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Pediatric robotic rehabilitation: Current knowledge and future trends in treating children with sensorimotor impairments


Abstract and Figures

Background: Robot-aided sensorimotor therapy imposes highly repetitive tasks that can translate to substantial improvement when patients remain cognitively engaged into the clinical procedure, a goal that most children find hard to pursue. Knowing that the child's brain is much more plastic than an adult's, it is reasonable to expect that the clinical gains observed in the adult population during the last two decades would be followed up by even greater gains in children. Nonetheless, and despite the multitude of adult studies, in children we are just getting started: There is scarcity of pediatric robotic rehabilitation devices that are currently available and the number of clinical studies that employ them is also very limited. Purpose: We have recently developed the MIT's pedi-Anklebot, an adaptive habilitation robotic device that continuously motivates physically impaired children to do their best by tracking the child's performance and modifying their therapy accordingly. The robot's design is based on a multitude of studies we conducted focusing on the ankle sensorimotor control. In this paper, we briefly describe the device and the adaptive environment we built around the impaired children, present the initial clinical results and discuss how they could steer future trends in pediatric robotic therapy. Conclusions: The results support the potential for future interventions to account for the differences in the sensorimotor control of the targeted limbs and their functional use (rhythmic vs. discrete movements and mechanical impedance training) and explore how the new technological advancements such as the augmented reality would employ new knowledge from neuroscience.
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NeuroRehabilitation xx (20xx) x–xx
IOS Press
Pediatric robotic rehabilitation: Current
knowledge and future trends in treating
children with sensorimotor impairments
Konstantinos P. Michmizosa,and Hermano Igo Krebsb
aDepartment of Computer Science, Rutgers University, Piscataway, NJ, USA5
bDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA6
BACKGROUND: Robot-aided sensorimotor therapy imposes highly repetitivetasks that can translate to substantial improve-
ment when patients remain cognitively engaged into the clinical procedure, a goal that most children find hard to pursue.
Knowing that the child’s brain is much more plastic than an adult’s, it is reasonable to expect that the clinical gains observed
in the adult population during the last two decades would be followed up by even greater gains in children. Nonetheless, and
despite the multitude of adult studies, in children we are just getting started: There is scarcity of pediatric robotic rehabilitation
devices that are currently available and the number of clinical studies that employ them is also very limited.
PURPOSE: We have recently developed the MIT’s pedi-Anklebot, an adaptive habilitation robotic device that continuously
motivates physically impaired children to do their best by tracking the child’s performance and modifying their therapy
accordingly. The robot’s design is based on a multitude of studies we conducted focusing on the ankle sensorimotor control.
In this paper, we briefly describe the device and the adaptive environment we built around the impaired children, present the
initial clinical results and discuss how they could steer future trends in pediatric robotic therapy.
CONCLUSIONS: The results support the potential for future interventions to account for the differences in the sensorimotor
control of the targeted limbs and their functional use (rhythmic vs. discrete movements and mechanical impedance training)
and explore how the new technological advancements such as the augmented reality would employ new knowledge from
Keywords: Rehabilitation robotics, robot-aided therapy, robot-aided neurorehabilitation, pediatric, cerebral palsy, adaptive
robotic therapy
1. Introduction25
Robot-aided neurorehabilitation is a form of phys-
ical or occupational therapy that uses a robotic device
to educate or re-educate the brain on how to move an
Address for correspondence: Konstantinos P. Michmizos,
Laboratory for Computational Brain, Department of Computer
Science, Rutgers University, 110 Frelinghuysen Road, Piscataway,
NJ 08854, USA. Tel.: +1 848 445 8841; Fax: +1 732 445 0537;
impaired limb in the presence of an acquired neuro- 29
logical disease, such as stroke, or a developmental 30
motor disability, such as cerebral palsy. The clinical 31
evaluation of rehabilitation devices provided strong 32
evidence that robots can replicate, even augment, the 33
functional improvement achieved by human thera- 34
pists (Kwakkel, Kollen et al., 2008) with comparable 35
cost (Lo, Guarino et al., 2010; Wagner, Lo et al., 36
2011). That is why the American Heart Associa- 37
tion now recommends robotic therapy as a standard 38
1053-8135/17/$35.00 © 2017 – IOS Press and the authors. All rights reserved
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2K.P. Michmizos and H.I. Krebs / Pediatric robotic rehabilitation
post-stroke treatment, at least for the upper extrem-39
ities (UE) (Miller, Murray et al., 2010; Winstein,
Stein et al., 2016). A striking finding over the last41
few years is that a successful sensorimotor recovery42
requires more than limb motion: In fact, the first43
effort to employ the patient’s active participation into
robotic therapy (Krebs, Palazzolo et al., 2003) led45
to a series of adaptive treatments aiming to con-46
tinuously challenge and assist a patient to improve;47
This has signified the assist-as-needed robotic ther-
apy as a key mechanism for improving motor function49
(Volpe, Krebs et al., 2000; Patton & Mussa-Ivaldi50
2004; Patton, Stoykov et al., 2006).
Especially for children with sensorimotor impair-52
ments, motor function has been found to improve
by purposeful activity and task-specific training that54
adapts to each patient’s skills and needs (Valvano55
2004; Michmizos, Rossi et al., 2015). Although other,
highly intensive, approaches such as constraint-57
induced movement therapy have given positive58
results in children with mild upper limb impairments59
(Huang, Fetters et al., 2009; Gordon, Hung et al.,60
2011), what constitutes the appropriate treatment,61
especially for children with more severe sensori-62
motor impairments, remains to be found. For as
long as motor learning remains the major working
hypothesis for sensorimotor rehabilitation (Hogan,65
Krebs et al., 2006), a well-designed robotic ther-
apy, for either adults or children, should follow the67
principles of motor learning, namely massed prac-68
tice, cognitive engagement and functional relevance
(Damiano 2006). However, massed practice is dif-70
ficult to achieve in children whereas the number
of executed movements by itself cannot be fully
accounted for the improvement achieved through73
robots. What is more, cognitive engagement requires74
strong concentration, which is very difficult to pre-75
serve in children. Even the functional relevance76
of a rehabilitation task is not always appealing or77
even apparent to most children who rarely use their
impaired limb to execute the targeted task. These79
are some of the biggest challenges that any pediatric
robotic habilitation device should aim to address.81
We have recently introduced the MIT’s pedi-82
Anklebot, a robotic device that provides an intensive83
task-specific sensorimotor therapy to the ankle of84
children with motor disabilities (Michmizos, Rossi85
et al., 2015). The device lives in a human-robot sym-86
biotic system that assesses the ability of the child
to move and adapts the difficulty of the movement
(Michmizos & Krebs 2012; Michmizos & Krebs
2012) by changing its speed and accuracy constraints
(Michmizos & Krebs 2014; Michmizos & Krebs 91
2014; Michmizos, Vaisman et al., 2014). In this paper, 92
we briefly present the device, as well as the clinical 93
results upon its employment in two pediatric Hos- 94
pitals, Blythedale Children’s Hospital in Valhalla, 95
NY, USA and Bambino Ges´
u Children’s Hospital in 96
Rome, Italy, and show how these results can influence 97
future trends in pediatric robotic therapy. 98
2. The MIT’s pedi-Anklebot 99
The MIT’s pedi-Anklebot is an impedance- 100
controlled low-friction, back-driveable habilitation 101
device that targets the ankle joints and aims to pro- 102
mote motor learning in children of ages 6–10 years 103
old (Michmizos, Rossi et al., 2015). While the design 104
of its hardware follows that of the adult version of 105
the device, its software (controller and a set of seri- 106
ous games) aims to tackle the distinct challenges 107
in pediatric habilitation. To this end, we expanded 108
the performance-based adaptive robotic therapeutic 109
scheme that we had previously introduced for our UE 110
robots (Krebs, Palazzolo et al., 2003) to include motor 111
learning principles (Michmizos & Krebs 2012). In 112
the following sections, we briefly describe how the 113
device adapts the therapy to meet the needs and 114
the special challenges associated with the pediatric 115
habilitation, demonstrate its potential as a therapeu- 116
tic device that can induce motor learning in discrete 117
ankle movements and show evidence that its use can 118
result to notable changes in the walking pattern. 119
2.1. Hardware design 120
The pedi-Anklebot provides active assistance to 121
the ankle in 2 degrees-of-freedom (DOF), namely 122
dorsi-plantar flexion (DP) and inversion-eversion 123
(IE); it also has a passive DOF for internal-external 124
rotation. Overall, it allows 25dorsiflexion, 45125
plantar flexion, 25inversion, 15eversion, and 126
15internal/external rotation, which are near the 127
maximum range of comfortable motion for normal 128
subjects and beyond what is required for typical gait 129
(Weiss, Kearney et al., 1986; Weiss, Kearney et al., 130
1986). The device consists of two linear actuators 131
mounted in parallel so that if both push or pull in the 132
same (opposite) direction, a DP flexion (IE) torque 133
is produced (Fig. 1a). The actuation is provided by 134
2 brushless DC motors and a Rohlix linear traction 135
drive that can deliver a maximum torque 7.21 Nm in 136
DP flexion and 4.38 Nm in IE. The torque capability 137
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K.P. Michmizos and H.I. Krebs / Pediatric robotic rehabilitation 3
Fig. 1. The MIT’s pediatric ankle robotic system (pedi-Anklebot). (A) The mechanical design of the robotic device showing the components
of the device. (B) An 8-year old child wearing the robot in seated position; the weight of the robot is supported from the chair, through a
screw-bolt. (C) The set of the adaptive serious games that were developed for the device based on motor learning principle (up) and the
relative positioning of the patient with respect to the projected games (bottom).
lifts approximately 25% of a child’s weight and there-138
fore can be used as a supplemental support to the
paretic ankle plantarflexors during walking; Alterna-140
tively, the robot can be used in a seated position where141
discrete ankle movements can be trained (Fig. 1b).142
The robot is also equipped with two motion sensors,
a mini-rail linear encoder (Schneeberger) and a Gur-144
ley rotary encoder, as well as load cells (Futek) at145
each actuator output.146
2.2. Software design
We have developed a set of 3 goal-directed serious148
games (SGs), namely a race (Noah’s Ark), Soccer
and Shipwreck games (Fig. 1c), to address motor150
impairments including poor coordination, impaired151
motor speed or accuracy, and diminished strength,152
as well as to address cognitive or perceptual impair-153
ments (Michmizos & Krebs 2012). To do so, all our154
SGs follow the same design principles that include155
meaningful play and challenge and have: a) an inter-156
esting concept, to support the level of perceptual157
joy throughout the therapeutic sessions; b) a simple158
visual interface, to communicate easily the game con-159
cept; c) easy controls, to facilitate guidance around160
the visual interface and focus on the game concept;161
and d) simple rules, to minimize learning period.162
The SGs are seamlessly integrated with the hard-163
ware and the controller of the pedi-Anklebot as they164
require discrete or rhythmic movements which can be165
assisted-as-needed by the robot. In addition, the task
objectives of the race, the soccer and the shipwreck
games were blocked, serial, and random, respec-
tively, covering the entire spectrum of the structured 169
practice. The predictability of the available game- 170
play environments also varied greatly. The race game 171
could provide a closed environment whereas the 172
other two game environments were open, with that 173
of the Shipwreck varying the most. As the player 174
plays the game and his or her skills and familiarity 175
increases, the game offers a higher level of chal- 176
lenge to retain attention and motivation; nonetheless, 177
since a too-difficult-to-play game will make a child to 178
become frustrated, the gameplay could become easier 179
if needed. Overall, the set of the SGs can promote all 180
three stages of motor learning: cognitive, associative, 181
and autonomous (Fitt & Posner 1967). 182
To retain active participation during therapy, we 183
translated to the ankle movements the concept of 184
adaptive assist-as-needed robotic therapy introduced 185
for the UE. Specifically, our recent finding that 186
the performance in visually evoked, visually guided 187
ankle pointing movements can be described by a lin- 188
ear function, as predicted by Fitts’ law, supported the 189
idea that the speed-accuracy trade-off (SAT) could 190
be incorporated into an assist-as-needed therapeu- 191
tic intervention for the ankle (Michmizos & Krebs 192
2014). In that sense, the SGs trained the child’s ankle 193
while challenging his/her ability to move fast and 194
accurately: Depending on one’s ability to aim, the 195
target of the game became smaller or larger; Depend- 196
ing on one’s ability to move fast or slow, the speed of 197
the game also changed; for details see (Michmizos & 198
Krebs 2012; Michmizos, Rossi et al., 2015). 199
To challenge children to improve while keep-
ing them motivated, each therapeutic session was
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4K.P. Michmizos and H.I. Krebs / Pediatric robotic rehabilitation
grouped into sections of nrepetitions. For each
section, we defined the performance level (PL) as
PL =
1|PM <0.1
0|−0.1PM ≤+0.1
+1|PM >+0.1
where the value of PL indicates whether patients per-
formed worse (PL = –1) or better (PL = 1) than their
expected ability (PL = 0 denotes when patients per-
form approximately the same); and PM is one of the 4
performance metrics (PMs) that we used, namely the
ability to initiate movement, the power to move from
the starting position to the target, the ability to reach206
the target efficiently and in a timely manner, and to
reach the target accurately; for details see (Michmi-208
zos, Rossi et al., 2015). By averaging over PM values209
and a weighted sum of the PL values in 3 consecutive210
sections (Fig. 2), the controller adapted to children’s
performance and variability, and challenged them to212
continue to improve. The performance-based adap-213
tive algorithm for the speed, s, and the accuracy, w,
in section J+1, is as follows:
where λs>0
w<0 were the gains of the simple
control loop and:
14 PLsum ≤−1
10 < PLsum ≤−8
8< PLsum ≤−6
6< PLsum ≤−3
3< PLsum 3
3< PLsum 6
6< PLsum 8
8< PLsum 10
10 < PLsum 12
12 < PLsum 14
The challenging component of our games was the
asymmetry of a (PLsum), which aimed to trigger219
patients to improve further but made the task eas-220
ier, yet to a lesser extent, when the performance was221
Fig. 2. Weighted sum of three consecutive PL values for adapting
the game speed and accuracy constraints. PLsum is used for chal-
lenging performance. A window of size 3 is adjusted to each PL
so that the current PL value is weighted by 4, and the previous two
PL values are weighted by 2 and 1, respectively.
2.3. Experimental setup 222
The children wore a modified shoe and a knee 223
brace, to which the robot was attached. Subjects were 224
seated and the knee brace was securely fastened to the 225
chair to fully support the weight of the robot and to 226
ensure that measurements were made in a repeatable 227
posture. A screen was positioned at eye level (Fig. 1c). 228
Ankle position kinematics, with respect to the zero- 229
angle (neutral position), were recorded at 200 Hz 230
sampling frequency and converted to screen pixels 231
for visualization. A DP (IE) movement of the ankle 232
moved the cursor vertically (horizontally); hence the 233
cursor moved in a 2D coordinate system with the 234
origin corresponding to the ankle’s neutral position 235
defined as the sole being at a right angle to the tibia. 236
2.4. Experimental protocols 237
We have so far completed 2 pilot pedi-Anklebot 238
studies that are described in detail elsewhere (Mich- 239
mizos, Rossi et al., 2015; Krebs, Michmizos et al., 240
2016). Briefly, in the first study (discrete movements 241
study - DMS), we recruited 3 impaired children 242
(average age 9 years old) at the “Bambino Ges´
u” 243
Children’s Hospital, Rome, Italy; 2 of the children 244
were diagnosed with cerebral palsy (CP) and the other 245
was diagnosed with a lesion of the common peroneal 246
nerve. In the second study (rhythmic movement – 247
walking pattern study – WPS), we recruited 4 CP 248
children (average age 9 years old) at Blythedale Chil- 249
dren’s Hospital, Valhalla, NY. Enrollment criteria for 250
this study were a) age 6–10 years (based on child 251
size); b) congenital hemiplegia or acquired hemi- 252
plegia with at least 6 months from the acute phase; 253
c) cognitive and visual abilities adequate to under- 254
stand and perform the interactive robotic training; 255
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K.P. Michmizos and H.I. Krebs / Pediatric robotic rehabilitation 5
Table 1
Discrete movement kinematics improvement (DMS). Reported numbers are % changes in average values between admission and discharge
in 3 children (CD-1, CD-2 and CD-3). Metrics are defined in (Michmizos, Rossi et al. 2015)
% Speed Accuracy Robot Robot Smooth Slot Dwell Min Min
change Initiated Assistance Movement Time Time Trajectory Distance
CD-1 51 24 45 80 83 24 100 80 317 205 4 2 476 107 6 2.5 750 100
CD-2 33 29 30 61 73 29 100 61 3850 28 26 2 766 98 8 0 460 55
CD-3 70 5 46 81 100 5 100 81 4700 1000 26 3 53 382 3 4 450 60
d) Tardieu spasticity grade 3 at ankle plantar flexor256
muscles; e) ability to walk independently without the
use of aids or orthoses, f) agreed not to receive focal258
treatment with Botulinum toxin serotype A (BoNT-259
A) for muscle spasticity during the study; g) signed260
consent and assent. Children were excluded if they261
had a) functional surgery; or b) focal treatment with
BoNTA for muscle spasticity in the prior 6 months,263
in their lower extremities. For both studies, the chil-264
dren and their parents gave informed assent and
consent according to the procedure approved by the266
Ethics and Institutional Review Board committee of267
“Bambino Ges´
u” Children’s Hospital, Rome, Italy268
(DMS), the Blythedale’s Institutional Review Board
(WPS) and the Massachusetts Institute of Technology
Committee on the Use of Humans as Experimental271
For both studies, the children were trained twice273
per week for 6 weeks in seated position for a total
of 12 sessions. Training was unilateral focusing on
the most impaired side (even in the case of bilat-
eral impairment). Each robotic training started with
an active-Range of Movement (A-ROM) measure-278
ment by a therapist and 80% of the A-ROM became279
the maximum ROM for the pedi-Anklebot. For the280
DMS study, each child conducted 44 movements per
direction (DP and IE). For the WPS, each child exe-282
cuted 6 blocks of 40 movements each for a total283
of 240 targeted ankle movements employing Noah’s284
Ark or Shipwreck games in DP flexion followed or
preceded by the same number of repetitions for IE
movements. All games were played with the adaptive287
robotic assistance as described elsewhere (Michmi-
zos, Rossi et al., 2015). Since all subjects were naive289
to the task upon enrollment, we selected Noah’s Ark290
and Shipwreck game because they were designed for
the first stages of motor learning, namely the cogni-292
tive, and associative stages, where one may have a293
vague idea of the movement required for a task but294
might not be confident on how to execute that move-295
ment. To ensure a continuous engagement into the296
rehabilitation session, the cognitive status of the chil- 297
dren was continuously assessed by the clinicians and 298
nurses. 299
2.5. Experimental results 300
The DMS examined a large number of metrics 301
assessing the discrete movement kinematics. Inter- 302
estingly, all metrics were improved in all kids. Table 1 303
shows the changes in the average values of the kine- 304
matics metrics between admission and discharge. 305
The results were consistent for both trained direc- 306
tions (DP and IE) with the percent improvements 307
being larger in DP direction than in IE. Overall, at 308
discharge, all kids consistently exhibited less robot- 309
initiated movements, less assistive power from the 310
robot, movements that were smoother and took con- 311
siderably less time to complete in addition to being 312
more accurate. 313
The WPS examined functional tasks that are 314
required in walking. Specifically, it measured the 6- 315
minute walk (6-MWT), which measures the distance 316
the patient can walk in 6 minutes on a flat surface. 317
and the timed-up-and-go (TUG) test, which assesses 318
mobility and balance by measuring the time it takes 319
for a person to stand and walk 3 meters away, turn 320
back, and sit down. Table 2 shows the changes in these 321
two tests at admission and discharge of the protocol. 322
Table 2
Walking Metrics Improvement (WPS). Reported numbers are %
changes in functional walking tests between admission and
discharge in 4 children (CW-1, CW-2, CW-3 and CW-4).
Negative value indicates worsening. The functional tests
were the 6-minute walk (6-MWT) and timed-up-and–go
(TUG) tests. Of notice, CW-1 has bilateral
impairments and training was limited to unilateral
% change 6-MWT TUG
CW-1 –4.2 10.6
CW-2 8.2 9.3
CW-3 21.2 10
CW-4 4.7 11
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6K.P. Michmizos and H.I. Krebs / Pediatric robotic rehabilitation
3. Discussion323
In this paper, we provide a proof of concept for the324
pedi-Anklebot used in two different clinical settings,325
with two different therapeutic targets: discrete ankle
movements and functional walking. Our approach327
for applying therapy to the ankle has a number of328
unique characteristics: First, the therapeutic scheme329
adapts to each kid separately, based on quantitative
measurements of kinematic and kinetic performance.
Second, the therapeutic environment employs con-332
cepts of motor learning, initially designed for the333
upper extremity but recently proved to hold for the
lower limbs as well (Michmizos & Krebs 2014; Mich-335
mizos & Krebs, 2014; Michmizos, Vaisman et al.,336
2014). Third, the robotic therapy targeted specific337
ankle joints and went beyond rhythmic training, con-
trary to the current school of thought that favors339
rhythmic patterns of whole-body movements dur-340
ing partial body weight support treadmill walking;341
a technique that was found to produce limited results
(Duncan, Sullivan et al., 2011). Fourth, targeting of343
discrete movements is a different rehabilitation strat-
egy, compared to the traditional view that a robot345
should imitate the manual therapy and, therefore,346
impose continuous rhythmic walking movements347
(Colombo, Joerg et al., 2000). The results pre-
sented here substantiate new approaches in designing349
the next generation of pediatric neuro-rehabilitation350
robots, as discussed below.351
3.1. The difference between working and
walking our way through the world
The pedi-Anklebot targeted the ankle because of its354
crucial role in human walking and because a deficit355
in foot control is the most common and debilitating356
condition in upper motor neuron disorders involv-
ing the corticospinal tract, such as CP that affects 1358
to 4 per 1,000 live births (Odding, Roebroeck et al.,
2006). However, the extent to which the sensorimo-360
tor control of the LE, in general, and of the ankle,
in particular, resembles that of the UE will influence362
the translation of any method, working hypothesis or363
technology used from the UE to the LE. Following364
this line of research, we have conducted three studies365
on the sensorimotor control of ankle pointing move-366
ments at 3 modeling levels. We first demonstrated367
that a macroscopic law of gross UE motor behavior,
the Fitts’ law, can also be used to described the ankle
movements in both DP and IE direction (Michmi-
zos & Krebs 2014). We then showed that the speed
profiles of the normal ankle movements are remark- 372
ably similar to the speed profiles of the arm and wrist 373
point movements (Michmizos, Vaisman et al., 2014). 374
Interestingly enough, we also found that the reaction 375
time, a metric that can be used for assessing implicit 376
learning, also increases linearly with the number of 377
stimuli, as would be predicted by the Hick-Hyman 378
law in UE (Michmizos & Krebs 2014). 379
However, any straight analogy between the LE and 380
the UE seems to be an oversimplification, especially 381
when one does not take into account the special char- 382
acteristics of the lower limb movements. Since the 383
functionality is not the same, the same neurological 384
cause will have a different functional outcome. In the 385
LE, a common condition that occurs in stroke and CP 386
is a weakness of the dorsiflexor muscles that lift the 387
foot during walking, commonly referred to as “drop 388
foot.” The two major complications of drop foot – 389
slapping of the foot after heel strike (foot slap) and 390
dragging of the toe during swing (toe drag) – present 391
a major challenge to efficient gait since clearing the 392
ground during the swing phase and maintaining ankle 393
stability during the stance phase are essential for effi- 394
cient gait. Another striking observation is that the 395
ankle sensorimotor control in DP and IE is far from 396
being regarded as a natural expansion of controlling 397
the arm or the wrist. We have indicated a statistically 398
significant difference in the lag of ankle response 399
between the DP and IE directions and have attributed 400
this to the stronger cortical projections that the tib- 401
ialis anterior (a main muscle for DP movement) has 402
(Michmizos & Krebs 2014). Therefore, one should 403
carefully study the anatomy, the neurophysiology 404
and the behavioral characteristics of the specific limb 405
prior to designing a therapeutic intervention targeting 406
at it. 407
3.2. Training discrete vs. rhythmic movements 408
The working hypothesis of our rehabilitation 409
robots is based on the model of dynamic primitives, 410
according to which the sensorimotor control of UE 411
and LE can be broken down into three primitives: 412
submovements (i.e., discrete movements), oscilla- 413
tions (i.e., rhythmic movements), and mechanical 414
impedances that are needed for interaction with 415
the physical environment (Hogan & Sternad 2013). 416
Since different brain areas are involved in controlling 417
discrete and rhythmic movements (Schaal, Sternad 418
et al., 2004), it seems reasonable to assume that a 419
rehabilitation device should target discrete and rhyth- 420
mic movements, separately. At least for walking, 421
K.P. Michmizos and H.I. Krebs / Pediatric robotic rehabilitation 7
any normal step includes collision with the pave-422
ment as well as balance and that is why mechanical
impedance should also be targeted as a potential424
therapeutic component. Built upon our rehabilitation425
model, the MIT-Skywalker was recently introduced426
to offer three distinct training modes: discrete move-
ments, rhythmic movements, and balance (Susko,428
Swaminathan et al., 2016). Although a larger clinical429
trial is still pending, there is already accumulating430
evidence that the device can improve clinical and
kinematic measurements, at least for the impaired432
population that has been tested upon.433
3.3. Robotic therapy integrated into an
augmented reality environment435
Despite the promising clinical results with the
robot “assisting as needed” even when movement437
is significantly impaired, the therapeutic intervention438
does not account for the cognitive and perceptual defi-
ciencies that accompany poor coordination and motor440
disorders. Therefore, the optimal habilitation recipe
and how this can be given while keeping the chil-442
dren engaged into the task remain to be determined.
Recently, we have introduced the idea of integrat-444
ing a rehabilitation robot to an augmented reality445
environment where the relevant movement is mir-446
rored to an animated character projected in front of
the child (Kommalapati & Michmizos 2016). We
speculate that the visual observation of one’s own
movements will activate the “mirror neuron system”,450
a brain system underlying the human capacity to learn
by imitation (Gallese, Fadiga et al., 1996; Rizzolatti,
Fadiga et al., 1996; Rizzolatti & Craighero 2004).453
Our rehabilitation algorithm personalizes the diffi-454
culty of the tasks by adapting the difficulty of reaching455
virtual targets on the animated environment through
changing the visual gain between real and animated
movements. Whether this will result to a measurable458
and significant therapeutic outcome remains to be
In summary, the initial results that we report
here support the potential for new neurorehabilita-462
tion methods and robotic devices that augment the463
impaired child’s ability towards an independent and464
productive life. The introduction of adaptive mech-465
anisms into the pedi-Anklebot seems to increase466
the child’s motor response quality in both discrete467
and rhythmic tasks (functional walking). While more
thorough studies are still needed, the results have
raised a number of open questions: What kind of
computational features should we optimize to find the
right responders or get the maximum improvement? 472
What dose intensity should we give to each patient? 473
When should we target a whole body training or a 474
modular approach? How one should decide on the 475
type of a virtual environment? What kind of feedback 476
should we give to the kids? Should we use computer 477
animation to provide proprioceptive feedback during 478
therapy? What constitutes an appropriate set of diffi- 479
culty metrics for our games? Would a type of social 480
interaction during a gameplay benefit the youngsters? 481
Answering these and other questions would also help 482
clinicians and scientists studying the origin of motor 483
learning across the spatial and temporal scales of 484
brain function, and offer novel and highly testable 485
hypotheses for neuro-rehabilitation. The latter would 486
hopefully add new therapeutic avenues to the ones 487
currently pursued. 488
4. Conclusion 489
The robotic rehabilitation of pediatric patients 490
involves unique constraints and, therefore, creates 491
unique challenges in comparison to adult rehabilita- 492
tion. Our robotic device aims to provide an effective 493
therapy to children, by engaging them and fostering 494
their desire to put forth maximal effort in rehabil- 495
itation, as well as growing with them as progress is 496
made. To fully harness the therapeutic power of adap- 497
tation, we need to continue our research on the special 498
characteristics of the sensorimotor control of the tar- 499
geted joints as well as on the differences between 500
rhythmic and discrete movements, as well as mechan- 501
ical impedance training. Being an iterative procedure, 502
this evidence-based design of the robotic therapy will 503
continue to improve our expectations, from chang- 504
ing the behavioral and clinical metrics to making a 505
difference in a child’s life. 506
Conflict of interest 507
None to report. 508
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... The paediatric Anklebot provided intensive task-specific sensorimotor therapy to the ankle of children with motor disabilities to promote motor learning [75] Safety ...
... Finally, motivation is crucial because function recovery is not enough to engage children in the rehabilitation process [75]. Consequently, researchers have used strategies to engage children, like aesthetic designs attractive to the children [26,76] or a virtual environment where they can interact with virtual objects [77,78]. ...
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Children with physical disabilities often have limited performance in daily activities, hindering their physical development, social development and mental health. Therefore, rehabilitation is essential to mitigate the adverse effects of the different causes of physical disabilities and improve independence and quality of life. In the last decade, robotic rehabilitation has shown the potential to augment traditional physical rehabilitation. However, to date, most robotic rehabilitation devices are designed for adult patients who differ in their needs compared to paediatric patients, limiting the devices’ potential because the paediatric patients’ needs are not adequately considered. With this in mind, the current work reviews the existing literature on robotic rehabilitation for children with physical disabilities, intending to summarise how the rehabilitation robots could fulfil children’s needs and inspire researchers to develop new devices. A literature search was conducted utilising the Web of Science, PubMed and Scopus databases. Based on the inclusion–exclusion criteria, 206 publications were included, and 58 robotic devices used by children with a physical disability were identified. Different design factors and the treated conditions using robotic technology were compared. Through the analyses, it was identified that weight, safety, operability and motivation were crucial factors to the successful design of devices for children. The majority of the current devices were used for lower limb rehabilitation. Neurological disorders, in particular cerebral palsy, were the most common conditions for which devices were designed. By far, the most common actuator was the electric motor. Usually, the devices present more than one training strategy being the assistive strategy the most used. The admittance/impedance method is the most popular to interface the robot with the children. Currently, there is a trend on developing exoskeletons, as they can assist children with daily life activities outside of the rehabilitation setting, propitiating a wider adoption of the technology. With this shift in focus, it appears likely that new technologies to actuate the system (e.g. serial elastic actuators) and to detect the intention (e.g. physiological signals) of children as they go about their daily activities will be required.
... 14 Previous platforms were designed with 1 or 2 degrees of freedom (DOF), limiting the functional training available as the ankle moves in 3 planes of motion. [15][16][17][18][19] Zhang et al 14 concluded that to be successful, platform-based ankle robots need to provide effective movement, active assistance, and work in multiple planes of motion to mimic the true ankle joint. However, no current system available has 3 DOF combined with assist-andresist modes. ...
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Purpose: This pilot study assesses the feasibility of using PedBotHome to promote adherence to a home exercise program, the ability of the device to withstand frequent use, and changes in participant ankle mobility.PedBotHome is a robotic ankle device with integrated video game software designed to improve ankle mobility in children with cerebral palsy. Methods: Eight participants enrolled in a 28-day trial of PedBotHome. Ankle strength, range of motion, and plantar flexor spasticity were measured pre- and posttrial. Performance was monitored remotely, and game settings were modified weekly by physical therapists. Results: Four participants met the study goal of 20 days of use. There were statistically significant improvements in ankle strength, spasticity, and range of motion. Conclusions: PedBotHome is a feasible device to engage children with static neurological injuries in ankle home exercise. This pilot study expands the paradigm for future innovative home-based robotic rehabilitation.
... The use of robotic technology for neurorehabilitation has become increasingly important for both adults and children with different motor impairments [1][2][3][4]. Rehabilitation robots have been introduced in the clinical rehabilitation environment tocomplement conventional therapy and improve therapeutic 1184 F. Chrif et al. / Usability evaluation of an interactive leg press training robot for children outcomes, as they can enhance the quantity and the quality of the rehabilitation dose, by increasing the training duration and the number of repetitions and providing more accurate repetition trajectories [5,6]. ...
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Background: The use of robotic technology for neurorehabilitative applications has become increasingly important for adults and children with different motor impairments. Objective: The aim of this study was to evaluate the technical feasibility and usability of a new interactive leg-press training robot that was developed to train leg muscle strength and control, suitable for children with neuromuscular impairments. Methods: An interactive robotic training system was designed and constructed with various control strategies, actuators and force/position sensors to enable the performance of different training modes (passive, active resistance, and exergames). Five paediatric patients, aged between 7 and 16 years (one girl, age 13.0 ± 3.7 years, [mean ± SD]), with different neuromuscular impairments were recruited to participate in this study. Patients evaluated the device based on a user satisfaction questionnaire and Visual Analog Scale (VAS) scores, and therapists evaluated the device with the modified System Usability Scale (SUS). Results: One patient could not perform the training session because of his small knee range of motion. Visual Analog Scale scores were given by the 4 patients who performed the training sessions. All the patients adjudged the training with the interactive device as satisfactory. The average SUS score given by the therapists was 61.2 ± 18.4. Conclusion: This study proposed an interactive lower limb training device for children with different neuromuscular impairments. The device is deemed feasible for paediatric rehabilitation applications, both in terms of technical feasibility and usability acceptance. Both patients and therapists provided positive feedback regarding the training with the device.
... Likewise, the prediction of self-executed movements is important because a significant improvement in motor performance is achieved when training consists solely of voluntary movements 49 . Indeed, the initiation of voluntary movements has been used as a reliable indicator of clinical improvement 50 . Lastly, functional relevance of the targeted movement indicates that an effective therapy should comprise of training across different movement directions 51 . ...
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The effective decoding of movement from non-invasive electroencephalography (EEG) is essential for informing several therapeutic interventions, from neurorehabilitation robots to neural prosthetics. Deep neural networks are most suitable for decoding real-time data but their use in EEG is hindered by the gross classes of motor tasks in the currently available datasets, which are solvable even with network architectures that do not require specialized design considerations. Moreover, the weak association with the underlying neurophysiology limits the generalizability of modern networks for EEG inference. Here, we present a neurophysiologically interpretable 3-dimensional convolutional neural network (3D-CNN) that captured the spatiotemporal dependencies in brain areas that get co-activated during movement. The 3D-CNN received topography-preserving EEG inputs, and predicted complex components of hand movements performed on a plane using a back-drivable rehabilitation robot, namely (a) the reaction time (RT) for responding to stimulus (slow or fast), (b) the mode of movement (active or passive, depending on whether there was an assistive force provided by the apparatus), and (c) the orthogonal directions of the movement (left, right, up, or down). We validated the 3D-CNN on a new dataset that we acquired from an in-house motor experiment, where it achieved average leave-one-subject-out test accuracies of 79.81%, 81.23%, and 82.00% for RT, active vs. passive, and direction classifications, respectively. Our proposed method outperformed the modern 2D-CNN architecture by a range of 1.1% to 6.74% depending on the classification task. Further, we identified the EEG sensors and time segments crucial to the classification decisions of the network, which aligned well with the current neurophysiological knowledge on brain activity in motor planning and execution tasks. Our results demonstrate the importance of biological relevance in networks for an accurate decoding of EEG, suggesting that the real-time classification of other complex brain activities may now be within our reach.
Background: The use of robotic technologies in pediatric rehabilitation has seen a large increase, but with a lack of a comprehensive framework about their effectiveness. Objective: An Italian Consensus Conference has been promoted to develop recommendations on these technologies: definitions and classification criteria of devices, indications and limits of their use in neurological diseases, theoretical models, ethical and legal implications. In this paper, we present the results for the pediatric age. Methods: A systematic search on Cochrane library, PEDro and Pub Med was performed. Papers published up to March 1st, 2020, in English, were included and analyzed using the methodology of the Centre for Evidence-Based Medicine in Oxford, AMSTAR2 and PEDro scales for systematic reviews and RCT, respectively. Results: Some positives aspects emerged in the area of gait: an increased number of children reaching the stance, an improvement in walking distance, speed and endurance. Critical aspects include the heterogeneity of the studied cases, measurements and training protocols. Conclusion: Many studies demonstrate the benefits of robotic training in developmental age. However, it is necessary to increase the number of trials to achieve greater homogeneity between protocols and to confirm the effectiveness of pediatric robotic rehabilitation.
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Pacjenci zarażeni SARS-CoV-2, o lekkim i umiarkowanym przebiegu, leczeni są w warunkach domowych. Coraz częściej, oprócz tradycyjnej farmakoterapii, stosuje się metody alternatywne, w tym olejki eteryczne. Ich składniki aktywne wykazują szereg korzystnych działań. Prześledzenie danych literaturowych na temat użyteczności olejków eterycznych w łagodzeniu objawów SARS-CoV-2 było bezpośrednim celem pracy. Olejki oraz ich składniki badano pod kątem łączenia się z białkami wirusowymi, co wskazało na ich bezpośrednie i celowe działanie przeciwwirusowe. Opisano także przykłady olejków i formy terapeutyczne pozwalające na niwelowanie objawów choroby (zmniejszanie odczucia duszności i objawów ze strony gór-nych dróg oddechowych) oraz rehabilitację oddechową (trening olfaktoryczny). Eukaliptol o działaniu przeciw-drobnoustrojowym i przeciwzapalnym jest tu szczególnie polecanym związkiem. Olejek lawendowy o działaniu redukującym stres i poprawiającym jakość snu wpływa na jakość życia pacjentów. Nie zaleca się stosowania mentolu – może on potencjalnie wpływać na zaburzenia samopostrzegania stopnia nasilenia duszności. Olejki eteryczne, w odpowiednich dawkach nie wykazują działania szkodliwego dla zdrowia. Działając syner-gistycznie z lekami przeciwwirusowymi mogą być przydatne w objawowym leczeniu COVID-19, nie są jednak skuteczne w monoterapii. Wskazuje się rolę aromaterapii w rekonwalescencji pacjentów covidowych.
Background: Spinal cord injury (SCI) results in neurological dysfunction of the spinal cord below the injury. Objective: To explore the immediate and long-term effects of robotic-assisted gait training (RAGT) on the recovery of motor function and walking ability in children with thoracolumbar incomplete SCI. Methods: Twenty-one children with thoracolumbar incomplete SCI were randomly divided into the experimental (n = 11) and control groups (n = 10). The control group received 60 min of conventional physical therapy, and the experimental group received 30 min of RAGT based on 30 minutes of conventional physical therapy. Changes in walking speed and distance, physiological cost index (PCI), lower extremity motor score (LEMS), SCI walking index and centre-of-pressure (COP) envelope area score were observed in both groups of children before and after eight weeks of training. The primary outcome measures were the 10-metre walk test (10MWT) and six-minute walk distance (6MWD) at preferred and maximal speeds. In addition, several other measures were assessed, such as postural control and balance, lower limb strength and energy expenditure. Results: Compared with control group, the self-selected walk speed (SWS), maximum walking speed (MWS), 6MWD, PCI, LEMS, COP, and Walking Index for Spinal Cord injury II (WISCI II) of experimental group were improved after treatment. The 6MWD, PCI, COP, and WISCI II after eight weeks of treatment were improved in experimental group. All indicators were not identical at three different time points when compared between two groups. Pairwise comparisons in experimental group suggested that the SWS, MWS, 6MWD, PCI, LEMS, COP, and WISCI II after treatment were higher than those before treatment. The 6MWD, LEMS, COP, and WISCI II after treatment were higher than at the one-month follow-up appointment. The SWS, PCI, LEMS, COP, and WISCI II at the eight-week follow-up appointment were improved. Conclusion: Robotic-assisted gait training may significantly improve the immediate motor function and walking ability of children with thoracolumbar incomplete SCI.
This work is part of the European project MOTION (Interreg 2 Seas Mers Zeeën), which aims to develop an exoskeleton for children with cerebral palsy (CP). The developed exoskeleton is equipped with a smart garment in order to detect the stress (e.g. physical, physiological) during the rehabilitation. Five different sensors, i.e. electrocardiogram (ECG), respiratory rate (RR), pressure, galvanic skin response (GSR) and textile heat fluxmeter (THF), are integrated into this smart garment for stress detection. This paper focuses on the development of the textile heat fluxmeter. Several researchers used heat fluxmeters in physiological studies to measure the body heat exchanges with the environment. However, the non-permeability of such fluxmeter gives inaccurate measurements in wet condition. Innovative flexible textile heat fluxmeter may detect, analyze, and monitor the heat and mass transfers with minimum disturbance due to its porosity. Moreover, it is desirable to have flexible sensors when they need to be in contact with the human body, in which the flexibility and non-irritability requirements are of utmost importance.
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Purpose: The aim of this guideline is to provide a synopsis of best clinical practices in the rehabilitative care of adults recovering from stroke. Methods: Writing group members were nominated by the committee chair on the basis of their previous work in relevant topic areas and were approved by the American Heart Association (AHA) Stroke Council's Scientific Statement Oversight Committee and the AHA's Manuscript Oversight Committee. The panel reviewed relevant articles on adults using computerized searches of the medical literature through 2014. The evidence is organized within the context of the AHA framework and is classified according to the joint AHA/American College of Cardiology and supplementary AHA methods of classifying the level of certainty and the class and level of evidence. The document underwent extensive AHA internal and external peer review, Stroke Council Leadership review, and Scientific Statements Oversight Committee review before consideration and approval by the AHA Science Advisory and Coordinating Committee. Results: Stroke rehabilitation requires a sustained and coordinated effort from a large team, including the patient and his or her goals, family and friends, other caregivers (eg, personal care attendants), physicians, nurses, physical and occupational therapists, speech-language pathologists, recreation therapists, psychologists, nutritionists, social workers, and others. Communication and coordination among these team members are paramount in maximizing the effectiveness and efficiency of rehabilitation and underlie this entire guideline. Without communication and coordination, isolated efforts to rehabilitate the stroke survivor are unlikely to achieve their full potential. Conclusions: As systems of care evolve in response to healthcare reform efforts, postacute care and rehabilitation are often considered a costly area of care to be trimmed but without recognition of their clinical impact and ability to reduce the risk of downstream medical morbidity resulting from immobility, depression, loss of autonomy, and reduced functional independence. The provision of comprehensive rehabilitation programs with adequate resources, dose, and duration is an essential aspect of stroke care and should be a priority in these redesign efforts.
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The MIT-Skywalker is a novel robotic device developed for the rehabilitation or habilitation of gait and balance after a neurological injury. It represents an embodiment of the concept exhibited by passive walkers for rehabilitation training. Its novelty extends beyond the passive walker quintessence to the unparalleled versatility among lower extremity devices. For example, it affords the potential to implement a novel training approach built upon our working model of movement primitives based on submovements, oscillations, and mechanical impedances. This translates into three distinct training modes: discrete, rhythmic, and balance. The system offers freedom of motion that forces self-directed movement for each of the three modes. This paper will present the technical details of the robotic system as well as a feasibility study done with one adult with stroke and two adults with cerebral palsy. Results of the one-month feasibility study demonstrated that the device is safe and suggested the potential advantages of the three modular training modes that can be added or subtracted to tailor therapy to a particular patient's need. Each participant demonstrated improvement in common clinical and kinematic measurements that must be confirmed in larger randomized control clinical trials.
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This paper presents the pediAnklebot, an impedance-controlled low-friction, backdriveable robotic device developed at the Massachusetts Institute of Technology that trains the ankle of neurologically impaired children of ages 6-10 years old. The design attempts to overcome the known limitations of the lower extremity robotics and the unknown difficulties of what constitutes an appropriate therapeutic interaction with children. The robot’s pilot clinical evaluation is on-going and it incorporates our recent findings on the ankle sensorimotor control in neurologically intact subjects, namely the speed-accuracy tradeoff, the deviation from an ideally smooth ankle trajectory, and the reaction time. We used these concepts to develop the kinematic and kinetic performance metrics that guided the ankle therapy in a similar fashion that we have done for our upper extremity devices. Here we report on the use of the device in at least 9 training sessions for 3 neurologically impaired children. Results demonstrated a statistically significant improvement in the performance metrics assessing explicit and implicit motor learning. Based on these initial results, we are confident that the device will become an effective tool that harnesses plasticity to guide habilitation during childhood.
Full-text available
Little is known about whether our knowledge of how the central nervous system controls the upper extremities, can generalize, and to what extent to the lower limbs. Our continuous efforts to design the ideal adaptive robotic therapy for the lower limbs of stroke patients and children with cerebral palsy highlighted the importance of analyzing and modeling the kinematics of the lower limbs, in general, and those of the ankle joints, in particular. We recruited 15 young healthy adults that performed in total 1,386 visually-evoked, visually-guided and target-directed discrete pointing movements with their ankle in dorsal–plantar and inversion–eversion directions. Using a nonlinear, least-squares error-minimization procedure, we estimated the parameters for 19 models which were initially designed to capture the dynamics of upper limb movements of various complexity. We validated our models based on their ability to reconstruct the experimental data. Our results suggest a remarkable similarity between the top performing models that described the speed profiles of ankle pointing movements and the ones previously found for the upper extremities both during arm reaching and wrist pointing movements. Among the top performers were the support-bounded lognormal and the beta models that have a neurophysiological basis and have been successfully used in upper extremity studies with normal subjects and patients. Our findings suggest that the same model can be applied to different “human” hardware, perhaps revealing a key invariant in human motor control. These findings have a great potential to enhance our rehabilitation efforts in any population with lower extremity deficits by, for example, assessing the level of motor impairment and improvement as well as informing the design of control algorithms for therapeutic ankle robots.
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Reaction time (RT) is one of the most commonly used measures of neurological function and dysfunction. Despite the extensive studies on it, no study has ever examined the RT in the ankle. Twenty-two subjects were recruited to perform simple, 2- and 4-choice RT tasks by visually guiding a cursor inside a rectangular target with their ankle. RT did not change with spatial accuracy constraints imposed by different target widths in the direction of the movement. RT increased as a linear function of potential target stimuli, as would be predicted by Hick–Hyman law. Although the slopes of the regressions were similar, the intercept in dorsal–plantar (DP) direction was significantly smaller than the intercept in inversion–eversion (IE) direction. To explain this difference, we used a hierarchical Bayesian estimation of the Ratcliff’s (Psychol Rev 85:59, 1978) diffusion model parameters and divided processing time into cognitive components. The model gave a good account of RTs, their distribution and accuracy values, and hence provided a testimony that the non-decision processing time (overlap of posterior distributions between DP and IE < 0.045), the boundary separation (overlap of the posterior distributions < 0.1) and the evidence accumulation rate (overlap of the posterior distributions < 0.01) components of the RT accounted for the intercept difference between DP and IE. The model also proposed that there was no systematic change in non-decision processing time or drift rate when spatial accuracy constraints were altered. The results were in agreement with the memory drum hypothesis and could be further justified neurophysiologically by the larger innervation of the muscles controlling DP movements. This study might contribute to assessing deficits in sensorimotor control of the ankle and enlighten a possible target for correction in the framework of our on-going effort to develop robotic therapeutic interventions to the ankle of children with cerebral palsy.
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This study investigated the trade-off between speed and accuracy in pointing movements with the ankle during goal-directed movements in dorsal-plantar (DP) and inversion-eversion (IE). Nine subjects completed a series of discrete pointing movements with the ankle between spatial targets of varying difficulty. Six different target sets were presented, with a range of task difficulty between 2.2 and 3.8 bits of information. Our results demonstrated that for visually evoked, visually guided discrete DP and IE ankle pointing movements, performance can be described by a linear function, as predicted by Fitts' law. These results support our ongoing effort to develop an adaptive algorithm employing the speed-accuracy trade-off concept to control our pediatric anklebot while delivering therapy for children with cerebral palsy.
Conference Paper
We are currently examining the therapeutic efficacy of the pediAnklebot, an impedance-controlled low-friction, back-drivable robotic device that trains the ankle of neurologically impaired children of ages 6-10 years old. In this paper, we present the first clinical results from a small feasibility study involving 4 children with Cerebral Palsy. The children used the pediAnklebot in seated position to train their ankle twice per week for a total of 6 weeks (12 sessions). The initial results indicate an improvement of the ankle’s functions including its pointing abilities and gait speed. The observed clinical outcome reinforces our confidence that the pediAnklebot, driven by our adaptive, assist-as-needed, robotic therapy can harness plasticity to guide habilitation during childhood.
Conference Paper
Sensorimotor therapy gives optimal results when patients are cognitively engaged into highly repetitive tasks, a goal that most children find hard to pursue. This paper presents the key developments of our ongoing effort to design an interactive rehabilitation environment that motivates physically impaired children throughout their therapy. The continuous motivation is achieved by the system adapting fundamental therapeutic components to the performance of each child. The relevant movement is mirrored to an animated character projected in front of the child. We speculate that the visual observation of one’s own movements will activate the “mirror neuron system”, a brain system underlying the human capacity to learn by imitation. Our rehabilitation algorithm personalizes the difficulty of the tasks by adapting the difficulty of reaching virtual targets on the animated environment through changing the visual gain between real and animated movements. To track the sensorimotor performance, we estimated the time required to reach a target. To give a proof of concept for the adaptation of the visual gain, we developed a serious game driven by a Leap Motion device. In addition to becoming a testbed for studying sensorimotor integration and neuroplasticity, the proposed notion of visual gain can be integrated into a highly engaging environment in which physically impaired children will play their way to recovery.
We recorded electrical activity from 532 neurons in the rostral part of inferior area 6 (area F5) of two macaque monkeys. Previous data had shown that neurons of this area discharge during goal-directed hand and mouth movements. We describe here the properties of a newly discovered set of F5 neurons ("mirror neurons', n = 92) all of which became active both when the monkey performed a given action and when it observed a similar action performed by the experimenter. Mirror neurons, in order to be visually triggered, required an interaction between the agent of the action and the object of it. The sight of the agent alone or of the object alone (three-dimensional objects, food) were ineffective. Hand and the mouth were by far the most effective agents. The actions most represented among those activating mirror neurons were grasping, manipulating and placing. In most mirror neurons (92%) there was a clear relation between the visual action they responded to and the motor response they coded. In approximately 30% of mirror neurons the congruence was very strict and the effective observed and executed actions corresponded both in terms of general action (e.g. grasping) and in terms of the way in which that action was executed (e.g. precision grip). We conclude by proposing that mirror neurons form a system for matching observation and execution of motor actions. We discuss the possible role of this system in action recognition and, given the proposed homology between F5 and human Brocca's region, we posit that a matching system, similar to that of mirror neurons exists in humans and could be involved in recognition of actions as well as phonetic gestures.