2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
October 25-29, 2020, Las Vegas, NV, USA (Virtual)2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | 978-1-7281-6212-6/20/$31.00 ©2020 IEEE | DOI: 10.1109/IROS45743.2020.9341323

Dynamic Assistance for Human Balancing
with Inertia of a Wearable Robotic Appendage
Azumi Maekawa1 , Kei Kawamura2 , and Masahiko Inami3
Abstract— A reduced balance ability can lead to falls andcritical injuries. To prevent falls, humans use reaction forces
and torques generated by swinging their arms. In animals, we
can find that a similar strategy is taken using tails. Inspired bythese strategies, we propose an approach that utilizes a robotic
appendage as a human balance supporter without assistancefrom environmental contact. As a proof of concept, we developed a wearable robotic appendage that has one actuateddegree of freedom and rotates around the sagittal axis of thewearer. To validate the feasibility of our proposed approach,we conducted an evaluation experiment with human subjects.
Controlling the robotic appendage we developed improved thesubjects’ balance ability and enabled the subject to withstandup to 22.8 % larger impulse disturbances on average than in
the fixed appendage condition.

I. INTRODUCTION
Humans have an ability to dynamically maintain balance
during standing and locomotion. This ability helps us toperform tasks in our daily lives and prevents us from fallingover due to unexpected errors or external disturbances. As
our ability to maintain balance is reduced due to aging or
disability, we are more at risk of falling. Balancing ability canalso be reduced if we are concentrating on other tasks. For
example, when carrying something, we cannot fully exploit
the upper body for balancing.
To stabilize body attitude, humans use various strategies
such as foot placement adjustment and upper body motion.
The arms also play a role in stabilizing the body attitude.
For example, we use the inertia of our swinging arms torecover after tripping. Previous studies showed that the arms
contributed to control the whole body attitude by generating
reaction forces and torques [1][2]. In animals, we can observea similar strategy of using the inertia of their tail. Researchers
have revealed that a tail of cat contributes to its stability[3].
Inspired by these strategies, we propose an approachthat utilizes the inertia of wearable robotic appendages toaugment the wearer’s balance ability without the appendages
contacting with the environment. As a proof of concept,
we developed a backpack-type wearable robotic appendage
to assist the wearer in maintaining lateral balance with its
reaction force and torque. We designed the hardware and*This work was supported by JST ERATO
1 Azumi Maekaw is with the Graduate School of Engineering,
the University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo, Japanazumi@star.rcast.u-tokyo.ac.jp
2 Kei Kawamura is with the Graduate School of Arts and Sciences,
the University of Tokyo, 3-8-1, Komaba, Meguro-ku, Tokyo, Japan

wzdmriv@g.ecc.u-tokyo.ac.jp
3 Masahiko Inami is with Research Center for Advanced Scienceand Technology, the University of Tokyo, Meguro-ku Tokyo, Japaninami@star.rcast.u-tokyo.ac.jp
978-1-7281-6212-6/20/$31.00 ©2020 IEEE

Fig. 1. Appearance of the developed wearable robotic appendage. It has
one actuated DoF which rotates around the sagtital axis.

developed the physical prototype which has one actuateddegree of freedom (DoF) based on a reduced order model(Figure 1. To validate the feasibility of our proposed approach, we conducted an experiment with human subjects.
Our proposed approach also contributes to establishinga method for adding another function to supernumeraryrobotic limbs (SuperLimbs). SuperLimbs is a recently proposed approach to human augmentation that utilizes wearable
robotic arms to support the wearers in performing tasks andenhancing their ability [4]. Our approach can be implemented
in SuperLimbs to prevent falls in an emergency while
assisting the the wearer in performing a task. We believethat our approach has a potential to complement research on
SuperLimbs because it is independent of the end effector’s
shape.
This paper is organized as follows: 1) we propose a
new approach that utilizes wearable robotic appendages as abalance supporter without it contacting with the environment,2) we present the development of a backpack-type physicalprototype that has one actuated DoF, 3) we describe an
experiment with human subjects which was conducted todemonstrate that our approach contributes to augmenting
their balance ability. To the best of our knowledge, this is the

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first approach to make use of a robotic tail for human balanceand evaluate its effect with a human subject experiment.

arms to be used as manipulators when there is no need tosupport wearer’s balance.

II. RELATED WORK

III. HARDWARE DESIGN

Our work builds on methods using artificial tails in
robotics, researches on SuperLimbs, and wearable devices
for supporting wearer’s balance ability.

Body

τ

A. Tails in robotics
We can observe that animals use their tail for stabilizing
their body [3][5]. In the field of bio-inspired robotics, theeffectiveness of using actuated robotic tails to enhance thestability of mobile robots has been demonstrated. Chang-Siu
et al. presented a lizard inspired approach to reorient a mobile
robot’s body in the air [6]. In addition to this work, thebenefits of having a tail for various tasks have been demonstrated such as hopping of one-legged robot [7], locomotionof bipedal robot [8], high-speed turning [9], acceleration
and braking [10] in a wheeled robot, and recovering froma disturbance in a quadruped robot [11]. Our basic idea is to
apply these methods to the human body as one function ofa wearable robotic appendage. We can utilize benefits andfindings of these methods. However, the problem is morechallenging in our case due to the softness of the humanbody.
B. SuperLimbs
Thanks to the advancement of robotic technologies, wearable robots have been used to augment our ability beyond
physical constraints. SperLimbs is an approach that uses
wearable robotic arms that can move without restricting thewearer’s movement while supporting wearer’s task [4][12].
Parietti et al. proposed a method for stabilizing the wearer’s
body during an aircraft assembly task [13] by contactingwith the environment via SuperLimbs. In addition to thewearable extra arms approach, Gonzalez et al. proposed
wearable robotic legs and a control method to support thewearer’s task [14]. We investigate an approach to stabilize
wearer’s body attitude without contact with the environment.
Artificial tails for human have been proposed in previous
studies [15][16]. However, such research has not evaluatedtheir benefit for human balance assistance.
C. Balance support with wearable device
To augment human balance ability, several methods using
wearable mechanical devices have been investigated. Wojtara et al. proposed a method to support human balancewith a wearable reaction wheel [17]. Similarly, as an approach to using momentum exchange for human balance,
the use of control moment gyroscopes has also been investigated [18][19][20]. While these methods utilize flywheels
for human balance augmentation, we focus on an approach
using a wearable robotic arm like a robotic tail. Although
our proposed method’s workspace can be limited unlike themethods using flywheels, we can take advantage of the taillike approaches, which can provide greater torque in a shortertime [11]. Additionally, our approach allows the wearable

θ

Rod
Mass

Pin joint

ϕFig. 2. Reduced order model in coronal plane. It consists of the humanbody modeled as rigid body and mass-less rod attached a point mass.

Accurately modeling the physical interaction between ahuman body, which is soft and has high DoFs, and arigid wearable appendage is much more challenging thanmodeling the dynamics of robots that consist of only rigid
parts. As a proof of concept, we designed the robotic appendage’s hardware based on a reduced order model depicted
in Figure 2. This model has a nonlinear dynamics describedin Eq.1.
M (q)q̈ + h(q, q̇) + g(q) = τ(1)

q = [φ, θ]T(2)Where,In this paper, we focus on movement in the coronal plane.
We assumed that the robotic appendage consists of a massless rod attaching a point mass to the the wearer’s centerof mass (CoM). The appendage was assumed to have one
actuated DoF. According to previous research in robotic
tails [21][11], we can obtain a larger reaction force andtorque by increasing the moment of inertia (MoI) of therobotic appendage. MoI is quadratically dependent on length
while only linearly dependent on mass. By increasing thelength of the rod, a relatively large MoI can be obtained
while suppressing the static load on the wearer. On the other
hand, there is a trade-off that increasing the length of the rod
limits its workspace. The rod length was determined to be
0.9 m to enable the robotic appendage to obtain a large MoI
while avoiding contact with the ground during its movement.
The mass attached to the rod was selected to be 2.0 kg basedon the fact that a 10 kg load added to the pelvis is known tohave a significant effect on the wearer’s movement [22]. The
actual total weight of the hardware was about 9 kg without
cables and a battery. We selected an aluminum extrusion for
the rod because of its light weight and rigidity. For the mass’s
material, we selected brass because of its high density.
We used a brushless DC motor for the actuator. The
MAXON EC-4pole (200W) was selected for its high power
density. Then, a numerical simulation was performed todetermine the optimal gear ratio as described in [9][11].

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TABLE I
PARAMETER VALUES FOR A NUMERICAL SIMULATION
Parameter
Body Mass
Body Moment of Inertia
Tip Mass
Rod Length
Height of Center of Mass
Gear Efficiency

Motor driver

Value
60 kg
12 kgm2
2.0 kg
0.9 m
1m
0.5

Beld and pulley
BLDC motor

Battery
Wave strain gear

Backpack frame
Rod (aluminum)
Mass (brass)

Fig. 4.

The implementation of the robotic appendage prototype.

IV. EXPERIMENT
Fig. 3. The relationship among gear ratio, the time of interest, and bodyangle φ.

Table I shows physical properties used for the numericalsimulation. The human body’s MoI was determined basedon [23], and was set to be 12 kg m2 . We performed thenumerical simulation using Simulink based on the dynamics
equation 1 with the initial conditions, φ = 0, θ = 0. We
assumed that the the nominal voltage was applied to themotor during the performance. We also assumed that the
motor has a linear torque-speed curve T = µN T0 (1 − ωω0 ),where, T is the motor’s torque, µ is the gear efficiency,
N is the gear ratio, T0 is the stall torque, ω is the speed
after the gear transmission, and ω0 is the no load speed. We
determined the gear ratio based on the change of the bodyangle φ according to applied torque in a time of interest.
Figure 3 shows the result of the numerical simulation. The
optimal value of the gear ratio changes according to theoperation time. For example, the optimal value of the gear
ratio is about 230 when the time is 0.25 s, and it is about
170 when the time is 0.5 s. Recovering from the falling
requires a quicker response. Therefore, we determined the
reduction ratio to be about 230. We used a timing belt anda pulley mechanism with a strain wave gear for its lightweight and high load capacity. Considering commerciallyavailable options and the gear property, we selected the gear
combination with an actual ratio of 230.4. The motor wascontrolled by a Windows 10 PC with an Intel Core i98950HK 2.90G Hz CPU through the motor driver, EPOS4
70/15, from MAXON. Figure 4 shows an overview of the
hardware implementation. We used 6 cells LiPo battery as
the power supply for the motor in the following experiment.

To validate the feasibility of our proposed approach, we
designed an experiment with human subjects. We aimed
to evaluate the balance support capacity of the developed
appendage in respose to impulse disturbances in the lateral
direction. All experiments were carried out with the permission from the Local Ethics Research Committee at the
University of Tokyo, Japan.
A. Setup
Figure 5 (a) shows the experimental setup. We developed
an apparatus for disturbance generation. The apparatus consists of a brushless DC motor, MAXON EC 90 flat (260W),
and a belt-pulleys mechanism. Its reduction ratio is 2.8.
This apparatus can generate disturbances with its actuatorby pulling a rope attached to the subject. The magnitude ofthe disturbance was calibrated by linear regression based on
samples pre-measured with a force sensor. As a result of theregression, we were able to predict the output magnitude ofthe disturbance with the coefficient of determination R2 =0.98 within the torque range used in this study.
We set the apparatus to apply a specified force to therope for a short period to emulate an impulse disturbance(Figure 5 (c) shows an example of this disturbance). To
prevent the rope’s slack, we set the apparatus to pull therope with a constant weak force in the initial state. We fixed
the apparatus at 0.88 m height from the ground. We also
developed a foot sensor for the appendage control (Figure 6).
The details of how sensor information was used is describedin the control law section.
B. Subjects
We recruited six subjects (6 male, age: mean=23.5 years
old and SD=2.2, height: mean=1.72 m and SD=0.03, weight:
mean=60.6 kg and SD=6.2).

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ignore the effect of swinging subjects’ arms, we instructed
the subjects to cross their arms in all trials. We also instructed
the subjects to maintain the center of pressure (CoP) of thefeet as centered as possible and to withstand the disturbancewithout moving their feet. Before the start of each trial, acalibration step was performed to calculate xinit . Before
starting the experiment, we performed several trials under
the appendage controlled condition to familiarize the subjects
with the behavior of the system.
D. Control law
We designed a feedback control law for the robotic
appendage according to the position of the subject’s CoP.
Assuming that the motor torque is proportional to the current,
we controlled the torque τ as follows:kT k(x − xinit ) (x − xinit > )τ=(3)0(otherwise)

Fig. 5. (a) The experimental setup. This includes a foot sensor and (b) theapparatus which pulls the rope attached to the subject with a brushless DC
motor at a defined peak force. (c) An example of a generated disturbancemeasured by a force sensor.

No participants had any physical disabilities.
C. Procedure
We conducted the experiment with two conditions: 1)
the controlled condition and 2) the fixed condition. In thecontrolled condition, the appendage was controlled according
to a control law described in the next section. In the fixed
condition, the appendage was fixed to the initial position
during experimental trials. The experiment consists of ten
sessions with the controlled condition and ten sessions withthe fixed condition. Each session was carried out alternatively. In each session, we increased the magnitude of the
disturbance by 10 N per trial and examined whether the
subjects’ foot left the ground. If the subject’s any of thesubject’s feet did not leave the ground, we increased the
disturbance’s magnitude. If the subjects’ foot left the ground,a disturbance of the same magnitude as in the last trial wasprovided. If the subjects’ foot left consecutively in two trials,
the disturbance’s magnitude at that time was recorded as a
threshold value, and the session was terminated. To alleviate
fatigue, the subjects were allowed to take a break between
each session.
We instructed the subjects wearing the appendage to standupright and fixed it to the subject with fastening belts
attached to the backpack frame. We asked the subjects toplace the left foot on the foot sensor with the feet aligned.
We attached the rope to the subjects’ hip with one loop. To

The robotic appendage was controlled proportionally according to the position of subject’s CoP x estimated by pressure
sensors installed under the subject’s left foot (Figure 6). We
used FSR-408 force sensing resistors as pressure sensors.
We developed the control system according to equation 3
with this sensing setup. At the beginning of each trial, theposition of the CoP in the steady state was measured, andwe defined it as xinit . kT is the torque constant of the
motor. This parameter is obtained from the motor’s data
sheet, and it is 13.7 mNm/A. The proportional gain k wasdetermined empirically in a preliminary experiment. We
defined  to prevent unnecessary movement of the robotic
appendage caused by the body sway in a stable state. k and were 2700 A/mm and 1.2 mm respectively. The appendage
position θ was set to the initial position (θ = 0, in Figure 2)
in each trial. We also defined the limited range of the rotation,
and we set it to 0 < θ < 56 π. In this experiment, we ignored
the case where the subject’s CoP moved to the right side fromthe initial position, in other words, when x − xinit < 0.
Back viewL

Foot
P1, P2 : Pressure sensor
Fig. 6. Diagram of the foot sensor for measuring the CoP. We estimated the1
L. p1 and p2 are values of P1 and P2 respectively.
CoP as x = (p p+p
1
2)
L is the distance between two sensors and it was 85 mm.

V. RESULTS
We collected the threshold values in 20 sessions per
subject and compared the controlled condition with the fixed
condition. Figure 8 depicts the collected results for eachsubject. The statistical significance (α) was determined ata one-sided p-value of ≤ 0.05. The threshold values weresignificantly different according to the conditions within all

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Condition 1: appendage controlled

Condition 2: appendage fixed

t = 0.3

t = 0.6

t = 0.9t = 1.2

Fig. 7. Snapshots taken by a standard camera at 30 fps (The time at which the rope started to move was set to t = 0). In condition 1, the appendage wascontrolled with a feedback loop according to the foot sensor value. In condition 2, the appendage was fixed to the initial position.

subjects (Wilcoxon rank sum test). On average, the appendage control increased the threshold value of the subjects
by 11.9 % compared to the case where it was fixed. In thesubject with the largest increase in the threshold value, theincrease rate of the mean was 22.8 %. Converted to the peakvalue of the disturbance magnitude, this increase was by 50 N
(from 219 N to 269 N). On the other hand, the lowest increase
rate was 8.0 % (from 286 N to 309 N).
Figure 7 shows snapshots of the experiment in eachcondition. We found that the appendage could react to the
disturbance to stabilize the subject attitude. We concluded
that our proposed approach is beneficial for stabilizing thewearer’s attitude against a disturbance.

*

**

**

A. Discussion***** p < 0.05, ** p < 0.01**

Fig. 8. Comparison of the threshold value in each subject with and without
control of the appendage.

Although the result shows that our proposed approach enhances the wearer’s balance ability, we found several issues
where improvements could be made. During the experiment,
we observed that the appendage reached the defined limit
angle and stopped suddenly several times. We found that thesudden stop caused a negative effect on the subject’s balanceand could lead to the loss of the balance. We identified thatthe system would be improved by optimizing its trajectory
including acceleration and deceleration.Another issue is how
to attach the appendage to the human body. While the current
prototype is fixed to the body by tightening the belt, a
little play exists between the body and the backpack frame.
This problem can be resolved by optimizing the parts to be
attached to the human body or using ergonomic shapes. We
also found that the appendage started moving a little after the
disturbance provided. We concluded that the time it took for aprovided disturbance effect to be reflected on the sensor was
one cause of this delay. Introducing a sensor fusion approach
using another sensor, such as an accelerometer, can suppress
this delay.

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As a first step, we adopted the linear control law, anddid not take into account individual physical properties andstrategies. We concluded that our proposed approach could
be used more efficiently by applying non-linear controls
or adopting machine learning approaches. In addition, ourobservation suggested that the foot sensor could be used as ancommunication interface for the wearer. Although we aimed
to control the appendage independently of the wearer’s will,
we found that the wearer could control the appendage at willby changing the pressure distribution of the foot sole. By
inferring the wearer’s intention from the pressure pattern of
the feet sole with a wearable sensor module, the autonomous
control and the wearer’s control could be switched and used
at will.
VI. CONCLUSIONS AND FUTURE WORK
We proposed a novel approach that utilizes a wearable
robotic appendage as a balance support device without it
contacting with the environment. As a proof of concept, wedeveloped a prototype that has one actuated DoF and rotatesaround the sagittal axis of the wearer. To validate the feasibility of our proposed approach, we conducted an experimentwith human subjects. We designed the control method to
respond to the CoP of the subjects’ foot sole. We provided
impulse disturbances to the subjects and compared the conditions with and without the robotic appendage control. The
experimental results demonstrated the effectiveness of our
proposed approach. It was shown that, by controlling theappendage, the stability of the subjects’ body was improved.
In this research, the developed hardware has only one DoF
to simplify the problem and control. Therefore, it can only
deal with disturbances in the coronal plane and the effective
working range is limited. Additional DoFs will be a promising avenue to improve our proposed approach and enable theappendage to also function as a manipulator, as is proposedin research on SuperLimbs. We would like to investigate
advanced control methods for the appendage that has such
multiple DoFs. Furthermore, while we focused on balance
assistance in the standing situation in this experiment, we
would explore the interactions during cyclic motion of thewearer, such as during locomotion. We believe this work can
be a baseline for further investigation and inspire other works
on wearable robotics.
ACKNOWLEDGMENT
We would like to thank Zendai Kashino for useful comments and proofreading. We would likt to thank Sohei Wakisaka for advice about the experimental design. This project
was supported by JST ERATO Grant Number JPMJER1701,
Japan.
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