This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/TNSRE.2015.2464719, IEEE Transactions on Neural Systems and Rehabilitation Engineering
JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 20121

Measurement of Contact Behavior Including
Slippage of Cuﬀ When Using Wearable Physical
Assistant Robot
Yasuhiro Akiyama, Shogo Okamoto, Yoji Yamada, Member, IEEE, and Kenji Ishiguro

Abstract—Continuous use of wearable robots cancause skin injuries beneath the cuﬀs of robots. To prevent such injuries, understanding the contact behaviorof the cuﬀ is important. Thus far, this contact behavior
has not been studied because of the diﬃculty involved
in measuring the slippage under the cuﬀ. In this study,
for the first time, the relative displacement, slippage,and interaction force and moment at the thigh cuﬀ
of a robot during sit-to-stand motion were measured
using an instrumented cuﬀ, which was developed forthis purpose. The results indicated that the slippage
and relative displacement under the cuﬀ was unevenbecause of the rotation of the cuﬀ, which suggests thatthe risk of skin injuries is diﬀerent at diﬀerent positions.
Especially, the skin closer to the hip showed larger
dynamism, with a maximum slippage of approximately
10 mm and a displacement of 20 mm during motion.
Another important phenomenon was the individual
diﬀerence among subjects. During motion, the interaction force, moment, and slippage of some subjects
suddenly increased. Such behavior results in stressconcentration, which increases the risk of skin injuries.
These analyses are intended to understand how skin
injuries are caused and to design measures to prevent
such injuries.
Index Terms—Physical Assistant Robot, Contact
Mechanics, Human–Robot Interaction, Safety.

I. Introduction
HYSICAL assistant robots can eﬀectively improve
the quality of life of elderly people and increase theproductivity of workers, both of which are very importantin an aging society. Some existing physical assistant robots
have been proven to be useful for rehabilitating stroke
patients [1], [2], for making elderly people active [3], andfor providing assistance in labor-intensive tasks [4], [5].
In addition, exoskeletons have been developed for various
specialized uses such as military applications [6].
Wearable physical assistant robots require a higher levelof safety than other robots because of their close contact
with the user’s body. The contact safety of a physicalassistant robot was studied recently [7]. Now, a new ISO
standard ISO 13482 [8], which regulates the safety standard of personal care robots, including physical assistantrobots, has been launched. According to this standard, aP

Y. Akiyama, S.Okamoto, Y. Yamada and K. Ishiguro are with the
Department of Mechanical Science and Engineering, Nagoya University, Nagoya, Aichi, Japan e-mail: akiyama-yasuhiro@mech.nagoyau.ac.jp.
Manuscript received April 19, 2005; revised December 27, 2012.

physical assistant robot should ensure suﬃcient contact
safety so that discomfort and skin injuries such as blisters
and scratches are prevented. Skin injuries occur becauseof repetitive deformation of the skin tissue and slippage
between the skin surface and the cuﬀ, which connects therobot to the user [9]. Even in cases without injuries, skindeformation sometimes causes a feeling of discomfort.
The problem of pain and discomfort has been studied in
the field of orthotics. Most of these studies evaluated the
comfort of orthoses using subjective measures [10], [11].
Although some subjects in a previous study [12] attributed
the discomfort to factors such as slip, it is diﬃcult todetermine each factor. On the other hand, several physicalparameters were measured in some studies. Simon et al.
used a pressure sensor and MRIs to evaluate the pain of
the breast brace due to the increasing normal force [13].
The pressure under the contact area of a corset-type brace
was also simulated in another study [14]. Esmaeili etal. quantified the relationship between the deformationenergy of the skin and discomfort [15]. However, although
the friction behavior around the contact surface generates
an interaction force and causes skin deformation, themechanism of this eﬀect is not clearly understood becausesuch deformation has not been measured previously. Especially, the uncertainty of the slip behavior disturbed toestimate the interaction force at the cuﬀs by measuring
the displacement at the cuﬀs [16]. Thus, the risk of skin
injuries and level of discomfort cannot be evaluated despite
the existence of data on the physical strength of humantissues, which are shown below.
Some studies attempted to measure or estimate thecontact between the cuﬀ and skin. The diﬀerence between
the knee joint mechanisms of a human and robot [17]causes a mismatch around the joint. Akiyama et al. estimated the relative displacement between the cuﬀ andhuman thigh at the cuﬀ position caused by this ergonomic
mismatch. The interaction force measured at each cuﬀ wasrelated to the estimated displacement [7]. Another study
analyzed the misalignment at the shoulder joint caused bya mechanical mismatch between a wearer and an upperlimb exoskeleton [18]. The displacement of the cuﬀ due tomisalignment at the elbow joint was also analyzed [19].
Although some of these studies measured the interaction
force at the cuﬀ, the actual skin deformation at the cuﬀ
was not measured.
Many current physical assistant robots measure only

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/TNSRE.2015.2464719, IEEE Transactions on Neural Systems and Rehabilitation Engineering
JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012

the joint torque [20], [21], force [22], and ground reaction
force [23] for achieving control and ensuring safety against
fall risks. A safety mechanism for skin injuries cannot be
devised using the joint torque, force, and limited motion
range because the stress concentration and frictional force
on the skin under the cuﬀ might be overlooked because of
uneven contact and the existence of local slippage.
Physical parameters of the human skin that aﬀect theskin deformation and slippage were analyzed in earlier
studies. For example, the viscoelasticity of human skin
was measured under various conditions [24], [25], [26].
Some of these studies used a contactor with rotationalmotion whereas others used a contactor with linear motion to apply repetitive deformation to the skin. Some
researchers [27], [28], [29] measured the friction coeﬃcientalong with other physical parameters. However, the friction coeﬃcient of human skin easily changes in response tochanges in environmental conditions such as humidity [30].
In addition, skin stretching was measured by measuring
the strain of the skin between two fixation points [25],[26]. Such skin stretching was numerically analyzed by
Tepole et al. [31]. A skin stretch model using a finite
element method was developed to represent the nonlinear
deformation of skin. Another group [32] measured not only
the stretching of the skin surface but also the deformation
occurring in the tissue under the skin. They reported thatthe range of skin deformation was less than 1 cm in theforearm. However, because of the slippage induced by asmall normal force, the value of 1 cm does not represent
the mechanical limit of the displacement between a cuﬀ
and human skin. Although these physical parameters canbe used as basic data to analyze contact behavior, actual
skin movement under an area covered by a wide object has
not been analyzed and measured so far.
Thus, the direct measurement of friction behavior, including slippage, displacement, deformation, and interaction force and moment, around the cuﬀ is required tounderstand the contact mechanism under the cuﬀ. Lenziet al. developed a sensor system that can measure the
distribution of the normal force under the cuﬀ using a
distributed tactile sensor [33]. Although this sensor can
detect the concentration of the vertical force, it cannot
measure slippage and friction, which are crucial for assessing the risk of skin injuries. Ueda et al. developed a slip
sensor which detects slip by measuring the vibration of thesmall needle which contacted to the surface [34]. Although
this method could detect the slippage, it was diﬃcult toknow the amount of the slippage. Methods to monitor
the slippage of the cuﬀ are limited because the contact
area is covered and skin is flexible. In addition, the use ofsome sensors can possibly change the surface condition of
the cuﬀ and make it diﬃcult to monitor natural contact
behavior. Therefore, a sensor that requires only a small
contact area for measurement and can measure slippage
without aﬀecting the friction behavior is required. An
optical method possibly meets this requirement because
it potentially measures slippage without contact.
In this study, we installed optical slip sensors and force2

sensors on a cuﬀ, which allows us to measure multiple
types of contact information comprising the slippage,interaction force, and relative displacement between the
cuﬀ and human skin. Such measurements and analysesof contact behavior, including the direct measurement ofslippage, can contribute to the development of a contact
model that is useful for improving contact safety regulations.
II. Method
The experiment was performed with the permission of
the institutional review board of Nagoya University.
A. Apparatus
A commercially available physical assistant robot1 wasused for the experiment without any actuation. Fig. 1
shows the configuration of the fixation and degrees of
freedom of the robot. The cuﬀ on the left thigh was
replaced with a cuﬀ in which two slip sensors and four
force sensors were inserted (Fig. 2). Two two-dimensional
imaging devices (ADNS-9500, Avago Technologies, Singapore) with lenses (ADNS-6190-002, Avago Technologies,
Singapore) were supported by springs to ensure that there
was no clearance between the sensors and the skin. Then,the surfaces of the cuﬀ and springs were fixed to four
three-axis force sensors (US06-H5, Tech Gihan Co., Ltd.,
Japan), which were placed on the base of the cuﬀ. These
force sensors were used to measure the interaction force
and moment between the cuﬀ and skin. The contact areaof the cuﬀ was 5.5 cm wide and 9.5 cm long. The structureof the modified cuﬀ is shown in Fig. 3. The cuﬀ was directly
attached to the skin to avoid slippage between clothes andskin. The surface of the cuﬀ was fixed on the lateral side of
the human thigh which was parallel to the sagittal plane of
the subject. The frequencies of measurement of the force
and slippage were 50 Hz and 1 kHz, respectively. The slip
sensor measured the position in the Cartesian system, andthe resolution of the slip sensor was 0.06 mm.
The posture of the subject and the relative motion
between the subject and the robot were measured using athree–dimensional motion capture system (MAC 3D system, Motion Analysis Corporation, CA), the outputs fromwhich were sampled at 100 Hz. Markers were attached to
the lateral side of the center of the hip, knee, and ankle
joint of the robot, and the knee and ankle joint of thesubject. The data for the hip joint of the subject were
determined from the markers that were attached to thesacral and anterior superior iliac points on the spine [35].
The posture and position of the pelvis of the subject were
calculated from the same markers, whereas those of therobot were measured using markers attached to the pelvis
link. The positions of the cuﬀ were marked on the lateralside of the robotic link. The positions covered by the robot
were determined using cluster markers.
1 Because of contractual obligations aimed at preventing the evaluation of this robot, the name, manufacturer, and details of the assist
algorithm cannot be revealed.

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
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JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 20123

causing discomfort to the subject. Before recording wasstarted, several minutes were spent on adaptation. During
adaptation, the subject attempted sit-down and stand-up
motions continuously until he became comfortable.
In the experiment, the subject repeated sit-down andstand-up motions on a 52-cm-tall chair more than 15
times. The sit-to-stand motion was selected for this experiment because it is the fundamental motion performedin daily activities and might require the assistance of aphysical assistant robot. This motion has been studied
previously, and most of its characteristics are known [36],[37].

Fig. 1. Overview of physical assistant robot

Fig. 2. Instrumented cuﬀ of left thighFig. 3. Structure of instrumented cuﬀ

B. Protocol
Ten healthy male volunteers participated in the experiment. They were between 21 and 24 years of age (averageage: 22.3 years) and between 169 and 178 cm in height(average height: 173.0 cm). After attaching the robot tothe subject, the length of the thigh and shank links was adjusted to align the subject’s hip and knee joints to those of
the robot. Then, the cuﬀs were fixed to the legs using belts.
The belts were tightened as firmly as possible without

C. Data Processing
The positions of the markers attached to the center ofjoints of the subject and robot were projected on to thesagittal plane in which the sit-to-stand motion occurred.
Then, the posture and position of the subject and robot
were defined using body links, each of which was definedas the line connecting two adjacent joint centers. Then,the relative displacement of the cuﬀ position on the skinsurface was calculated by comparing the position of the
cuﬀ and its initial position on the human thigh, which wasmarked as a particular point between the hip and knee
joints. This relative displacement includes the slippage
and deformation of the skin tissue because of the friction
behavior. Although surface slippage could be obtained
from the slip sensor, skin deformation, which includes
shear deformation and inner slippage of the tissue, wasestimated indirectly. The interaction force was obtainedby the summation of the outputs from all force sensors.
All data were filtered using a linear-phase finite-impulseresponse low-pass filter with a cutoﬀ frequency of 2 Hz
and a filter order of 30.
The geometry of the robot, cuﬀ, and human subject isshown in Fig. 4. At the thigh cuﬀ, slip sensors were arrayedin tandem in the longitudinal direction of the robotic thighlink, which was defined as the line connecting the centerof the hip and knee joints. Because the position of the cuﬀ
was measured at the center of the slip sensors, the relative
displacement at each slip sensor was calculated from therelative position and attitude of the cuﬀ as follows:()
ds1 (t) = Dt (t) + lsin(θd (t)), −l(1 − cos(θd (t)))()
ds2 (t) = Dt (t) + − lsin(θd (t)), l(1 − cos(θd (t)))(1)
where θd is the relative angle between the thigh link of therobot and the human thigh. l is the distance between theslip sensor and center of the cuﬀ. Dt , ds1 , and ds2 are therelative displacements between the cuﬀ and human thighand are defined in the X–Y coordinate system. The Y –axis
corresponds to the direction of the longitudinal axis of therobotic thigh. The original points of each coordinate wereconsidered as the position of the cuﬀ center or slip sensors.
The first term of (1) represents the translational motionof the cuﬀ, and the second term represents the rotationalmotion.

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/TNSRE.2015.2464719, IEEE Transactions on Neural Systems and Rehabilitation Engineering
JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012




θd

ds2

Dt




l

l
ds2

ds1

Dt

θd

Dt

Dt

 


l

4

ds1
l

 


Fig. 4. Coordination system around thigh cuﬀ (left: overview, right:
definitions of parameters)
TABLE I
Average duration of sit-to-stand motion for each subject
Subject
no.
1
2
3
4
5
6
7
8
9
10

Sitting
pace [s]
1.4
1.5
1.7
1.8
1.5
2.3
1.7
3.1
2.2
1.4

± SD
0.1
0.2
0.2
0.4
0.1
0.2
0.2
0.2
0.1
0.1

Standing
pace [s]
1.3
1.4
1.2
1.5
1.3
2.0
1.6
2.6
1.7
1.2

± SD
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.2
0.1
0.1

Among all the sit-to-stand motions, the first five motions of each subject were not used because of the instability of the contact condition around the cuﬀ. The next 10
motions were analyzed. Motions were separated into twophases: sitting phase and standing phase. The static phase,in which the motions were not measured, was not used forthe analysis. The angle of the knee joint of the subject wasused to separate the phases. All the separated data werenormalized by the period of each phase for comparison
between subjects.
III. Results
A. Posture of Subjects
The average durations of the sit-to-stand motions ofeach subject are listed in Table I. Despite the diﬀerences
between the motion paces of the subjects, the deviations
within the paces of a subject were small, which suggested
the stability of motions of almost all the subjects. Fig. 5
shows the change in the knee angle (θk ) for each subject.
These changes are very similar to those observed in thecase of the sit-to-stand motion of a healthy person [38],indicating that the motions were normal even when the
robot was worn.
The postures of the representative subject and robot areplotted in Fig. 6. In this experiment, the robot was locatedmarginally anterior to the aligned position of the subject
to fit the cuﬀ to the skin. However, the relative position of
the robot changed during the sit-to-stand motion becauseof the deformation and slippage of the fixation parts.
The largest displacement of the cuﬀ position between
the subject and robot was observed around the middle

Fig. 5. Averages and standard deviations of θk for each subject during
sitting (top) and standing (bottom) phases

phase of the sitting motion. During this phase, the subject’s thigh pulled the robotic thigh and the human motion
preceded the robotic motion. Then, in the late sitting
phase, the robot lowered itself under the eﬀect of gravity.
B. Displacement
The relative displacement which includes the slippage
and skin deformation at the cuﬀ is the basic parameter
representing the motion around the cuﬀ. Figs. 7–10 show
the relative displacement along the long and short axesin the sagittal plane. Although the magnitudes of the displacement diﬀer individually, especially in the sitting posture, the displacement trend is common across subjects.
As shown in Fig. 7, during the sitting phase, the relative
displacement in the X direction increases initially, and thepeak is reached at around 50% of the sitting phase. Then,the displacement decreases until the end of the sitting
motion. The range of the displacement during the sitting
phase is approximately 20–70 mm. As shown in Fig. 8,
the displacement returns to zero gradually until the endof the standing phase. The displacement in the Y direction
also increases up to the 60–80% of the sitting phase, andit slightly decreases in the late sitting phase (Fig.9). The
peak displacement along the Y direction is approximately
5–40 mm in this phase. In the standing phase as well,
the displacement in the Y direction decreases gradually(Fig. 10).
Along both axes, there are large individual diﬀerences.
The range of the relative displacement diﬀers up to a
maximum of 50 mm between the orange and yellow lines
along the short (X) axis (Fig. 7) and 25 mm between theblack and purple lines along the long (Y) axis (Fig. 9).

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
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5

Fig. 6. Postures of human and robot (left: sitting, right: standing)

Another feature of the displacement in the X direction
was the diﬀerence in the displacement between sensors.
The displacement at the position of the upper sensor wasalways larger than that at the position of the lower sensor.
This trend indicated the unevenness of the displacement
under the cuﬀ.
One of the reasons for the diﬀerence in the relative
displacement between sensors in the X direction was therotation of the human thigh link against the robotic thigh(Fig. 11). Because of the rotation, the relative displacement at the position of the upper sensor was larger thanthat at the position of the lower sensor by approximately
10 mm.
The direction of the displacement suggested that thethigh link of the robot moved downward and backwardwith respect to the subject in the sitting phase. According
to Fig. 9, the position of the robot dropped rapidly
at around 50% of the sitting phase. Then, the relative
displacement gradually returned to zero in the standing
phase. In contrast, Fig. 8 shows that the displacement in
the X direction did not converge to zero in the standing
phase. This mismatch between the end of the standing
phase and the beginning of the sitting phase implies thatthe residual displacement was canceled by the subject inthe standing posture before starting the next motion. In
addition, the standard deviation was larger along the shortaxis (X) than along the long axis (Y) because of the large
displacement of the hip fixation in the front-back direction.
C. Slippage
The amount of slippage in the X and Y directions ispresented in Figs. 12–15. For some subjects, the maximum
slippage reached several millimeters, whereas for others,
the slippage was negligible at the position of the lower slip
sensor. The slippage diﬀered between sensor positions in

Fig. 7. Relative displacement in X direction between human androbot in sitting phase (top: upper sensor, bottom: lower sensor)

addition to the subjects, phases, and axes, which suggested
that the slippage included both translational and rotational movements. The diﬀerence in the slippage between
sensors was less in the Y direction than in the X direction
given that the rotation center of the slippage was locatednear the knee joint. Because the slip sensors were aligned
to the longitudinal axis of the thigh link, the eﬀect of cuﬀ
rotation seldom aﬀected the slippage in the Y direction.
The diﬀerence in slippage in the Y direction represented

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
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6

Fig. 8. Relative displacement in X direction between human androbot in standing phase (top: upper sensor, bottom: lower sensor)

Fig. 10. Relative displacement in Y direction between human androbot in standing phase (top: upper sensor, bottom: lower sensor)

Fig. 9. Relative displacement in Y direction between human androbot in sitting phase (top: upper sensor, bottom: lower sensor)

Fig. 11. Angular diﬀerence between thigh links (top: sitting, bottom:
standing)

the skin stretching between the sensors.
In contrast, the diﬀerence in the slippage in the X
direction suggested the existence of rotation, local slip, andskin movement. Especially, during the sitting phase, theslippage measured by the upper sensor along the X-axis
was notably larger than that measured by the lower sensor

along the X-axis (Fig. 12). This trend corresponded to thetrend of the relative displacement. For one subject, theslippage was notably large, in terms of not only the amountbut also the deviation. Such instability and uniquenesssuggested that individual diﬀerences should be carefully
considered when the slip behavior is generalized.

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
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Fig. 12. Slippage in X direction between human and robot in sitting
phase (top: upper sensor, bottom: lower sensor)

7

Fig. 13. Slippage in X direction between human and robot instanding phase (top: upper sensor, bottom: lower sensor)

Although such large individuality existed, a common
trend could be found. Around the middle phase of thesitting motion, slip occurred in both the X and Y directions. The direction of slippage suggested that the robot
slid downward and backward, which corresponded to thedirection of the relative displacement. However, slippage
in the Y direction eased at the end of the sitting phase(Fig. 14) and it had no apparent relationship with thechange in the relative displacement.
D. Interaction force and moment
Interaction force and moment were generated at the
cuﬀ because of the motion of the subjects. Although theinteraction force in the compression direction, normal to
the skin surface, aﬀects the comfort of the subject, theamount of shear force is more important to evaluate therisk of skin injuries [9]. Thus, the discussion in this study
focuses on the sagittal plane. Figs. 16 and 17 show thechange in the interaction force. The interaction moment isshown in Fig. 18. In Figs. 16 and 18, data for one subject
were omitted because of an electronic fault in the sensor
used for force measurements in the X direction.
The change in the interaction force in the X direction(Fig. 16) and the interaction moment (Fig. 18) was nearlyflat with small peaks in the middle sitting phase. A few
participants, represented by green and ocher curves, were
exceptions. The trend in the Y direction diﬀered from thatin the X direction. One prominent peak was found in the
middle of both the sitting and standing phases (Fig. 16).
Figs. 16–18 also show that two among the ten subjects
were found to be very unique. The patterns of the force
and moment of the two subjects,represented by ocher

Fig. 14. Slippage in Y direction between human and robot in sitting
phase (top: upper sensor, bottom: lower sensor)

and green lines, diﬀered from those of the other subjects.
Especially, for these two subjects, the force in the X
direction and the moment drastically changed during the
motions. In addition, each subject had diﬀerent oﬀsets of
the interaction force and moment in the standing posture,
which might be attributed to the initial condition of

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
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JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012

Fig. 15. Slippage in Y direction between human and robot instanding phase (top: upper sensor, bottom: lower sensor)

fixation of the cuﬀ. When tightening the cuﬀ belts, several
degrees of initial force were inevitably applied.
IV. Discussion: Contact behavior around thecuff and risks of skin injuries
A. General Behavior
The motion and force in the contact area of the thighcuﬀ were measured using various sensors, and the relative
motion, slippage, and interaction force and moment werecompared with each other. In general, these parameterschanged in the same direction during the major part ofthe motions. This was because the kinematic mismatchchanged the trajectories of the thighs of the human androbot, and this relative displacement interacted with theforce, moment, and slippage through physical parameterssuch as the friction coeﬃcient and viscoelastic constant.
The measured slippage values in the X direction were
diﬀerent between the two slip sensors, whereas their general profiles were similar. This diﬀerence suggested theexistence of an uneven distribution of slippage beneaththe cuﬀ due to partial slip and rotation. During the sitto-stand motion, slippage was larger at the position of theupper sensor than at the position of the lower sensor in
the X direction. This tendency could be attributed to therotation of the thigh link. The change in the rotation angle
and moment also supported this tendency. Because of therelative rotation, the position that was close to the hip
joint showed large movement, which indicated a high riskof injuries.
An important inference from the comparison between
slippage and relative displacement was that a maximum

8

Fig. 16. Interaction force in X direction between human and robot
at thigh cuﬀ (top: sitting, bottom: standing)of 40 mm of the actual relative displacement, which was
calculated by subtracting slippage (Figs. 12 and 14) from
relative displacements (Figs. 7 and 9), seemed too large tobe considered as skin stretching. This gap was probably
caused by the deformation of skin, fat, and muscle tissues.
During joint bending, skin around the joint was deformed
because of the change in its shape and because of tension.
This large deformation around the joint propagated to theskin and tissue of the thigh. The flabbiness of the skin andtissue movement aﬀected the relative displacement. Thus,
the results of this experiment indicated that not only the
relative displacement and the slippage of the skin surface
but also the deformation of the skin and tissue caused bymotion changed the risk of skin injuries.
According to the changes in the interaction force(Figs. 16 and 17), the shear stress was approximately
0.4 × 104 Pa when considering the contact area. Although
this value was ten times smaller than the stress required
to generate a blister [30], the unevenness of the contact
indicated the probability of stress concentration. Thus,
safety margins should include the eﬀect of such stressconcentration.
B. Individuality
The results for all parameters such as the displacement,slippage, and interaction force and moment diﬀered drastically for each subject. Such individuality appeared especially in the sitting posture. Thus, individuality increasedin the sitting phase and converged in the standing phase.
Among all the subjects, one subject, represented by thegreen line, had a large relative displacement and slippage.

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/TNSRE.2015.2464719, IEEE Transactions on Neural Systems and Rehabilitation Engineering
JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 20129the middle of the sitting phase (Figs. 16 to 18). This
simultaneous increase in the slippage, the interaction force,and moment indicated the deformation of the skin andtissue. This potentially indicated the stacking of the skinand tissue, which meant the elevation of skin tissue, atthe edge of the cuﬀ in the middle of the sitting phase.
The stacking increases the maximum shear force during
the motion, thus increasing the risk of skin injuries. The
observation of the interaction force and skin deformation
around the edge of the cuﬀ could be used to determine
whether such phenomena occur.
In addition, the contact behavior of another subject,represented by the ocher line, was diﬀered from that of
the subject represented by the green line. The amount ofslippage represented by the ocher line was not large in the
X direction despite the interaction force and moment forthis subject being larger than those for the other subjects.
This diﬀerence might have originated from individual
diﬀerences in physical parameters such as the friction
coeﬃcient and viscoelasticity. This kind of individuality
in skin conditions is also likely to influence the risks ofskin injuries.
Fig. 17. Interaction force in Y direction between human and robot
at thigh cuﬀ (top: sitting, bottom: standing)

V. Conclusion
In this study, the contact behavior of the cuﬀ, including
the slippage at the thigh cuﬀ, was analyzed. The results
suggested that the diﬀerence between the motions of thehuman and robot interacted with the relative displacement, the interaction force and moment, and the slippageat the cuﬀ. For the first time, the measurement of theslippage enabled us to separate the relative displacement
to the deformation of the tissue and slippage of theskin. During the sit-to-stand motions, on average, several
millimeters of slippage and approximately 40 millimetersof the displacement of the cuﬀ were measured with the interaction forces and moment between the cuﬀ and humanthigh being approximately 10 N and 0.2 N·m.
Acknowledgment
This study was conducted as a part of the “Practical
Applications of Service Robot Project,” which is directedby the New Energy and Industrial Technology Development Organization (NEDO). Also, we thank the support
by JSPS KAKENHI Grant Number 26750121.
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Fig. 18. Interaction moment in X–Y plane between human and robot
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Yasuhiro Akiyama Yasuhiro Akiyama received the B.E. degree in engineering from
Tokyo Institute of Technology, Tokyo, Japan,
in 2006, and the M.S. and the Ph.D. degree
in engineering from the University of Tokyo,
Tokyo, Japan, in 2008 and 2011, respectively.
Since then, he has been a postdoctoral researcher at Nagoya University, Nagoya, Japan.
His main areas of research interests are mechanical safety, human-robot interaction, andmanned space mission.

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/TNSRE.2015.2464719, IEEE Transactions on Neural Systems and Rehabilitation Engineering
JOURNAL OF LATEX CLASS FILES, VOL. 11, NO. 4, DECEMBER 2012

Shogo Okamoto Shogo Okamoto received
MS and PhD degrees in information sciencesin 2007 and 2010, respectively, from the Graduate School of Information Sciences, Tohoku
University. Since 2010, he has been an assistant professor at the Graduate School ofEngineering, Nagoya University. His researchinterests include haptics and human-assistive
technology.

Yoji Yamada YAMADA, Yoji received a doctor degree from Tokyo Institute of Technology
in 1990. He had been with Toyota Technological Institute since 1983 and became an
associate professor in the Graduate School of
the Institute. In 2004, he joined Intelligent
Systems Research Institute of National Institute of Advanced Industrial and Science Technology (AIST). In 2009, he moved to the Department of Mechanical Science and Engineering, Graduate School of Engineering, Nagoya
Unversity as a professor. His current research interests include safety
and intelligence technology in human/ machine systems, their robotic
sensing and control.

Kenji Ishiguro Kenji Ishiguro received the
M.S. degree in engineering from Nagoya University, in 2014. Since then, he has been working for DENSO Corporation as an engineer.
Kenji Ishiguro received the B.E. and M.S.
degree in engineering from Nagoya University,
in 2012 and 2014, respectively. Since then, he
has been working for DENSO Corporation as
an engineer. His research interests are humanrobot interaction, wearable robotics, and mechanical safety.

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