applied
sciences

Article
A Challenge: Support of Standing Balance in
Assistive Robotic Devices
V ittorio Lippi 1 , * and Thomas Mergner 2
1 Fachgebiet Regelungssysteme, T echnische Universität Berlin, Einsteinufer 17, D-10587 Berlin, Germany
2 Neurological Clinic at the University of Fr eiburg, Br eisacher Str . 64, 79106 Freibur g im Brei sgau, Germany;
thomas.mergner@uniklinik-fr eiburg.de
* Correspondence: [email protected]
Received: 16 June 2020; Accepted: 25 July 2020; Published: 29 July 2020
     
  

Abstract:
Neur ological patients using a powered lower -body exoskeleton for rehabilitation of standing
and walking skills in an upright body pose face the safety challenge of postural instability and
fall. Curr ent resear ch, ther efore, develops exoskeletons with self-balancing functions. This study
suggests basing the exoskeleton’s stabilization of standing postur e on a human-derived postural
contr ol mechanism. A corr esponding control system has pr eviously been successfully tested with
specific balancing tasks in humanoid rob ots. Here, we pr ovide a short introduction into the contr ol
method and, using a lightweight robot, pr esent as a test of the balancing an experimental shift in the
body weight distribution (as if, e.g., a human exoskeleton user was raising an arm or leaning the
upper body or lifting an external weight). An overview of other specific balancing tests previously
alr eady investigated in humans and humanoids is also briefly mentioned. Overall, the tests will allow
the quantification of the capabilities of self-balancing exoskeletons developed for patients with partial
paralysis of lower body sensorimotor functions.
Keywords:
exoskeleton; standing balancing; human-inspir ed balancing control method; tests of
balancing abilities
1. Introduction
Consider a patient with stroke or incomplete spinal cor d injury (iSCI) who uses a powered
exoskeleton as an assistive device for the training of residual lower body sensorimotor skills
(with additional beneficial e ff ects of bringing the body upright for blood pr essure r egulation and bowel
functions; overview in [
1
–
3
]). The task of the exoskeleton here is to sense leg and hip movements
and to enhance or pr oduce the joint forces such that the patient can perform the desir ed movements
such as hip, knee and ankle flexion and extension. W ith standing and on-gr ound walking, balancing
is then typically performed using hand–arm crutches that ar e used in a “quadruped”-like standing
and walking style, i.e., with the upper body leaning forwar d and supported. This is di ff erent fr om the
normal bipedal standing and walking style originally learned and used. Furthermore, it constrains the
usage of arms and hands, and it is very exhausting [ 4 – 6 ].
Physiologically , the deficits typically a ff ect the two main constituents of sensorimotor contr ol, i.e.,
the “pr oactive” part that provides voluntary action and the “r eactive” (often reflexive) part that contr ols
the postural stability and body balancing in r esponse to external and self-produced disturbances
(e.g., fr om the e ff ects of gravity and intersegmental reaction for ces; compar e [
4
]). Curr ent resear ch
and developments aim ther efore to extend the functionality of the exoskeleton such that it pr ovides
also postur e control [
7
–
10
] in addition to the contr ol of voluntary movements. Stability , fall-safe control,
and balance r ecovery are also a curr ent topic in exoskeleton resear ch [ 11 – 16 ].
Appl. Sci. 2020 , 10 , 5240; doi:10.3390 / app10155240 www .mdpi.com / journal / applsci

Appl. Sci. 2020 , 10 , 5240 2 of 14
A major aim in this r esearch field is to pr ovide the control tor que adjustments in the ankle, knee and
hip joints of the exoskeleton r equired for voluntary action and the standing balance (unconsider ed
r emain here tar geted foot placements as an additional constituent of maintaining walking balance).
It is important that the sensorimotor contr ol of the exoskeleton corresponds to that intended and
anticipated by the patient. This concerns the sensory information on joint kinematics and kinetics and
foot sole pr essure as well as vestibular and visual derived estimates of the kinematics of the body COM
(center of mass) and the corresponding ego-motion per ception in space. W ith major discrepancies
between expected and actual sensorimotor signals, considerable extra training would be requir ed for
the patients, and patients’ compliance may su ff er . This paper , therefor e, suggests using a method for
the sensorimotor contr ol of the exoskeleton that is human-derived and therefor e complies by and large
to human habits and expectations.
This human-derived sensorimotor contr oller with proactive and r eactive (self-balancing) properties
is described in the following in abbr eviated form. It has pr eviously already been implemented into
humanoid r obots for proof of principle (showing, for example, that it tolerates ‘r eal world’ noise and
inaccuracies and copes with external and self-pr oduced disturbances). Descriptions of this ‘disturbance
estimation and compensation’ (DEC) controller , can be found in [
7
,
15
–
17
]. Her e we present it in
abbr eviated form and test its functionality using a novel experimental paradigm.
2. Functionality of Exoskeleton
T argeted exoskeleton device . The focus of this paper is on enhancing the standing balance of the
patient-exoskeleton system with external disturbances and with self-produced disturbances that
may arise along with active body movements. Disturbance pr ediction—relevant for self-pr oduced
disturbances in humans in view of considerable feedback time delays (see [
7
])—as well as mechanisms
specific for walking such as foot placement contr ol, are not consider ed here.
Patient-exoskeleton integration . The consider ed exoskeleton type (Figure 1 ) is equipped in the body
sagittal plane with hinge joint actuators at the level of the hip, knee and ankle joints. The patient is
connected to it using strap fixations for pelvis (with abdomen), thighs, shanks and feet. The bilateral
sets of actuators ar e controlled using angle and tor que sensors. In the frontal plane, the exoskeleton
is passively stable, so that the balancing task during stance is restricted to the sagittal body plane.
The anthr opomorphic structure and actuation design of the pr oposed exoskeleton is similar to the one
of the r obotic exoskeleton Exo-H3 by CSIC / T echnaid [
13
] or the one pr esented in [
18
]. W e acknowledge
that this is just one of the possible solutions because, typically , exoskeletons have only hip and knee
motors and no lateral DoFs [
2
] and some wearable robots do not have an anthr opomorphic design,
e.g., [ 19 ].

Appl. Sci. 2020 , 10 , 5240 3 of 14
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 3 of 16

Figure 1 . Sche matic representation of the suggest ed power e d lower-body exoskele ton. M H , M K and
M A , motorized actuators for hip, knee and an kle joints , respe c tive ly . The str a p from back s u pport over
the abd o men red u c e s trunk bend i n g i n the lower vertebral c o l u mn, whereas trunk bend i n g i n the hi p
joints is es senti a lly u n restrained. Arm s u s ed for lift i ng objec t s, etc . not sho w n for s i m p lic i t y . F u rther
detail s in Tex t .
With both sensing and exec uting the pro a ctive movements a n d the ba la nc in g, t h e fol l owin g t w o
requirements need to be fulfilled : (1) Fix a tion of so me form of arti fi cia l vesti b ul a r system to the upper
exoske let o n l i nk (comp a re [1 5] ); ( 2 ) Ev al uat i on and control of th e COM of bo th, exoskeleton and
pa ti ent; ( 3 ) Rel a ti ng the C O M to the common ba se of support, giv e n by using common footwea r for
pa ti ent a n d exoskeleton (f ixi n g ea ch f o ot of the p a ti ent to a shoe-li k e f ootpla t e of the exoskel e ton) .
Four pre s s u r e senso r s und e r the exos keleton’s sole s o f e a ch foot ar e assume d to allow, togeth er with
joi n t a n gl e a n d torq ue sensors, a n esti m a ti on of th e total we ight of the COM (exo skeleton and patient)
a n d i t s spa t ial distri buti on on the ground. The a ttemp ts of active m o vement of the user are sen s ed to
comma nd the exoskeleton’s movements. Given tha t se nsory perception of interlink coo r din a tion is
i m pa ired i n t h e pa ti ents, i t i s up to the exoskeleton to a l so deal wi t h thi s i n f o rm a t i o n al ong wi th the
motor actions requir ed for balancing an d proactive m o vements.
Human insp ired control of b a lancing . The noti on tha t huma n bal a nc ing skil ls sti ll represent th e
‘golden standard’ for the b a lancin g o f h u mano id rob o ts ([ 20– 22 ]) appl i e s si mi la rl y to the exoskel e ton
in t h is pape r . H u man ba l a ncin g of st a n ce in t h e ab sence o f vi si on rel i es for e most on t h e ‘ankle
strategy’ [13]. The balanc in g in the ank l e joints al most cont inuou s ly compensat e s for t h e gr avit at iona l
t o r q u e o f t h e b o d y C O M , w h i c h a r i s e s d u r i n g s p on taneous, self-produced or external stim ulus-
evoked body sway ma inly in t h e s a g i t t a l body pl an e. Upon very rapid a n d la rge perturba tions, the
ankl e st r a t e g y m a y b e acc o m p anied b y t r ans i ent hip and knee b e nding t h at lo wers t h e C O M [ 2 3 ] .
This hip involvement is no t t o be confounded wit h the ‘hip strateg y ’ [24] wh ere humans exert rapid
hip bending to generate fo ot–groun d sh ear forces f o r ba la nci n g the body i n the sagi tta l pla n e—this
occurs typi cal l y when the a n kl e stra tegy tends to fail, e . g., wh en stan ding with the feet on a
perpendicular narrow be am (a situ atio n not considered here). Furt hermore, unconsidered remain
support man e uvers by ho ldin g with the hands, fu rt hermore an improvement of balanc ing in the
presence o f visual orientation c u es, which owes main ly to an improveme n t of the r a ther noisy

Figure 1.
Schematic repr esentation of the suggested power ed lower-body exoskeleton. M
H
, M
K
and
M
A
, motorized actuators for hip, knee and ankle joints, respectively . The strap from back support
over the abdomen r educes trunk bending in the lower vertebral column, whereas tr unk bending in
the hip joints is essentially unrestrained. Arms used for lifting objects, etc. not shown for simplicity .
Further details in T ext.
W ith both sensing and executing the pr oactive movements and the balancing, the following two
r equirements need to be fulfilled: (1) Fixation of some form of artificial vestibular system to the upper
exoskeleton link (compar e [
15
]); (2) Evaluation and control of the COM of both, exoskeleton and
patient; (3) Relating the COM to the common base of support, given by using common footwear for
patient and exoskeleton (fixing each foot of the patient to a shoe-like footplate of the exoskeleton).
Four pr essure sensors under the exoskeleton’s soles of each foot ar e assumed to allow , together with
joint angle and tor que sensors, an estimation of the total weight of the COM (exoskeleton and patient)
and its spatial distribution on the gr ound. The attempts of active movement of the user are sensed to
command the exoskeleton’s movements. Given that sensory perception of interlink coor dination is
impair ed in the patients, it is up to the exoskeleton to also deal with this information along with the
motor actions r equired for balancing and pr oactive movements.
Human inspir ed control of balancing . The notion that human balancing skills still r epresent the
‘golden standar d’ for the balancing of humanoid r obots ([
20
–
22
]) applies similarly to the exoskeleton
in this paper . Human balancing of stance in the absence of vision r elies foremost on the ‘ankle
strategy’ [
13
]. The balancing in the ankle joints almost continuously compensates for the gravitational
tor que of the body COM, which arises during spontaneous, self-produced or external stimulus-evoked
body sway mainly in the sagittal body plane. Upon very rapid and lar ge perturbations, the ankle
strategy may be accompanied by transient hip and knee bending that lowers the COM [
23
]. This hip
involvement is not to be confounded with the ‘hip strategy’ [
24
] wher e humans exert rapid hip bending
to generate foot–gr ound shear forces for balancing the body in the sagittal plane—this occurs typically
when the ankle strategy tends to fail, e.g., when standing with the feet on a perpendicular narrow beam
(a situation not consider ed here). Furthermore, unconsider ed remain support maneuvers by holding
with the hands, furthermor e an improvement of balancing in the pr esence of visual orientation cues,
which owes mainly to an impr ovement of the rather noisy vestibular information [
25
] and a top–down
alignment, starting with head and trunk, with r espect to the perceived vertical of the visual scene [
26
].

Appl. Sci. 2020 , 10 , 5240 4 of 14
A humanoid r obot is used in this paper to approximate the user–exoskeleton combination. W e used the
r obot Lucy (Figure 2 ) for our experiment, which uses the human-derived sensorimotor control for
balancing to be described below . The robot Lucy was developed as a platform to study human inspir ed
postur e control and balance. Specifically , it was previously used to test postur e control in the fr ontal
plane [
25
] or in both the fr ontal and the sagittal plane [
22
,
26
,
27
]. In this work, the mass distribution
of the r obot will be altered without updating the contr ol parameters by means of an additional
weight fixed on the pelvis (see Figur e 2 A). This is meant as a preliminary test of the versatility of the
contr ol system in face of forces due to the interaction with the external environment and with the
user . Each degree of fr eedom of the r obot is equipped with an encoder (joint angle ‘proprioception’)
and a torque sensor . Fixed to the robot’s upper body (head–arm–trunk, HA T , segment, her e a one
link rigid system), a bio-inspir ed vestibular system [
17
] estimates HA T (head, arms, trunk) angular
velocity and angle with r espect to the gravitational vertical and head linear acceleration for use of the
contr ol in the lower back, hip, knee and ankle joints. The description of the upper body as a unique
segment is a r easonable approximation for computing the CoM sway [
15
]. The joints ar e actuated by
impedance-contr olled actuators using electric motors. Lucy’s anthropometrics measur es are given in
T able 1 . In the following, we first describe the human-derived sensorimotor control system, which is
used in Lucy and which we suggest for futur e use in exoskeletons, before r eporting a novel test of
the contr ol.
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 4 of 16

v e st ib ul ar in f o rm at ion [ 2 5 ] and a t o p – do wn a l i g nm en t , st art i ng w i t h hea d and t r unk, wit h res p ect to
the perceived vertical o f th e visual scene [26].
A h u manoid robot is used in th is p a p er to a ppr oxima t e the user –e xoskeleton combina t ion. W e used t h e
robot Lucy (F igur e 2) for o u r experim e n t , which uses the human-derived sensorimotor control for
ba la ncing to be described below. The robot Lucy was develop e d as a p l atform to stud y human
inspir ed post ure cont ro l a n d ba lanc e. S p ecif ica l l y , it was previo us ly use d t o t e s t post ure con t rol i n
the f r ontal pla n e [2 5] or i n both the f r onta l a n d the sa gi tta l pla n e [2 2,26 ,27 ] . In thi s work, the mass
di stri b u ti on of the robot wi ll be a l tered wi thout upda ti ng the control p a ra meters by mea n s of a n
add i t i ona l w e ight fix e d o n t h e pelvis (see F i g u re 2 A ). Thi s i s meant as a pre limin ar y t e st of t h e
versat i lit y o f t h e cont rol sy s t em in face o f forces due to the i n tera cti o n wi th the external envi ronment
and w i th the user. Each d e gree of fre e dom of the r o bot is equip p ed with an encoder (join t ang l e
‘proprioception’) a n d a torq ue sensor. Fixed to the robot’s upper body (hea d– arm– trunk, HAT,
segment, her e a on e lin k r i gid system ), a b i o-inspir e d vest ibular system [17] e s timates HAT (head,
arm s , t r un k) angu l a r v e loc i t y and angl e wit h resp ect t o t h e gr av it at iona l v e rt ic al and hea d l i nea r
accelerat i on for use o f the c o ntrol in the lower bac k , hip, knee and ankle joints. T h e desc riptio n of the
up p e r b o dy a s a uni q u e s e gm ent is a r e ason ab le ap p r oxim at ion fo r com p ut ing t h e C o M swa y [ 1 5] .
The joints are actuated by imped a nce-controll e d act u at ors us ing e l ect r ic m o t o rs. Lucy’ s
ant h rop o m e t r ics m e as ure s are giv e n in Tab l e 1. In the f o ll owi n g, we f i rst descri b e the huma n-deri ved
sensor imot or cont rol s y st em, wh ich is u s ed in L u cy and whic h we s u gge s t for f u t u re use in
exoske let o ns, before report ing a nove l t e st of t h e cont r o l.

Figure 2 . Humanoid robot Lucy. ( A ) The humanoid. Notice the weight fixed to the pelv is; ( B ) d e t a il
of the actuatio n system in the foot : (1) DC m o tor, (2 ) spindle, (3) encoder , (4) force sensor ; the same
system is impl emented for al l the degree s of freedom; ( C ) schema of the 14 degrees o f freedom
implemented i n the robot. Al l de grees of free dom are actuat ed.
Table 1. Robot anthropometri cs.
Body m a ss 15.30 kg
Upper body ma ss
(inc lud i ng pe lvis ) 9. 50 kg
Thighs m a s s 2. 80 kg
Shank s m a ss 3. 00 kg
Tot a l he ight ( f rom ankl e
joints) 1. 52 m

Figure 2.
Humanoid r obot Lucy . (
A
) The humanoid. Notice the weight fixed to the pelvis; (
B
) detail of
the actuation system in the foot: (1) DC motor , (2) spindle, (3) encoder , (4) for ce sensor; the same system
is implemented for all the degr ees of freedom; (
C
) schema of the 14 degr ees of freedom implemented in
the robot. All degrees of fr eedom are actuated.
T able 1. Robot anthr opometrics.
Body mass 15.30 kg
Upper body mass (including pelvis) 9.50 kg
Thighs mass 2.80 kg
Shanks mass 3.00 kg
T otal height (from ankle joints) 1.52 m
Body COM height (from ankle joints) 0.68 m
Shank COM height 0.32 m
Thigh COM height 0.31 m

Appl. Sci. 2020 , 10 , 5240 5 of 14
3. Human Derived Self-Balancing Control
V arious self-balancing methodologies have been suggested for humanoid r obots, often with
r eference to human balancing [
19
]. They lend themselves as inspiration for the self-balancing mechanism
of the exoskeleton. Of particular inter est is a robotics balancing methodology developed on the basis
of human experiments because it may satisfy human habits and expectations. The human-derived
balancing contr oller , described below in abbr eviated form, has successfully been implemented into
humanoid r obots for proof of principle (showing, e.g., that it tolerates ‘r eal world’ noise and inaccuracies
as well as external and self-pr oduced disturbances). A detailed description of the control, called DEC
( d isturbance e stimation and c ompensation) model, can be found in [ 7 , 17 , 28 ].
3.1. The Human-Derived Disturbance Estimation and Compensation (DEC) Contr ol
Each DOF of the r obotic device is equipped with a DEC module, which:
(a)
Pr ovides multisensory disturbances estimates of the four basic physical joint impacts : (i) r otation
and (ii) translation of supporting links as well as (iii) contact for ces and (iv) field forces a ff ecting
supported links;
(b)
Compensates the impacts using long-latency feedback (r eflex) loops in a servo control, with
(c)
Low loop gain that tolerates biologic feedback time delays and makes the actuation compliant and
the ener gy consumption low .
For the cardinal body planes (her e relevant only sagittal), the modules exchange disturbance
information in terms of coordinate transformations, a concept originally developed on the basis of
human psychophysical experiments of motion per ception in [
29
] and later used in the DEC model [
7
,
25
].
In humans, the long latency reflexes ar e known to pass thr ough the cerebral cortex, and by this can be
voluntarily shaped to the behavioral demands. Such a shaping has not yet been r ealized for the DEC
model in our computer and r obot simulations. There, the network of DEC modules autonomously
pr oduces compensation of external (reflexive) and self-pr oduced (predicted) disturbances as well as
interlink coor dination (see [ 28 ]).
3.2. Human-Inspir ed Control System in Robotic Platform
Each degr ee of freedom is equipped with an encoder (joint angle pr oprioception) and a torque
sensor . Fixed to the r obot’s upper body (head–arm–trunk, HA T) segment, a bio-inspired vestibular
system [
17
] estimates HA T angular velocity and angle with respect to the gravitational vertical and
linear head acceleration for use of the hip, knee and ankle joint contr ols (Figure 3 B). The joints ar e
actuated by impedance-contr olled actuators using electric motors.
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 6 of 16

Figure 3. (A) S c hem a tic m o de l of di stu r bance est i m a tion a n d com p ensati on (DEC ) contr o l m o du le .
The su bsy s t e m labe led “Cont r olled sy s t em ” represents the mechanics of the body; ( B ) network of
interconnected DEC control m o du les. The sy m b ol α represents the angle in space of the upper body
( α us ), pe lvis ( α ps ), body center of m a ss ( α bs ), thigh ( α ts ), shank ( α ss ) and of the fo ot support base ( α fs ).
Each m o du le c o ntrols the CoM of all bo dy s e g m e nt s above the indicat e d j o int (ex a m p le: body center
of mass, CoM , above ankle jo ints).
The DEC control is use d in a mod u lar fo rm here for a t riple inve rt ed pendu l um (TIP) scena ri o ,
in which e a ch modul e i s co nt rollin g a Do F ( s ee [3 0, 3 1 ] for det a i l s ) . T h e fo ur mod u les shown in Fig u re
3 B a r e controll i n g the a n kl e joi n ts, the knee joi n ts a n d t h e hi p joi n ts, a n d the pel v is joi n t, respecti vel y ,
while all oth e r degr ees of free dom are actuated as simu lated sp ring d a mper s. In this wo rk we
implemented the compensation o f support surface tilt, gr avity and external t o rqu e (e .g., c o ntact
force), wh ile the compensation o f the support su rface tr anslat io n remained unconsidered in the
experiment p e rformed . Th e estim a tion of the d i st urba nces to be compensa ted is described in the
following paragraphs of this sectio n. In general, they are based on th e k i nematics variable s me asured
by the sensors (i.e., orientation of the upper body , jo int ang l es an d the respect i ve der i vativ e s). In
order to specif y the task of sta n di ng upright i n te rms of t a rget positi on, the robot i s comm a n ded to
maint a in an u p right st anc e wit h a ll t h e se gment s vert ic al wh il e ba la ncing. Th is is possibl e du e t o t h e
fact that bod y pose is exp r essed in ter m s of s e gm ents’ swa y a n d then there is no si ngula r ity i n the
control.
Suppor t surfac e tilt . Thi s t ilt is est i mat e d b y combining vest ibul ar an d propriocept i ve si gna l s . The
vest ibul ar s i g n al is imp l e m ent e d usin g t h e bio-insp ired model pr esented in [15,32]. P r oprio c eptive
sign als are pr oduced b y the encoder s (Figure 2B ). The sensor fusion is implement e d by summing the
ti l t a n d rot a tion vel o ci ty computed by the propri ocepti ve system wi th the joi n t a n gles provided by
the proprioc eptive syste m , as shown in (1). Mor e details o f th is approach t o sensor fu sion are
provi d ed i n [3 3–3 5] .

Figure 3. Cont.

Appl. Sci. 2020 , 10 , 5240 6 of 14
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 6 of 16

Figure 3. (A) S c hem a tic m o de l of di stu r bance est i m a tion a n d com p ensati on (DEC ) contr o l m o du le .
The su bsy s t e m labe led “Cont r olled sy s t em ” represents the mechanics of the body; ( B ) network of
interconnected DEC control m o du les. The sy m b ol α represents the angle in space of the upper body
( α us ), pe lvis ( α ps ), body center of m a ss ( α bs ), thigh ( α ts ), shank ( α ss ) and of the fo ot support base ( α fs ).
Each m o du le c o ntrols the CoM of all bo dy s e g m e nt s above the indicat e d j o int (ex a m p le: body center
of mass, CoM , above ankle jo ints).
The DEC control is use d in a mod u lar fo rm here for a t riple inve rt ed pendu l um (TIP) scena ri o ,
in which e a ch modul e i s co nt rollin g a Do F ( s ee [3 0, 3 1 ] for det a i l s ) . T h e fo ur mod u les shown in Fig u re
3 B a r e controll i n g the a n kl e joi n ts, the knee joi n ts a n d t h e hi p joi n ts, a n d the pel v is joi n t, respecti vel y ,
while all oth e r degr ees of free dom are actuated as simu lated sp ring d a mper s. In this wo rk we
implemented the compensation o f support surface tilt, gr avity and external t o rqu e (e .g., c o ntact
force), wh ile the compensation o f the support su rface tr anslat io n remained unconsidered in the
experiment p e rformed . Th e estim a tion of the d i st urba nces to be compensa ted is described in the
following paragraphs of this sectio n. In general, they are based on th e k i nematics variable s me asured
by the sensors (i.e., orientation of the upper body , jo int ang l es an d the respect i ve der i vativ e s). In
order to specif y the task of sta n di ng upright i n te rms of t a rget positi on, the robot i s comm a n ded to
maint a in an u p right st anc e wit h a ll t h e se gment s vert ic al wh il e ba la ncing. Th is is possibl e du e t o t h e
fact that bod y pose is exp r essed in ter m s of s e gm ents’ swa y a n d then there is no si ngula r ity i n the
control.
Suppor t surfac e tilt . Thi s t ilt is est i mat e d b y combining vest ibul ar an d propriocept i ve si gna l s . The
vest ibul ar s i g n al is imp l e m ent e d usin g t h e bio-insp ired model pr esented in [15,32]. P r oprio c eptive
sign als are pr oduced b y the encoder s (Figure 2B ). The sensor fusion is implement e d by summing the
ti l t a n d rot a tion vel o ci ty computed by the propri ocepti ve system wi th the joi n t a n gles provided by
the proprioc eptive syste m , as shown in (1). Mor e details o f th is approach t o sensor fu sion are
provi d ed i n [3 3–3 5] .

Figure 3.
(
A
) Schematic model of disturbance estimation and compensation (DEC) contr ol module.
The subsystem labeled “Controlled system” r epresents the mechanics of the body; (
B
) network of
interconnected DEC contr ol modules. The symbol
α
repr esents the angle in space of the upper body
(
α us
), pelvis (
α ps
), body center of mass (
α bs
), thigh (
α ts
), shank (
α ss
) and of the foot support base (
α fs
).
Each module controls the CoM of all body segments above the indicated joint (example: body center of
mass, CoM, above ankle joints).
The DEC contr ol is used in a modular form here for a triple inverted pendulum (TIP) scenario,
in which each module is controlling a DoF (see [
30
,
31
] for details). The four modules shown in
Figur e 3 B are contr olling the ankle joints, the knee joints and the hip joints, and the pelvis joint,
r espectively , while all other degr ees of freedom ar e actuated as simulated spring dampers. In this work
we implemented the compensation of support surface tilt, gravity and external torque (e.g., contact
for ce), while the compensation of the support surface translation r emained unconsider ed in the
experiment performed. The estimation of the disturbances to be compensated is described in the
following paragraphs of this section. In general, they ar e based on the kinematics variables measured
by the sensors (i.e., orientation of the upper body , joint angles and the r espective derivatives). In order
to specify the task of standing upright in terms of tar get position, the robot is commanded to maintain
an upright stance with all the segments vertical while balancing. This is possible due to the fact that
body pose is expr essed in terms of segments’ sway and then there is no singularity in the contr ol.
Support surface tilt.
This tilt is estimated by combining vestibular and pr oprioceptive signals.
The vestibular signal is implemented using the bio-inspir ed model presented in [
15
,
32
]. Pr oprioceptive
signals ar e produced by the encoders (Figur e 2 B). The sensor fusion is implemented by summing the
tilt and r otation velocity computed by the proprioceptive system with the joint angles pr ovided by the
pr oprioceptive system, as shown in (1). More details of this appr oach to sensor fusion ar e provided
in [ 33 – 35 ].
The signal used to compensate the support surface r otation uses the integral of the tilt velocity
of the foot in space, obtained through the down-channeling of the vestibular head in space velocity
thr ough the modules, where it is summed with the pr oprioceptive inputs
.
α f s = .
α hs − .
α hp − .
α pl − .
α lsh − .
α sh f (1)
( hs —head–space; hp —HA T -pelvis—where HA T is Head–Arms–T runk ; pl —pelvis-leg; lsh —leg-shank;
shf —shank-foot).
In this context “down-channeling” is r eferred to the pr opagation of a signal from the upper
module (in this case the “pelvis module” in Figure 3 B) to the lower ones (“hip”, “knee” and “ankle”
modules in Figur e 3 B). Similarly , “up-channeling” means that the signal computed in a control module
is sent to the module above (i.e., from the “ankle module” to the “knee module”). This distinction

Appl. Sci. 2020 , 10 , 5240 7 of 14
is necessary because, in the proposed bio-inspir ed model, the estimated foot-in-space orientation
is a ff ected by a dead-band function, see (2) and (3). The contr ol system uses two versions of each
orientation in space signal, one a ff ected by the threshold (up-channeled fr om the foot) and the other
one not a ff ected by it (down-channeled from the head). The up-channeled signal is used in the servo
loop, the down-channeled one is used for gravity compensation.
The foot is assumed to be always in firm contact with the support surface (as shown in Figur e 3 B,
.
α fs = .
α ss ). The estimated foot in space tilt is
α f s = Z t
0
ρ  .
α f s  − k α f s d τ , (2)
wher e
ρ ( )
is the thr eshold function and t the current time. The term
− k α fs
is added to make the
integrator leaky ( k was set to 1 / 80).
Given the thr eshold θ > 0, the function ρ ( α ) is defined as
ρ ( α ) = 












α + θ α ≤ − θ
0, − θ<α<θ
α − θ α ≥ θ
(3)
The value of
θ
is a parameter of the ankle contr ol module, in this setup it is set to 0.009 rad / s.
The thr eshold function was introduced to mimic the nonlinear r esponse exhibited by human subjects
wher e larger support surface tilts ar e more compensated than smaller ones [
7
]. It can be shown that
such nonlinearity does not harm the equilibrium, in that the stability of the system depends on the
contr ol parameters that are independent of the value θ [ 33 ].
The estimate of support surface tilt fr om (2) is up-channeled through the modules to r econstruct
the orientation in space of each segment.
Gravity . The gravity tor que T g for the ankle joint is calculated by
T g = m g h · sin ( α bs )  m g h α bs (4)
wher e m is the mass of the body , h the height of the CoM,
α bs
its angle in space and g the gravity
constant. In a similar way , the gravity disturbance acting on each joint is computed on the basis of the
sway of the CoM of all the segments above the contr olled joint.
Contact for ce disturbance.
The external contact for ce repr esents the interaction with the external
world, i.e., with the impact that is not pr oduced by gravity and the movement of the support surface.
The contact for ce disturbance estimator also identifies the unmodelled e ff ects such as the inertial force
pr oduced by an unknown additional mass. Considering that robots and exoskeletons do not usually
have a full body sensor input for contact for ces, the identification of unexpected contacts with the
envir onment should be performed on the basis of the available sensors exploiting the knowledge of
the dynamics. This, for example, can be performed using a Luenber ger observer with an extended
state vector featuring the external for ce as an additional state variable [
36
] or , in order to cover mor e
general nonlinear cases, a particle filter [
37
]. In the case of the DEC, the contact for ce is repr esented as
an extra tor que applied on a joint. Such a tor que is computed as the di ff erence between the applied
tor que (which includes the compensation of the external disturbances) and the torque computed on
the basis of the kinematics. For example, the total applied tor que in the ankle joint is
T A = J d 2
dt 2 α bs (5)
wher e J is the moment of inertia. The external torque becomes:
T ext = T A −  T g + T c  , (6)

Appl. Sci. 2020 , 10 , 5240 8 of 14
wher e T
g
is the gravity tor que described in the pr evious paragraph and T
c
is the contr ol torque
pr oduced by the module.
The same concept applies to all the joints, considering mass and moment of inertia of the set of
links above the contr olled joint, as explained in detail in [ 17 ].
Contr ol equations.
The disturbance compensation is implemented by summing the disturbance
estimates with the input of the contr oller (PD in Figure 3 A). For the support surface tilt, this can be seen
as a coor dinate transformation of the controlled variable fr om joint coordinates to space coor dinates.
Gravity and external push values ar e divided by mgh, resulting in an angle equivalent to the tor que,
i.e., the angle that would produce the tor que evoked by gravity during body (or segment) lean as
shown in (4). The tor que commanded by the servo controller module is defined by
T c = − K p 







ε −  T g + T ext 
mgh 







− K d 







.
ε −  .
T g + .
T ext 
mgh 







(7)
wher e K
p
and K
d
ar e the proportional and the derivative gain, respectively , and
ε
is the err or of
the contr olled variable as computed using the up-channeled information. The controlled variable is
specified for each module: i. Body COM sway for ankle joint, ii. Joint angle for the knee and, iii. T runk
(HA T) in space for the hip joint and the joint in the lower back. The e ff ect of each disturbance input
and of the err or signal of the servo loop can be adjusted by gains (see T able 1 for module parameters)
while the r elation between proportional ( K
p
) and derivative ( K
d
) gain is fixed for all disturbances.
Notably , all behavioral tests with Lucy—previously [
17
] and her e—are performed with the same set of
contr ol parameters, with the aim of testing the robustness of the contr ol system with a setup that is not
accounted for by such nominal contr ol parameters. According to (6), including T
ext
as an input for
the PD contr oller means that there is a positive feedback of the active tor que in the joint. In general,
this can make the system unstable, especially in the presence of delay . In order to avoid instability ,
the signal T
ext
is low pass filter ed using a Butterworth filter with cuto ff frequency
ω ext
and multiplied
by a gain G ext smaller than unity . The contr ol parameters are shown in T able 2 .
T able 2. Contr ol parameters.
Symbol Quantity V alue
ANKLE
K p proportional gain 119.57 Nm / rad
K d derivative gain 11.95
Nms / rad
G ext external torque gain 0.5
ω ext
External torque filter cuto ff fr equency
5 rad / s
KNEE
K p proportional gain 55.72 Nm / rad
K d derivative gain 0.4458
Nms / rad
G ext external torque gain 0.5
ω ext
External torque filter cuto ff fr equency
5 rad / s
HIP
K p proportional gain 22.71 Nm / rad
K d derivative gain 5.67
Nms / rad
G ext external torque gain 0.5
ω ext
External torque filter cuto ff fr equency
5 rad / s
3.3. Balancing Experiment
In or der to experimentally simulate a user–exoskeleton interaction scenario, we used the r obot
Lucy to r epresent the exoskeleton and challenged its disturbance compensation by sinusoidal support
surface tilts of peak-to-peak 4
◦
and 8
◦
in the body’s sagittal plane. Such disturbance is r elatively small
compar ed to the capability of the system—for this reason, the r obot is not expected to fall. The r obot
(Figur e 2 C) has 14 DoF . The control in the sagittal plane is implemented using 4 contr ol modules

Appl. Sci. 2020 , 10 , 5240 9 of 14
(Figur e 3 B). The hypothetical exoskeleton, shown in Figure 1 , has 3 DoF in the sagittal plane. In the
scenario pr esented, the additional DoF in the back do not produce a r elevant e ff ect on the behavior .
Figur e 4 A shows the body sway of all the body segments, computed on the basis of the internal sensors.
All the segments ar e swaying together , i.e., the di ff er ence between the body segments’ orientation in
space is very small and not exceeds considerably 1
◦
. This suggests that it is legitimate to describe the
kinematics of the body in this scenario with the sway of the body CoM (Figur e 5 ).
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 10 of 16

Figure 4. ( A ) body sway in space of the b o dy seg m e nt s in the sagitta l plane computed using the
internal sen s ors in the presen ce of a peak-to- peak 8° t i l t a n d w i t h t h e a d d i t i o n o f a n e c c e n t r i c w e i g h t
to the pelvis (compare Figure 2A). TS—trunk-i n-space; PS —pelvis- in-spa ce; LS—l eg -in-space; SS—
s h ank-i n -s pac e ; FS—foot i n spac e. Al l bod y s e gment s m o ve tog e ther in t h is s c enario, a n d all sway s
are within a range smaller th an 1°; ( B ) s t i c k fi gure s h owi n g the posi ti on of the s e gments at d i fferent
tim e s (e very 10 s).

Figure 4.
(
A
) body sway in space of the body segments in the sagittal plane computed using the internal
sensors in the presence of a peak-to-peak 8
◦
tilt and with the addition of an eccentric weight to the pelvis
(compare Figur e 2 A). TS—trunk-in-space; PS—pelvis-in-space; LS—leg-in-space; SS—shank-in-space;
FS—foot in space. All body segments move together in this scenario, and all sways ar e within a range
smaller than 1 ◦ ; ( B ) stick figure showing the position of the segments at di ff er ent times (every 10 s).

Appl. Sci. 2020 , 10 , 5240 10 of 14
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 11 of 16

Figure 5. Robo t balancing tes t s. Robot Lu cy su cce ssfu lly b a lanced in the body sagittal p l ane when
presented w i th support surface tilts in th e bo dy sagitta l plan e of peak-to-pe ak ( A ) 4° and ( C ) 8°. Bo dy
C O M sway w i th the a ddit i on of an e ccentri c we ig ht fixed to the robot’s a n terior pelv is ( s ee Figure
2A). Thi s in creased the sway r e sponses to the peak -to-peak ( B ) 4° and ( D ) 8 ° su pport su rface ti lts , bu t
the ( B and D ) tilt distu r bance wa s stil l w e ll com p ensate d. The eff e ct o w es to the ‘co n tact forc e
compensation’ of the robot’s disturbance e s t i mati on and co m p ensation (DEC ) sy stem . Ba lance was
lost when this DEC m e chanism was inact i vated (n ot s h own). Thi s experi ment mi mi c s a s i tuati o n
where the exoskeleton user, while ex posed to su pport su rface ti lts , wou l d chang e the b o dy weig ht
distribu tion by raisin g th e arm s , l e an in g th e u pper body or lift i n g with a h a n d an ex tern al weig h t .
As already sh own in the c l assic a l work o f Hor a k and Nashner [24], t h e here implemented ‘ankle
stra tegy’ turns the body i n to a n i n verted pendulum . Its COM is m a inta i n ed cl ose to the upri ght usi n g
p r im ar il y an k l e t o rq ue. For exam p l e , dur i ng an ev ok ed forward sw ay, musc le s on the backs i de of the
b o dy a r e act i v a t e d in a b o t t o m – up w a y (sep arat ed b y a few mil l i s e c onds) in t h e wake of m a in t a inin g
the body seg m ents aligne d and uprigh t. A backw a r d s w a y e v o k e s t h e s a m e r e s p o n s e p a t t e r n o n t h e
front side o f t h e body. A differ e nt balanc e strate gy, als o descr i bed by Hor a k an d Nashner [24] is th e
‘hip strateg y ’, which is se en for examp l e when hu m a n s are st and i ng on a n a rrow b e am . As m e nt ioned
above (Sectio n 2), balanc e is then maint a ined by r a pid hip flexion/ex tension, creating horizontal shear
forces on the body support —a method that is re st rict ed in its use f ulne ss an d u n der normal standin g
conditions w o uld be more exhausting and less effi ci ent. A modi fi ed versi o n of the a n kl e stra tegy is
seen with lar g e perturbations where the ank l e joint torq ues tend to exceed i t s l i mi t. Hum a n subject s
then tend to bend tra n siently the knees to get i n to a sq ua t posi ti on [23 ] . Concei va b l y, use of the a n kle
strategy is r e stricted to lo wer body ex oskeletons with a c tua t ed ankl e joi n ts, as f o r exa m ple i n the
exoskel e ton R o bot [14 ] . It rema i n s to be sta t ed th at t h e above de s c ribed b a l a nc ing met h od , which is
dra w i n g to a la rge extent on the a n kle torque re s p onses, i s no t appl icab le t o t h ose lowe r body
exoskeletons which do not contain an ankle jo int wit h act u at ion. The ank l e st r a t e gy d i sp la y e d in
Fig u re 4B for Lucy applies not only to re sponses to sinusoidal s u p p ort surface r o tations, b u t also to
tra n sla t ion and other perturba tion such a push aga i nst the body. An i l l u stra ti ve exa m p l e f o r
responses to sinu soid al tilt s and for pse u dor a ndom t r ans l at ions i s shown in t h e t w o films , pr ovided
i n the suppl ementa ry m a teria l , where Lucy b a la nces i n the body sa gi ttal p l a n e.
Movements in the front a l plane, where no stimul u s was provided , were neg l i g i b le. Exo s ke let o n
user act i on su ch a s li ft ing a n ext e rna l we ight , le anin g t h e t r unk or r a isin g t h e arm s w a s mim i ck ed by
producin g a c h ange in t h e robot ’ s weigh t dist r i but i on. To t h is end , an ecc e nt ric weight w a s f i xed i n
f r ont of the p e l v i s of the robot Lucy (see Fi gure 2 A ; 1 kg a t a 12 .5 cm eccentri ci t y wi th respect to the
A B
C D

Figure 5.
Robot balancing tests. Robot Lucy successfully balanced in the body sagittal plane when
presented with support surface tilts in the body sagittal plane of peak-to-peak (
A
) 4
◦
and (
C
) 8
◦
.
Body COM sway with the addition of an eccentric weight fixed to the r obot’s anterior pelvis
(see Figure 2 A). This incr eased the sway r esponses to the peak-to-peak (
B
) 4
◦
and (
D
) 8
◦
support surface
tilts, but the (
B
,
D
) tilt disturbance was still well compensated. The e ff ect owes to the ‘contact force
compensation’ of the r obot’s disturbance estimation and compensation (DEC) system. Balance was lost
when this DEC mechanism was inactivated (not shown). This experiment mimics a situation wher e the
exoskeleton user , while exposed to support surface tilts, would change the body weight distribution by
raising the arms, leaning the upper body or lifting with a hand an external weight.
As alr eady shown in the classical work of Horak and Nashner [
24
], the her e implemented ‘ankle
strategy’ turns the body into an inverted pendulum. Its COM is maintained close to the upright using
primarily ankle tor que. For example, during an evoked forward sway , muscles on the backside of the
body ar e activated in a bottom–up way (separated by a few milliseconds) in the wake of maintaining
the body segments aligned and upright. A backwar d sway evokes the same response pattern on the
fr ont side of the body . A di ff erent balance strategy , also described by Horak and Nashner [
24
] is the
‘hip strategy’, which is seen for example when humans ar e standing on a narrow beam. As mentioned
above (Section 2 ), balance is then maintained by rapid hip flexion / extension, creating h orizontal shear
for ces on the body support—a method that is restricted in its usefulness and under normal standing
conditions would be more exhausting and less e ffi cient. A modified version of the ankle strategy is
seen with lar ge perturbations where the ankle joint tor ques tend to exceed its limit. Human subjects
then tend to bend transiently the knees to get into a squat position [
23
]. Conceivably , use of the
ankle strategy is r estricted to lower body exoskeletons with actuated ankle joints, as for example
in the exoskeleton Robot [
14
]. It remains to be stated that the above described balancing method,
which is drawing to a lar ge extent on the ankle tor que responses, is not applicable to those lower body
exoskeletons which do not contain an ankle joint with actuation. The ankle strategy displayed in
Figur e 4 B for Lucy applies not only to responses to sinusoidal support surface r otations, but also to
translation and other perturbation such a push against the body . An illustrative example for responses
to sinusoidal tilts and for pseudorandom translations is shown in the two films, pr ovided in the
Supplementary Material, wher e Lucy balances in the body sagittal plane.
Movements in the fr ontal plane, where no stimulus was pr ovided, were negligible. Exoskeleton
user action such as lifting an external weight, leaning the trunk or raising the arms was mimicked
by pr oducing a change in the robot’s weight distribution. T o this end, an eccentric weight was fixed
in fr ont of the pelvis of the robot Lucy (see Figur e 2 A; 1 kg at a 12.5 cm eccentricity with respect to
the body axis). It remained unaccounted in the r obot’s control parameters but was drawing on the

Appl. Sci. 2020 , 10 , 5240 11 of 14
so-called contact for ce compensation of the DEC control (in addition to the r unning support surface tilt
compensation). The result of the experiment was that the tilt evoked sway responses wer e enlar ged,
but balance was maintained (Figur e 5 B,D). When contact force compensation was disabled, in contrast,
Lucy tended to fall forwar d during the tilt stimuli.
The r obot Lucy balances during stance despite the rather weak strength of the leg actuators,
DC Maxon RE-max 29 motor , providing 24 W of power . The motor has a nominal tor que of 27 mNm.
A linear drive is implemented with a scr ew / spindle system (pitch 2 mm, estimated e ffi ciency 90%).
The lever arm is 5 cm, the resulting nominal tor que in the joint is 3.8 Nm. A detail of the actuation system
is shown in Figure 2 B. This point is meant her e to underline that the human body anthropometrics
(biomechanics) support biped standing and its balancing as long as the body is kept upright. In the
exoskeleton, bringing the patients from the sitting to the standing pose would r equire extra solutions
(e.g., special equipment such as a walking cane) when one wants to unburden the exoskeleton fr om
being equipped with str ong and heavy actuators.
4. Potential Extensions of the Balancing T ests
For the sake of completeness, we point out that the contact force compensation of the DEC contr ol
can also be tested in isolation by applying a body push (Figur e 6 B), and that further tests may consist
of support translation (Figur e 6 C) and the so-called “body sway refer enced platform” (Figure 6 D).
The latter excludes feedback from ankle pr oprioception so that the balancing relies primarily on
vestibular information (standing in a compliant surface would be a simple surrogate). These tests
suggested her e for the self-balancing of the exoskeleton are derived fr om human experiments and have
been consider ed in detail before in [
22
] for r obotic applications such as balancing benchmarking, together
with various stimulus waveforms, e.g., sine waves or a mor e complex waveform that allows extraction
of fr equency response functions. These tests have been applied to humans, which facilitates estimation
of human-likeness in the performance of the r obotic application. Interestingly , when comparing in [
22
]
humanoids of vastly di ff er ent body weights (67 kg vs. 17.5 kg) the di ff er ences in overall weight had
little r elevance for the balancing response.
Appl. Sci. 2020 , 10 , x FO R P EER R E VIEW 12 of 16

body a x is). It rema i n ed una ccounted i n the robot’s control pa ra meters but wa s dra w i n g on t h e so-
called contact force compe n sation of the DEC contro l ( i n a d di ti on to the runni ng support surfa c e t i l t
compensatio n ). The r e sult of the exper i ment was th at the tilt evok ed sw ay re sp onses wer e e n lar g ed,
but balance was m a int a ined (Fig ure 5B,D ). When contact fo rc e compensation was d i sabled, in
cont rast , L u c y t e nded t o f a ll forw ard du ring t h e t ilt st imul i.
The robot Lucy balance s d u ring stan ce despite the rather wea k strength of the leg actua t ors, DC
Maxon RE -max 2 9 mot o r, providing 24 W of power. The motor has a nom i nal t o rque of 27 mNm. A
line a r dr ive is implement e d wit h a screw/ spindl e sy ste m (pitch 2 m m , estim a ted efficienc y 90%). The
lever arm i s 5 cm, t h e r e s u lt ing nom i n a l t o rqu e in t h e j o int i s 3. 8 Nm . A det a i l o f t h e a c t u at ion s y st em
is shown in F i gur e 2 B . Thi s point is me ant here to underli n e tha t the huma n b o dy a n thropometri c s
(biomecha n ics) support biped st a n ding a n d its bala ncin g as l o ng as the body is kept upri ght. In the
exoskel e ton, bri n gi ng the pa ti ents f r om the si tti ng to t h e stand i ng p o se wou l d re qu ire extr a so lution s
(e.g ., spec ial equipment such as a w a lk ing cane ) wh e n one wants t o unburden t h e exoske leto n from
b e ing e q u i p p ed wit h st rong an d he av y act u at ors.
4 . Pote nt ia l Ex te nsi o ns of the Ba la nci n g Te st s
For the sake of compl e teness, we poi n t out th a t the conta c t f o rce compensa tion of the DEC
cont rol c a n a l so b e t e st ed i n i s ol at ion b y ap p l yin g a b o dy p u sh (F ig ure 6B ), and t h at furt her t e st s m a y
consist o f s u p p ort t r ansl at i o n (F igu r e 6C ) an d t h e so -c al led “b ody s w ay r e fer e nc ed p l at form ” (Fi g ure
6D). The latter exclud es fee d back fr om a n kle proprioc ept i on so t h at t h e balanc in g rel i es pr ima rily o n
vest ibul ar in f o rmat ion (st a nding in a co mpliant s u rface wou l d be a simple surr ogate). The s e tests
sugg ested h e re for the self-balanc i ng o f the exoskelet o n are der i ve d from hum a n experiment s an d
have been co nsider ed in d e t a il befor e in [2 2] for robot i c appl icat ions such a s ba l a n c ing benchm a rking ,
together with vario u s stim ulu s w a vefor m s, e.g ., si ne waves or a m o re complex waveform t h at a llow s
extraction of frequenc y response func tions. Th ese tests have b een applied to humans, which
f a ci li ta tes est i ma ti on of huma n-l i k eness i n the perf or mance of t h e robot i c applic at ion. Int e rest ingl y,
when compar ing in [ 2 2] hu manoid s of v a st ly di ff er ent body we ight s (67 kg vs. 17.5 kg) the d i fferences
in over al l we i g ht had lit t l e relev a nce for t h e bal a ncin g response .

Figure 6.
(
A
–
D
) Suggested four basic tests of self-balancing of the exoskeleton (r esorting directly to
testing of human postural control and its application in humanoid r obots; compare [ 12 ]).

Appl. Sci. 2020 , 10 , 5240 12 of 14
5. Discussion and Conclusions
Confidence in successful contr ol of stance stabilization is crucial for physical training with
an exoskeleton. In fact, fear of falling (FOF) is often a major problem for iSCI patients, especially of
those in whom fall was the r eason for the spinal cord injury . In addition, FOF adversely a ff ects the
e ffi ciency of therapy , rehabilitation and use of assistive devices [
37
]. Given this background, it may
be advantageous if patients learn and experience that they ar e using a human-inspired sensorimotor
contr ol system that is performing as they expect it, and this with compliant impedance-controlled
actuators that ar e considered safer and mor e comfortable for physical human–robot interaction [ 38 ].
FOF may arise if the patients experience the movements and postural actions pr oduced by the
exoskeleton as inadequate. It may be danger ous if they then try to enforce counteractions. W e conceive
that this may end in a dangerous “user –device conflict”. For example, fear of falling backward may
lead the patient to command an inadequate forward COM lean of the user –exoskeleton body , which the
exoskeleton in turn then may try to correct by a lean backwar d, which in turn, likely enhances the fear
and action of the patient even mor e—a potentially disastrous positive feedback situation.
Curr ently , little is known about such user –device problems. W e conceive that such problems
can best be over come by training and cautiously building up confidence, for example in that the
patient is initially using stationary handrails when maintaining balance. The training may then include
self-pr oduced changes in the balancing situation, for example when raising the arms or lifting an object
with a hand (compar e above, Section 3.3 , Balancing Experiment).
The contr ol model described in the previous sections r elies on the presence of a vestibular system
(e.g., derived from using IMUs; [
17
]). This is not an obvious design choice as most of the e ff ort in
exoskeleton designs is devoted to the tracking of user ’s movements (e.g., by means of encoders [
39
])
or muscle activity [
40
] or of the for ces that the user applies to the robot [
41
] without focusing on
the position of the exoskeleton itself in space. The compensation of external disturbances can coexist
with the pr eviously mentioned approaches that can be applied to the contr ol of active movements,
for example the servo loop can be controlled with a signal based on for ce sensors and at the same time
the for ces produced by the user can be explicitly consider ed in (6) so that they do not interfere with
the compensation of the external forces. Overall, the development of robotic exoskeletons appears
to be still long-lasting in view of the many di ffi culties to make these devices suitable for patients’
r eengagement in everyday activities [
42
]. The integration of postur e control seems one of the possible
ways to impr ove the usability of the exoskeletons and also to inspire design decisions, e.g., in choosing
the sensors.
Supplementary Materials:
The following are available online at http: // www .mdpi.com / 2076- 3417 / 10 / 15 / 5240 / s1 ,
V ideo S1: Lucy_tilt_Balancing.MP4, V ideo S2: Lucy_T rans_Balancing.m4v .
Author Contributions:
V .L. and T .M. were r esponsible for study design, data collection, analysis and manuscript
writing. All authors have read and agreed to the published version of the manuscript.
Funding:
W e acknowledge support by the German Resear ch Foundation and the Open Access Publication Fund
of TU Berlin.
Conflicts of Interest: The authors declare no conflict of interests.
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Why institutions use Plag.ai for originality review, entry 95

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