ph.D. in information science and technology from The University of Tokyo in
2023. His awards include the Young Researcher’s Award from the virtual reality
society of Japan and the Honorable Mentions Award in SIGCHI. His current
research area is Virtual / Augmented Reality of haptics and Human-
Augmentation.
---|---
|  Shigeo Yoshida is currently a senior researcher at OMRON SINIC X
Corporation in Japan. He received his Ph.D. in Information Studies, master’s
degree in Arts and Sciences, and bachelor’s degree in Engineering from The
University of Tokyo in 2017, 2014 and 2012 respectively. His research interest
involves a broad area of Human-Computer Interaction. He has been especially
focusing on designing interactions based on the mechanisms of perception and
cognition of our body.
---|---
|  Takuji Narumi received the B.E. and M.E. degrees from The University of
Tokyo, in 2006 and 2008, respectively, and the Ph.D. degree in engineering
from The University of Tokyo, in 2011. He is currently an Associate Professor
with the Graduate School of Information Science and Technology, The University
of Tokyo. His research interests include the intersection of technologies and
human science, and he has been working on extending human senses, cognition,
and behavior by combining virtual reality and augmented reality technologies
with findings from psychology and cognitive science. He was a recipient of
several awards, including MEXT The Young Scientists’ Award, the SIGCHI Japan
Chapter Distinguished Young Researcher Award, the Japan Media Arts Festival
2017 Excellence Award, and the CHI Honorable Mentions, in 2019 and 2020.
---|---