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A Review on the Rehabilitation Exoskeletons for the Lower Limbs of the Elderly and the Disabled

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Research on the lower limb exoskeleton for rehabilitation have developed rapidly to meet the need of the aging population. The rehabilitation exoskeleton system is a wearable man–machine integrated mechanical device. In recent years, the vigorous development of exoskeletal technology has brought new ideas to the rehabilitation and medical treatment of patients with motion dysfunction, which is expected to help such people complete their daily physiological activities or even reshape their motion function. The rehabilitation exoskeletons conduct assistance based on detecting intention, control algorithm, and high-performance actuators. In this paper, we review rehabilitation exoskeletons from the aspects of the overall design, driving unit, intention perception, compliant control, and efficiency validation. We discussed the complexity and coupling of the man–machine integration system, and we hope to provide a guideline when designing a rehabilitation exoskeleton system for the lower limbs of elderly and disabled patients.
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Citation: Wang, T.; Zhang, B.; Liu, C.;
Liu, T.; Han, Y.; Wang, S.; Ferreira,
J.P.; Dong, W.; Zhang, X. A Review on
the Rehabilitation Exoskeletons for
the Lower Limbs of the Elderly and
the Disabled. Electronics 2022,11, 388.
https://doi.org/10.3390/
electronics11030388
Academic Editor: Enzo
Pasquale Scilingo
Received: 11 November 2021
Accepted: 19 January 2022
Published: 27 January 2022
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electronics
Review
A Review on the Rehabilitation Exoskeletons for the Lower
Limbs of the Elderly and the Disabled
Tao Wang 1, , Bin Zhang 2 ,† , Chenhao Liu 2, Tao Liu 2, Yi Han 3, Shuoyu Wang 3, João P. Ferreira 4, Wei Dong 5,*
and Xiufeng Zhang 6, *
1Nanjing Lishui High-Tech Industry Investment Co., Ltd., 288 Qinhuai Avenue, Lishui District,
Nanjing 211200, China; twang@zlznzz.com
2State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering,
Zhejiang University, Hangzhou 310027, China; zjuzhangbin@zju.edu.cn (B.Z.); 12125056@zju.edu.cn (C.L.);
liutao@zju.edu.cn (T.L.)
3
Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology, 185 Miyanokuchi,
Tosayamada-Cho, Kami 782-8502, Japan; hanyi1719@126.com (Y.H.); wang.shuoyu@kochi-tech.ac.jp (S.W.)
4Institute of Superior of Engineering of Coimbra, Quinta da Nora, 3030-199 Coimbra, Portugal;
ferreira@mail.isec.pt
5School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
6Key Laboratory of Rehabilitation Technical Aids Technology and System of the Ministry of Civil Affairs,
National Research Center for Rehabilitation Technical Aids, Beijing 100176, China
*
Correspondence: dongwei@hit.edu.cn (W.D.); zhangxiufeng@hit.edu.cn (X.Z.); Tel.: +86-186-8689-3076 (X.Z.)
These authors contributed equally to this work.
Abstract:
Research on the lower limb exoskeleton for rehabilitation have developed rapidly to
meet the need of the aging population. The rehabilitation exoskeleton system is a wearable man–
machine integrated mechanical device. In recent years, the vigorous development of exoskeletal
technology has brought new ideas to the rehabilitation and medical treatment of patients with motion
dysfunction, which is expected to help such people complete their daily physiological activities or
even reshape their motion function. The rehabilitation exoskeletons conduct assistance based on
detecting intention, control algorithm, and high-performance actuators. In this paper, we review
rehabilitation exoskeletons from the aspects of the overall design, driving unit, intention perception,
compliant control, and efficiency validation. We discussed the complexity and coupling of the man–
machine integration system, and we hope to provide a guideline when designing a rehabilitation
exoskeleton system for the lower limbs of elderly and disabled patients.
Keywords:
exoskeleton; intention perception; rehabilitation; medical treatment; efficiency evaluation
1. Introduction
At present, there are a large number of people in China who suffer various movement
dysfunctions at different levels caused by stroke, spinal cord injury, and aging. It causes
a dual physical and mental impact on patients themselves and brings a heavy medical
burden to society and family [
1
]. Statistics from the Disabled Persons’ Federation of China
showed that the total number of disabled people had exceeded 85 million, accounting for
approximately 6% of the national population, among which about 24 million people were
suffering from physical disability [
2
], which requires care. Stroke is the deadly diseasewith
a high mortality and disability rate, which has shown explosive recent growth; 85% of
stroke patients lose their walking ability [
3
]. Moreover, trauma and degeneration are
the main causes of paralysis accompanied by motion and sensory dysfunction. There
are 2.5 million people worldwide who have suffered from this disease, and the number
has increased to 130 thousand annually [
4
]. The seventh national census of China shows
that the elderly above 60 account for 18.7% of the population, while the latest forecast of
United Nations population data shows that the elderly population in China will approach
Electronics 2022,11, 388. https://doi.org/10.3390/electronics11030388 https://www.mdpi.com/journal/electronics
Electronics 2022,11, 388 2 of 16
470 million,
accounting for more than 30% of the total population in 2025. This means that
China will become the country with the highest degree of an aging population in the world,
bringing severe challenges to the elderly care service system [5].
Elderly or disabled people with lower limb motor dysfunction, who stay in bed or sit
for a long time, will gradually develop a series of complications, such as pressure ulcers,
muscle atrophy, organ dysfunction, edema, or osteoporosis, which will further worsen
the health condition [
6
]. In order to improve the quality of life of such people, there is
already effective auxiliary walking equipment, such as crutches and wheelchairs, but such
devices are unintelligent and inconvenient to use [
7
] for the people who have lost their
moving ability. On the other hand, appropriate medical treatment is also an essential
procedure, and rehabilitation doctors need to formulate detailed treatment plans according
to the patient’s condition and complete regular procedures of body exercise training [
8
].
However, facing such a large number of patients with movement dysfunction, the relevant
professional technicians will be in short supply with the aging population. The recovery
of patients depends directly on the professional quality and clinical experience of the
technicians. The rehabilitation training process will also seriously consume the physical
energy of the physician, which is not conducive to improving efficiency and saving costs. To
meet the increasing demand, which is combining the professional rehabilitation procedures
with daily assistance, exoskeleton technology has drawn increasing attention to achieve
intelligent training and evaluation.
The vigorous development of exoskeletal technology has brought new ideas regarding
the rehabilitation and medical treatment of patients with motor dysfunction, which is
expected to help such people complete their daily physiological activities or even reshape
their motion function [
9
]. To fully understand the efforts on rehabilitation exoskeletons, this
paper reviews the published works on rehabilitation exoskeletons from 2003 to 2021 in the
Web of Science database [
10
]. When the papers were reviewed, keywords “rehabilitation
exoskeleton” and “lower limb exoskeleton” were combined with “for the disabled” or
“for the elderly” to collect the published literature. The keywords search generated more
than 136 journal and conference papers related to rehabilitation exoskeletons. Papers not
related to the research topic, repetitive articles, and articles related to walking aids for the
blind and children’s rehabilitation aids were excluded. We selected 96 papers to review the
exoskeletons from the point of manufacturing the rehabilitation exoskeletons. Based on
their contents, the key points of these papers can be categorized into five aspects: ergonomic
design, actuation, perception, control, and validation methods.
The exoskeleton systems were identified as wearable man–machine devices made
through anthropomorphic design, providing active assistance to the users according to
their motion intention. This is one of the most promising potential technical studies to deal
with the problems of disabled care and elderly assistance and rehabilitation [
9
]. The design
of rehabilitation exoskeletons should match the ergonomic principles to guarantee that the
system can correspond with the distribution of human joints. To achieve rehabilitation
procedures, the structure of the system should be specified, including sensors, actuators,
and controllers. Based on our surveyed literature, most exoskeletons were actuated by
motors and some artificial actuators such as pneumatic muscles (PMs) [
11
] and shape
memory alloy (SMA) [
12
] were reviewed. The control methods determined the performance
of the exoskeletons conducting assistance and rehabilitation. The control algorithms were
set to maintain human–machine interaction and send the precise control commands to
drive the actuators to perform corresponding auxiliary actions. Most interaction methods
were achieved by feedback control based on detecting the information of the exoskeletons,
the users, or the man–machine coupling system. Many behavioural and physiological
sensors were introduced into the rehabilitation system to represent the status of the man–
machine system, where the behavioural and physiological sensors describe the kinematic
features (such as joint angles, velocity, acceleration, etc.) and human physical status (such
as heart rate, Electromyogram (EMG), electroencephalogram (EEG), etc.). Whether it is
helping patients with daily physiological activities such as walking or performing regular
Electronics 2022,11, 388 3 of 16
rehabilitation training in accordance with the treatment plan, the exoskeleton system could
easily and effectively complete the rehabilitation goals. Finally, it is necessary to evaluate
the effectiveness of the exoskeleton systems and the performance of the assistance and
rehabilitation.
Developed countries represented by the United States, Switzerland, and Canada
started to explore the design and application of rehabilitation medical exoskeleton robots
very early [
13
]. So far, a series of commercial products have been developed to meet
various needs, which has greatly promoted the research process of exoskeleton technology
in helping the elderly and the disabled. During the 11th Five-Year Plan of China, according
to the growing demand for domestic social development (especially the elderly and the
disabled), rehabilitation robots started as a key research project. In the 12th Five-Year
Plan, a further concept was proposed regarding rehabilitation. The 13th Five-Year Plan
carried out a continuous special research plan for rehabilitation robots [
14
]. At present,
both universities and institutes have been committed to the research, and a large number
of rehabilitation exoskeletons have also emerged [15].
The ergonomic design determined the matching performance of the exoskeletons,
which plays a fundamental role to achieve assistance and rehabilitation. The actuators,
sensors, and controllers are the basic elements to conduct motion, perception, and control,
which are the essential parts of the rehabilitation exoskeletons. The validation methods
were designed to confirm the effectiveness of the rehabilitation procedure and the ex-
oskeletons. In this paper, we reviewed the rehabilitation exoskeletons from the aspects
of ergonomic design, actuation, perception, control, and validation. We discussed the
advantages and limitations of the man–machine interaction systems and stated our con-
siderations of designing and developing the rehabilitation exoskeletons in the future. We
hope this paper can provide an overall guideline to design a rehabilitation exoskeleton
system. The contributions of this paper include: (1) as a paper dedicated to reviewing the
rehabilitation exoskeletons, five aspects are listed to summarize state of the art technologies;
(2) the advantages and limitations for every aspect are proposed; (3) the challenges of the
ergonomic design, sensor-based motion perception, actuation, and control were discussed.
We hope this paper could provide a guideline when designing a rehabilitation exoskeleton
system for the lower limbs of the elderly and disabled.
2. Design of the Rehabilitation Exoskeletons
Due to the differences in the degree and location of the loss of motor function of
the wearer, the structural forms of the exoskeleton helping the elderly can be designed
according to the different rehabilitation goals. The unpowered exoskeletons, which do
not contain any powered elements (such as a battery, electric motor, etc.), provided a rich
experience for the ergonomic design because the matching performance determined the
distribution and transmission of the force [
16
]. There were already several representatives of
passive exoskeletons, such as OX, UPRISE, Niudi, and FORTIS [
16
]. The OX was designed
by the Australian Government Department of Defense, and it can transfer two-thirds
of the pressure borne by a soldiers’ shoulders, spine, and legs to the ground. Mawashi
Co. (Quebec, Canada) developed UPRISE transferring 50–80% of the pressure borne by
a soldiers’ shoulders to the ground without interfering with normal motion. UPRISE is
constructed by using high-strength titanium alloy. Niudi Co. (Chongqing, China), LTD
from China proposed a modularized UE that can withstand 70 kg but weighs only 6 kg. The
FORTIS is designed by Lockheed Martin Co. (Bethesda, MD, USA) to help workers carry
heavy tools. The unpowered exoskeletons have great potential in the military, industry,
rescue fields, etc. The passive exoskeletons were well-bionic designed and constructed by
dexterous structure. The ergonomic design of the passive exoskeleton could be referred to
as the design of rehabilitation exoskeletons.
The rehabilitation exoskeletons were designed for the elderly and the disabled who
have been suffering from moving dysfunction. Compared with the power-enhanced
exoskeleton worn for people with normal mobility, the safety and stability of the man–
Electronics 2022,11, 388 4 of 16
machine interaction process must be guaranteed through the special design of the system
itself in structure. To achieve this basic requirement, the overall scheme of the existed
systems was divided into a platform-based exoskeleton, crutches-based exoskeleton, and
self-balanced exoskeleton. The Swiss Locomat [
17
] and American ALEX III [
18
] belong
to the first type of rehabilitation exoskeleton. The users were equipped with lower limb
exoskeletons under the protection of the weight support structure and completed the
walking process on the treadmill, which can safely achieve the intensive training of lower
limb muscle strength, as shown in Figure 1c,d. The second type of system combines
crutches with the exoskeleton. The Israeli ReWalk series [
19
] introduced the users’ upper
limbs to maintain stability by using crutches for patients with lower motion dysfunction, as
shown in Figure 1b. The mode switching buttons were set in the crutches helping the users
adjust movement modes such as tuning walking speed, navigation, and interaction. The
third category uses the balance control algorithm to automatically adjust the movement
posture of the human–machine system, which can operate normally without structural
assistance, such as the New Zealand Rex [18].
Electronics 2022, 10, x FOR PEER REVIEW 4 of 16
The rehabilitation exoskeletons were designed for the elderly and the disabled who
have been suffering from moving dysfunction. Compared with the power-enhanced exo-
skeleton worn for people with normal mobility, the safety and stability of the man–ma-
chine interaction process must be guaranteed through the special design of the system
itself in structure. To achieve this basic requirement, the overall scheme of the existed
systems was divided into a platform-based exoskeleton, crutches-based exoskeleton, and
self-balanced exoskeleton. The Swiss Locomat [17] and American ALEX III [18] belong to
the first type of rehabilitation exoskeleton. The users were equipped with lower limb ex-
oskeletons under the protection of the weight support structure and completed the walk-
ing process on the treadmill, which can safely achieve the intensive training of lower limb
muscle strength, as shown in Figure 1c,d. The second type of system combines crutches
with the exoskeleton. The Israeli ReWalk series [19] introduced the users’ upper limbs to
maintain stability by using crutches for patients with lower motion dysfunction, as shown
in Figure 1b. The mode switching buttons were set in the crutches helping the users adjust
movement modes such as tuning walking speed, navigation, and interaction. The third
category uses the balance control algorithm to automatically adjust the movement posture
of the human–machine system, which can operate normally without structural assistance,
such as the New Zealand Rex [18].
Figure 1. Overall exoskeleton plan for helping the elderly and the disabled. (a) Schematic diagram
to describe the structure of exoskeletons. (b) Based on crutches, reprinted from ref. [19]; (c) Based
on the platform, reprinted from ref. [17]; ; (d) Based on the self-balance design, reprinted from ref.
[18].
Figure 1.
Overall exoskeleton plan for helping the elderly and the disabled. (
a
) Schematic diagram to
describe the structure of exoskeletons. (
b
) Based on crutches, reprinted from ref. [
19
]; (
c
) Based on the
platform, reprinted from ref. [17]; (d) Based on the self-balance design, reprinted from ref. [18].
In terms of active freedom configuration, the existing exoskeletons also showed dif-
ferent characteristics, and the summary of the existing exoskeletons is shown in Table 1.
The working form of the rehabilitation exoskeletons were divided into treadmill based and
over-ground. The treadmill-based exoskeletons constructed a specific trajectory in space,
and the patients’ legs were constrained [
17
]. The over-ground exoskeletons usually allowed
the patients to walk on the ground [
18
,
19
]. Motors were still the common actuators to
Electronics 2022,11, 388 5 of 16
drive the motion of the exoskeleton, which were easily controlled based on the developed
algorithms. The devices were designed based on the level of losing mobility. Most of the
exoskeletons were targeted to the hip joints and could assist the patient to walk based
on balance control. Some exoskeletons introduced crutches to avoid a tumble. However,
there is still a lacking of standard validation methods to confirm the effectiveness of the
exoskeletons. Some systems drive a single joint such as the knee and ankle, and the wearer
often participates in a fixed posture to complete daily physical activities such as walking.
In order to enable the exoskeleton to assist patients with basic gait and active hip and
knee, such as Indego of Parker Hannifin Corporation [
20
23
], ROBIN of Korea Industrial
Technology Institute of Parker Hannifin [
24
,
25
] and MINDWALKER of Delft Polytechnic
University in the Netherlands. In addition [
26
], a few systems set multiple active joint
mobilities to achieve self-balance or motor flexibility. For example, Rex of Rex Bionics, New
Zealand and ATLAS 2020 [
27
], developed by the Spanish National Research Council, have
10 active degrees of freedom.
Table 1.
Summary of existing exoskeletons and their related technical details (treadmill-based
exoskeletons: The man–machine system operates on the treadmill. Over-ground: The man-machine
system can operate on the ground).
Devices Working Form Actuator Control Strategies Target Parts of
Human
Keywords of
Validation Methods
Lokomat [17]Treadmill based
exoskeleton Motor Position and impedance Hip and knee EM activity
ALEX III [18] Over-ground Motor Balance and impedance Hip, knee and ankle Reshape walking
ability
ReWalk [19] Over-ground Motor Force and impedance Hip and knee Walking assistance
Indego [23] Over-ground Motor Position and
force control Hip and knee Walking assistance
Mindwalker [26] Over-ground SEA-motor
Electroencephalogram
(EEG)-based
position control
Hip, knee and ankle Reshape walking
ability
BLEEX [28] Over-ground Hydraulic Cylinders Position and
force control Hip, knee and ankle Reshape walking
ability
Ankle-foot
Exoskeleton [29]Over-ground Pneumatic Muscle Position and
force control Ankle Reduction in
Metabolic (21%)
LOPES [30]Treadmill based
exoskeleton
Bowden Cable-based
Series Elastic Actuator Torque Hip, knee and ankle Improving the control
compliance
Rex [31] Over-ground Motor Balance and
force control Hip, knee and ankle Reshape walking
ability
HAL [32] Over-ground Motor
EMG-based force control
Hip, knee and ankle Walking assistance
The wearable form of the rehabilitation exoskeletons guarantees the exoskeletons can
assist in an ergonomic way. The exoskeletons must be designed based on the distribution
of the humanoid characteristics such as muscle distribution, tendon-based transmission,
and skeleton-based support. The position of the actuators should be placed along with
human joints. The passive exoskeletons applied in military and industry fields showed great
development in ergonomic design. Unlike the unpowered exoskeletons, the external energy
should be introduced into the man-machine system because the rehabilitation exoskeletons
are targeted to reshape or maintain the mobility of the people with moving dysfunction.
Therefore, the rehabilitation exoskeletons should be powered exoskeletons, including
actuators, sensors, and control methods. In our surveyed literature, the motors were the
most traditional actuators used in rehabilitation systems, which have been developed for
decades. Some novel actuators were introduced into the rehabilitation exoskeletons, such
as PM and SMA, inspired by their bionic characteristics.
Electronics 2022,11, 388 6 of 16
3. Actuation
The joint actuators belong to the execution part of the exoskeleton movement, deliv-
ering the desired power to achieve the auxiliary movement. The moving performance
was determined by key characteristics such as the power effect, composition shape, and
response speed of the actuators. In terms of the current technology of the actuators of
exoskeletons for the elderly and the disabled, it can be divided into three aspects motor
drive, air pressure drive, and functional electric stimulation based on surveyed papers.
Motor-driven exoskeleton drives the system joints by a straight or rotating motor. Most
rehabilitation training equipment with compact structure and fast response was driven by
electric motors [
33
37
], as illustrated in Figure 2b. Meanwhile, the structure of the reha-
bilitation exoskeletons was bulky because of the big batteries and motors.
Galle et al. [29]
proposed a powered ankle–foot exoskeleton to reduce the metabolic cost which is driven
by pneumatic artificial muscle, as shown in Figure 2b. Timing control was optimized
and implemented, and the experimental results showed a 21% reduction in metabolic
cost. However, prolonged rehabilitation training causes muscle fatigue, such as in the US
Vanderbilt system [
38
] (Figure 2c). Similar to the PM-actuated exoskeletons, the hydraulic
exoskeletons depended on the pressure supplies [
28
]. The electrohydraulic actuator in-
cluded a motor, gear pump, and antagonistic installed cylinders [
39
]. The cylinders were
controlled by servo valves and powered by combustion engines or electric motors.
Electronics 2022, 10, x FOR PEER REVIEW 7 of 16
Figure 2. Exoskeleton’s actuators. (a) Motor drive, adapted from ref. [33]; (b) Air pressure drive
reprinted from ref. [29]; (c) Self muscle drive, reprinted from ref. [40].
In addition, new driving solutions for joint assistance are also being explored and
developed. Chinese Academy of Sciences applies magnetic rheological actuator to robot
rehabilitation system, which can act as a brake or clutch according to the working state of
the system (human activity mode/manual activation mode) for energy consumption sav-
ing [41]. The University of Carlos III introduced the design, test, and analysis of SMA
drives under various configurations and explained the feasibility of the method in soft
robots and light exoskeletons [42].
The electric motors were still the most used actuators for the rehabilitation exoskele-
tons. Generally, the motors increase the torque by decreasing the rotation speed by the
reduction boxes. That is how the electric motors were limited by requiring transmission
elements to convert their high-speed, low-torque output features to low-speed and high-
torque features [30]. The rehabilitation exoskeletons could provide a powerful force to lift
users’ body and keep balance. However, the rehabilitation exoskeletons were of large vol-
ume because of the motors, reducers, and batteries which made the system bulky and
nonflexible. Therefore, there was a tradeoff between the flexible system and powerful out-
put force. For the rehabilitation process, the movements of rehabilitation were achieved
slowly to guarantee safety during training. It implied that the motors were suited to assist
people with slow speed, which was appropriate for the disabled and the elderly.
The PMs were studied for decades from modelling, design, and control [43,44]. The
PMs were compliant actuators mimicking human muscles, which were lightweight, had
a high power-to-weight ratio, and were compliant [45]. However, there was an inevitable
hysteresis between the inflation and deflation process. The hydraulic actuators were se-
lected to drive exoskeletons because of their high-specific power [39], high-force output
[28], wide control bandwidth, smooth actuation [46] etc. However, a significant limitation
of the pneumatic and hydraulic actuators was the dependence on non-portable pressure
supplies. Both the pumps and air compressors were too heavy and large to carry. Their
applications were limited to the platform-based rehabilitation fields with no or low port-
ability.
The other novel actuators were proposed and applied to the rehabilitation system.
The SMA-actuated soft exoskeletons achieved finger motions. Due to the limited scale of
the output force, novel actuators were suitable for precise rehabilitation with a small mo-
tion range. There is still a long road to transfer the novel actuators from lab to prototype.
Figure 2.
Exoskeleton’s actuators. (
a
) Motor drive, adapted from ref. [
33
]; (
b
) Air pressure drive
reprinted from ref. [29]; (c) Self muscle drive, reprinted from ref. [40].
In addition, new driving solutions for joint assistance are also being explored and
developed. Chinese Academy of Sciences applies magnetic rheological actuator to robot
rehabilitation system, which can act as a brake or clutch according to the working state
of the system (human activity mode/manual activation mode) for energy consumption
saving [
41
]. The University of Carlos III introduced the design, test, and analysis of SMA
drives under various configurations and explained the feasibility of the method in soft
robots and light exoskeletons [42].
The electric motors were still the most used actuators for the rehabilitation exoskele-
tons. Generally, the motors increase the torque by decreasing the rotation speed by the
reduction boxes. That is how the electric motors were limited by requiring transmission
elements to convert their high-speed, low-torque output features to low-speed and high-
torque features [
30
]. The rehabilitation exoskeletons could provide a powerful force to
lift users’ body and keep balance. However, the rehabilitation exoskeletons were of large
volume because of the motors, reducers, and batteries which made the system bulky and
nonflexible. Therefore, there was a tradeoff between the flexible system and powerful
output force. For the rehabilitation process, the movements of rehabilitation were achieved
Electronics 2022,11, 388 7 of 16
slowly to guarantee safety during training. It implied that the motors were suited to assist
people with slow speed, which was appropriate for the disabled and the elderly.
The PMs were studied for decades from modelling, design, and control [
43
,
44
]. The
PMs were compliant actuators mimicking human muscles, which were lightweight, had a
high power-to-weight ratio, and were compliant [
45
]. However, there was an inevitable hys-
teresis between the inflation and deflation process. The hydraulic actuators were selected
to drive exoskeletons because of their high-specific power [
39
], high-force output [
28
], wide
control bandwidth, smooth actuation [
46
] etc. However, a significant limitation of the
pneumatic and hydraulic actuators was the dependence on non-portable pressure supplies.
Both the pumps and air compressors were too heavy and large to carry. Their applications
were limited to the platform-based rehabilitation fields with no or low portability.
The other novel actuators were proposed and applied to the rehabilitation system. The
SMA-actuated soft exoskeletons achieved finger motions. Due to the limited scale of the
output force, novel actuators were suitable for precise rehabilitation with a small motion
range. There is still a long road to transfer the novel actuators from lab to prototype.
4. Motion Intention Perception
Essentially, every person has a unique gait pattern, and it is inaccurate to set a fixed
gait pattern [
38
]. Therefore, it is necessary to percept human motion to provide feedback to
the exoskeleton system. Human motion intention recognition is involved in obtaining man–
machine interaction and state information, data fusion algorithm to achieve the purpose of
human motion, or even predict the human motion based on multiply sensors.
According to the difference in intention information acquisition mode, it can be divided
into three intention perception methods based on motion signal, biological signal and mixed
man–machine hybrid signal [
38
]. The motion signals described kinematic and dynamic
characteristics such as motion acceleration, walking speed, joint angles etc., which can be
measured by the gyros or accelerators. The biological signals represented the physiological
information such as muscle fatigue, neural activation, etc., which can be measured by EMG,
EEG, etc. The man–machine hybrid signals described the interaction forces.
The first method had been widely used in typical exoskeletal systems such as the
LOPES [
47
] American eLEGs [
48
] through conventional sensors distributed in man–machine
connections or system motor parts, such as an inertial measurement unit mounted on the
limb, a contact force sensor in insoles. The second method could effectively reduce the
hysteresis of intention perception based on extracting and processing EEG or myography
data. For example, the University of Houston used non-invasive brain-computer interface
technology to control the Neuro Rex exoskeleton in real-time, explain the wearer’s intention
through EEG signals and finally achieve the goal of assisting paraplegic patients to com-
plete walking independently [
31
]. The HAL exoskeleton developed by the University of
Tsukuba in Japan can detect and obtain electrical signals generated by muscle movement on
the skin surface, which was processed as input to the system control [
32
]. The third method
comprehensively considers the advantages and disadvantages of the above two methods
and establishes a man–machine sensor network to comprehensively utilize biological and
motion signals. The high reliability and low latency of intention perception have now
become one of the focuses of research on exoskeleton technology.
A single sensing data can only reflect limited information of the man-machine inter-
action process. It requires the fusion processing of multimodal information of different
sources, different levels and different manifestations to ensure the speed and accuracy
of intention perception. For data fusion algorithms, according to the difference of data
processing levels, it can be divided into data level, feature level, and decision level fusion.
More common methods include D-S evidence theory, artificial neural network, adaptive
weighted average, Bayesian estimation, fuzzy set theory, etc. For example, Northwestern
Industrial University has achieved data fusion of EEG and EMG through D-S (Demp-
ster/Shafer) evidence theory and backpropagation neural network [
49
]. The integration
Electronics 2022,11, 388 8 of 16
of the data collected by the three sensors improves the recognition accuracy of various
motion modes.
Human motion information has been drawing researchers’ attention from the aspects
of the portable and wearable form, high accuracy, and low latency. Fortunately, the motion
sensors can be manufactured into tiny types based on the current semi-conductor develop-
ment. However, the accuracy of the motion recognition was still limited. The most popular
physiological information was represented by EEG and EMG, depicting the command from
the brain and execution from muscles [
31
,
32
]. Moreover, there were no non-invasive sen-
sors with a high signal–noise ratio measuring the intention information [
50
]. The invasive
sensors showed great potential in improving signal quality, but it is still unclear whether
the invasive sensors interfere with normal human motion. MINDWALKER combined the
EMG and EEG to extract the motion features to improve the accuracy [26,51,52].
Besides, motion intention could be obtained by the kinematics parameters. Indego [
23
]
introduced inertia measurement units (IMU) to recognize gait patterns. Then, they tuned
the center of pressure to track the desired movements. Peruzzi et al. [
53
] implemented
gait evaluation based on multiple IMUs. Integrating was conducted to obtain the velocity
and displacement. However, the IMUs-based motion detection would introduce inevitable
errors when conducting integration. Wang et al. [
54
,
55
] implemented zero velocity state
detection by judging the difference between the forward acceleration measured by the
accelerator and the forward acceleration derived by the differential of angular velocity
measured by gyros.
The most efficient sensors with a high signal–noise ratio and low latency represented
the motion behind the human, which introduced inevitable latency of the man–machine
system. Motion prediction based on kinematic and dynamic information could solve the
problem essentially. It is still feasible to use the current sensors to conduct perception
during rehabilitation because the rehabilitation process was usually slow-speed, and the
latency of the sensors was acceptable in the slow process of rehabilitation.
5. Control Methods
The exoskeleton compliant control strategy is based on the result of intention percep-
tion. Controlling the joints to assist the human body in accordance with the wearer’s motion
intention or the rehabilitation physician’s plan was key to ensure that the system generated
the desired motion and produced auxiliary effects. Li et al. sorted the control strategies
for lower limb rehabilitation exoskeletons with eight categories [
56
]. At present, common
control algorithms for helping the elderly and the disabled mainly include gait trajectory
planning, impedance/guide control, biological signal-based control algorithm, etc.
The trajectory planning control was usually used to perform movement tasks when
humans lost the motor ability completely and conducted passive rehabilitation at the early
stage of damage [
57
]. In the gait trajectory planning algorithm, the exoskeleton joints
were controlled to produce periodic motions according to the pre-designed path, which
simulated the gait of humans completing daily activities achieving the coordination of
human and machine actions. The reference movement trajectory can be set in a variety
of ways. Firstly, the gait trajectory playback strategy that directly uses healthy human
gait parameters was widely used in rehabilitation medical exoskeleton. Systems such
as WPAL [
58
,
59
] in Japan and Mina [
60
,
61
] in the United States can collect gait data of
normal wearers and reproduce the movement process when assisting patients. Secondly,
a mathematical model-based gait trajectory generation method can also be employed
to calculate the required motion parameters through related theories. Rex from New
Zealand generated a gait based on the ZMP model so that the system had self-balancing
ability. ATLAS in Spain planned the corresponding motion trajectory based on the inverted
pendulum model and calculated the key parameters such as step length and step height
required to complete the desired gait [62].
Furthermore, to activate the muscle participation in the rehabilitation process and achieve
compliant interaction torque and voluntary muscle torque, the impedance/admittance model
Electronics 2022,11, 388 9 of 16
was established to realize the mixed control of the force and position of the joint motion. The
impedance control could provide assistance that is proportional to the difference between
the human limb and the given trajectory [
63
,
64
]. McGill University in Canada designed a
new adaptive impedance control strategy, which combined backstepping control, time delay
estimation, and interference observer, improving the effect of passive assisted rehabilitation
training [
65
]. The University of Twente in the Netherlands had designed and verified the
admittance controller on the LOPES II exoskeleton, which could generate the gait trajectory
of the impaired based on the healthy leg [66].
The most classic biology-based control methods were based on EMG and EEG [
57
].
Both of them control the exoskeletons based on the direct motion intention [
67
,
68
]. The
control algorithm based on biological information analyzed the control input required for
the movement of the exoskeleton on the basis of collecting and analyzing the bioelectric
signal of the human body. The Italian Institute of Technology combined the Hill muscle
model and EMG signals to estimate the driving torque required for the knee joint to
complete the exercise in real-time [
69
]. The University of Michigan in the United States used
an adaptive gain proportional EMG controller for ankle joint assistance, relying on dynamic
gain to map the wearer’s muscle activity to actuation control signals. The experimental
trials showed that the system significantly enhanced ankle strength and reduced metabolic
consumption [
70
]. EEG-based control is manipulating the exoskeletons based on the brain–
computer interface (BCI). Evidence has shown that a patient with tetraplegia could be able
to control an exoskeleton by using BCI [
71
]. Vouga et al. [
72
] enabled a monkey wearing
an exoskeleton to track the cursor on a screen based on continuous regression methods.
EEG parsing has been the hot research for decades, and they usually resorted to a black
box model. EEG has shown great potential in controlling rehabilitation exoskeletons [73].
The interaction control theory has been developed for a long time, and it has been
rather mature for the rehabilitation exoskeletons during one rehabilitation process. There
was no need to demand the real-time performance of the control methods because the
rehabilitation process was usually reduced to a slow process [
9
]. However, there was lacking
rehabilitation strategy control which usually was made by the doctors. The rehabilitation
strategy is to set the rehabilitation control with different groups of parameters related
to users’ status. The optimization methods should be implemented to select the best
parameters based on the judgement of the rehabilitation stage.
6. Validation of the Rehabilitation Exoskeleton
Quantitative evaluation of the auxiliary effect of the exoskeleton was necessary to
test and optimize the system. The evaluation indicators need to be determined according
to the requirements of rehabilitation training. The efficiency evaluation of rehabilitation
exoskeletons can be divided into task-based evaluation, kinematic and kinetics evaluation,
and interaction evaluation. In task-based evaluation, walking speed and walking distance
are direct indicators of the training results, and the corresponding data can be obtained
through the 5 min walking test (5MWT) [
9
], 6 min walking test (6MWT), 10 m walking test
(10MWT) [
74
], and timed up and go (TUG). Besides, endurance [
75
], versatility [
76
], and
max speed [
77
] were used to evaluate the performance of the rehabilitation exoskeletons
under specific tasks.
The validation methods for rehabilitation exoskeletons focuses on sensors used for
biomechanics and energetics measurements. In general, kinematic and dynamic measure-
ment was used to evaluate the flexibility of the rehabilitation exoskeletons and to predict
energy expenditure indirectly. The most popular kinematic parameters were used to vali-
date the exoskeletons were joint angular trajectories, range of motion (ROM), speed, and
COM position [
9
]. Joint torque output [
78
], peak power [
79
], and maximal torque [
80
]
were used to test the validation of the proposed exoskeletons. Metabolic cost measurement
represented how much energy was saved by the rehabilitation exoskeletons. The EMG
signal represented the activity of the muscle, which can be used to describe the fatigue of
the muscles [
74
]. Kinematic parameters describe the changes of displacement in linear or
Electronics 2022,11, 388 10 of 16
angular position and their derivatives, such as linear velocity, linear acceleration, angular
velocity, and angular acceleration. They can be obtained by the camera-based recognizing
and wearable recognizing system. Kinetics aims to study forces that affect human motion.
These forces can change the linear or angular motions. Force data can be obtained directly
by using force and torque sensors. GRF is the representation of the human body’s impact
on the ground measured by force plates, which can be used to analyze the force provided by
exoskeletons. The energy for human motions comes from the chemical energy by digesting
food, and it flows in three directions: entropy, maintenance, and muscle energy. The energy
of metabolic cost is part of muscle energy, and it can be measured indirectly by recording
respiratory flow, respiratory flow rate, heart rate, muscle activity, etc.
Comfort reflected the subjective sense of patient interaction with the device. Generally,
we collected the feedback about comfort based on the questionnaire. The strategies of
online detection of physiological data such as heart rate and oxygen consumption can
also be used to intuitively reflect the physiological state of the human body. Besides, the
ergonomic parameters determined the matching performance when humans wore the
exoskeletons, which represented the effectiveness of the design [
9
]. However, the current
evaluation methods were good at confirming the effectiveness of the exoskeletons, but they
failed to confirm the effectiveness of the rehabilitation process. Clinically, doctors adjust the
rehabilitation process based on the score-based evaluation methods, which is currently the
golden standard [
81
]. The multi-information collected by the sensors should be introduced
into the evaluation process to confirm the rehabilitation stage.
7. Discussion and Conclusions
At present, countries all over the world have achieved considerable research results
concerningexoskeleton technology for rehabilitation medical treatment [
9
]. Prototypes
and commercial products with different forms and functions are emerging, bringing new
ways to help the rehabilitation of the elderly and the disabled. However, in terms of the
current technical conditions, it is still facing serious challenges to realize the comprehensive
promotion of the exoskeleton in the social rehabilitation service system.
1.
The matching performance between the exoskeletons and the human body is signifi-
cantly low. The exoskeleton system with more active degrees of freedom has better
flexibility, but complex structural composition and hardware lines affect the overall
performance of the system. The most popular ergonomic indicators were human-robot
relative position, interface displacements, anthropometric database percentiles, and
adaptability to different height ranges [
82
]. The joints of the human body and exoskele-
ton have obvious rotation centers misalignment during movement, which will reduce
man-machine interaction. The coupling system may be deformed and misaligned
during the interaction, which may reduce the power-assisted effect. Problems similar
to the above are widespread in existing systems and severely disrupt ergonomics. To
make the wearable exoskeletons more comfort, the unpowered exoskeletons inspired
the novel design of rehabilitation exoskeletons. The materials and manufacturing
methods for lower limb exoskeletons are important because they guarantee a safe and
ergonomically comfortable interface with the human [83,84].
2.
Sensor-based motion feedback is the basis of exoskeleton controlling and rehabilita-
tion [
56
]. The joint angle and interaction torque were the frequently used feedback
in most studies. The joint angle can be used to describe the difference between the
given trajectory and output and calculate the force by joint angle deviation [
85
], the
impedance by derivation of the ankle joint [
86
]. The interaction torque was usually
used to generate real-time trajectory [
87
] and provided reference to correct the tra-
jectory [
88
]. The recognition and prediction of human movement intention are not
accurate enough. The motion intention is estimated by the mechanical signal obtained
by the sensor; although the result is reliable and stable, there is a large hysteresis which
is generated by the signal conversion and decoding process [
89
]. The human intention
based on biological signal analysis has good timeliness, but the data is unstable, and
Electronics 2022,11, 388 11 of 16
the use process is cumbersome. Therefore, it is necessary to set up a steady communi-
cation pipeline between the rehabilitation exoskeletons and humans. Moreover, there
were many kinds of existing data fusion algorithms such as radial basis function neural
networks [
90
], convolutional neural networks [
91
], musculoskeletal model [
92
], etc.,
but motion mode recognition is often difficult to meet the requirements of safety and
reliability accuracy. Previous work has proposed machine learning-based predictors
based on EMG, kinetics, and kinematics to estimate the desired motion intention.
More recently, several researchers have explored using teleceptive sensing of terrain
to improve the prediction of desired locomotion [
93
]. The above difficulties are urgent
problems to be solved in human intention recognition and prediction. It is feasible to
combine the physical model of human motion with the motion data to achieve fast
and stable intention perception [
93
]. The body domain network is designed to obtain
the information of human body movement, physical parameters and state.
3.
Lightweight and high power/weight ratios of driving units are difficult to achieve.
Existing exoskeletons’ actuators are often with lower power/weight ratios, and they
have large volumes and mass, such as Lokomat [
63
] and ALEX [
18
], resulting in large
and bloated overall structural forms. Hydraulic [
39
] and pneumatic actuators [
11
]
improved the power/weight ratio but introduced non-portable pressure supplies
and control difficulties. The series elastic actuators combined the performance of
easy to control and the compliant features [
67
]. However, it is necessary to explore
more effective driving forms as well as innovative design and optimization methods
of high-power density driving units. A permanent magnet servo motor should be
designed by using conservative optimization design methods to realize the lightweight
of permanent magnet servo motor [
94
]. The speed closed-loop control strategy and
position closed-loop control strategy should be designed to drive the permanent
magnet motor to achieve high precision control.
4.
The deviation between system motion control and human motion is prominent. The
strong autonomy of human motion, the strong coupling of man-machine interaction,
and the complexity of the system model have made it difficult for many control
algorithms to achieve the goal of man-machine coordination and interaction [
56
]. The
exoskeleton system should meet the needs of the wearer to complete all kinds of
basic movements and basic movement transformation. For the passive rehabilitation
process, the trajectory-based control is enough to replay the predefined trajectory [
60
].
But the predefined trajectory is not suitable for different individuals. Introducing
human motion intention input into man-machine interaction control was an effective
method to achieve more dexterous in assisting human motion [
95
]. Dynamic control
strategy should be implemented in the rehabilitation system, and the stability should
be confirmed based on real-time state detection and stability criteria. Dynamic control
involved the dynamic modelling of the system, for example, a simple mass-spring-
damper model to characterize series elastic actuator [
96
], actuated dynamic model [
97
],
and hybrid dynamic model [
98
]. Finally, optimization control methods [
99
] should be
introduced to ensure the reliability and consistency of the rehabilitation.
A number of typical products, such as Lokomat [
17
], Rewalk [
19
], HAL [
32
], etc., have
been successfully developed, and application verification has been initially carried out.
However, due to the difficulty of lightweight design, weak motion intention identifica-
tion ability and poor motion control, it is difficult to obtain the qualitative efficiency to
improve the existing exoskeleton assistance. It does not have the technical level of system
lightweight, accurate identification and smooth motion, which restricts the promotion
and application of such exoskeletons. Therefore, it is urgent to study high torque density
motor lightweight driving system design theory and method. The multi-mode human
movement biological information decoding and transmission mechanism should be re-
vealed [
92
], and a multi-source body and exoskeleton coordination movement compliant
control strategy need to be established. The final goal is to solve the key scientific problems
in the engineering application of the exoskeleton robot for the elderly and the disabled and
Electronics 2022,11, 388 12 of 16
provide the theoretical foundation and technical support for the development of wearable
electromechanical systems.
Author Contributions:
Conceptualization, W.D. and X.Z.; methodology, T.W. and Y.H.; validation,
T.L., S.W. and J.P.F.; writing—original draft preparation, B.Z. and C.L.; writing—review and editing,
T.W. and B.Z. All authors have read and agreed to the published version of the manuscript.
Funding:
This work was supported in part by the National Natural Science Foundation of China
under Grant U1913601, 52175033, and U21A20120, Zhejiang Provincial Natural Science Foundation
of China: LZ20E050002, State Key La-boratory of Fluid Power and Mechatronic Systems (Grant No.
GZKF-202101), and DongGuan Innovative Research Team Program (2020607202006).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments:
We are grateful to Ning Zhang (Key Laboratory of Rehabilitation Technical Aids
Technology and System of the Ministry of Civil Affairs, National Research Center for Rehabilitation
Technical Aids, Beijing 100176, China, zhangning@nrcrta.cn) who made profound contributions for
the project works.
Conflicts of Interest: The authors declare no conflict of interest.
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... The exoskeletons are actuated either through external power or by mechanical means. The control system, which sends signals to these actuators, based on the communication between the exoskeleton and B S. Arunkumar arunkumars@am.amrita.edu 1 Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam 690525, India the wearer, further enhances the performance of exoskeleton [3]. ...
... While few articles have discussed the various actuation types, control strategies, materials, and manufacturing methods employed in LLEs [2,11]. A group of reviews has surveyed the application of LLEs for rehabilitation purposes, strength augmentation, locomotion assistance, clinical validation, the complexity of human-machine interaction [3,[12][13][14][15][16], or for a particular disease like stroke [17,18] or spinal cord injury (SCI) [19,20]. ...
... Relative to other reviews which focuses on specific topics of the LLE, this work examines indepth its various aspects such as design features, actuation types, control methods, materials, manufacturing methods and applications in the areas of manufacturing and rehabilitation. The main contribution of this work is focused towards addressing the following questions: (1) what are the design, actuation, and modern control strategies adopted in LLEs? (2) what are the materials and manufacturing methods used for LLEs? (3) what are the benefits and hazards for exoskeleton wearers? (4) what is the efficacy of LLEs in the area of rehabilitation? ...
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... The spatial force applied by body i to its successor body j G A 10 × 1 vector represents the gravity effects of the user multibody dynamics systems I i Spatial moment of inertia of body i J A L , J A R Robot's left and right ankle Jacobian J F RF Jacobian of the contact point J s Jacobian of saddle force applying point l 1 The radius of the saddle of the robot l 3 , l 2 The length of the shank and thigh of the robot M Represents a 10 × 10 inertia matrix of the user multibody dynamics systems i P P i The translation vector from P i to i q Position of the model joints in joint spacė q Velocity of the model joints in joint spacë q Acceleration of the model joints in joint space i R P i The rotation matrix from P i to i S robot Robot model switch parameter S user User's foot switch sensor v i Spatial velocity of body i X A 6 × 6 transfer matrix from one coordinate system to another X ankle X coordinate of the robot ankle in Cartesian workspace X f eet Positions of the robot or user ankles in workspace stance_f oot X H J Force transfer matrices from the user hypothetical joint to stance foot X saddle X coordinate of the robot saddle in Cartesian workspace X seat Positions of the robot saddle in workspace vẌ seat ...
... As statistics indicate a rise in both the elderly population and mobility impairments [1], more attention is being given to this field, leading to the rapid development of devices that cater to the needs of the elderly population [2]. Among these devices are lower limb exoskeletons, which have different shapes and manufacturing strategies depending on their construction goals. ...
... Whether in robotics, physics, or automotive engineering, Plücker coordinates stand as a powerful tool for understanding and manipulating the motion of objects in three-dimensional space [45]. 2 Plücker coordinates. ...
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With the widespread implementation of robotics exoskeletons in rehabilitation, modeling and dynamics analysis of such highly nonlinear coupled systems has become significantly important. In this paper, a swift numerical human–robot dynamics modeling has been developed to achieve accurate and realistic interpretation. This takes into consideration the separation and impact between multiple bodies for rehabilitation planning. To this end, first, a novel parallel algorithm combined with sequential interaction conditions is proposed based on the numerical recursive Newton–Euler method. The approach begins by deriving separated numerical models for the complicated system: i.e. both the human and the robot. These models are then augmented, with a primary focus on reducing the error of the interaction conditions, including forces and positions. The accuracy of the proposed model, with a computational complexity of O(n), is assessed by comparing to a previously validated nonrecursive analytical model with a higher computational complexity of O(n^4). Additionally, the quality of the connection between the human and the robot is assessed to establish a suitable control objective and an effective interaction strategy for rehabilitation planning. The study employs a lower-limb walking assistive robot developed in the ARAS lab (RoboWalk) to validate the proposed method. The algorithm is empirically implemented on the RoboWalk test stand, ensuring the integrity of the proposed dynamics modeling. The human–robot interaction forces are estimated with an accuracy of 2 N, in the presence of friction and measurement noise. Finally, the effectiveness of the model-based controller is assessed by using the proposed method, providing valuable tools for the enhancement of overall performance of such a complex dynamics system.
... Assistive technology has great potential to help people with disabilities live independently and to participate in social activities as well as to promote well-being (Gentry, 2009;Kirstin van Dam et al., 2023) Brose et al (2010) describe how robotic systems enable people with physical disabilities such as neuromuscular diseases to eat, prepare meals, brush teeth, shave, dress themselves, open cabinet doors, load the dishwasher and take things in their daily life environment. In addition, assistive technology used in rehabilitation to increase strength and balance limitations such as exoskeletons is an interesting topic in the motor rehabilitation of physically disabled people (Wang et al., 2022). The use of computers in schools can be improved for students with physical disabilities and collaboratively created computer-based strategies can be implemented by teachers in learning and teaching in schools. ...
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With rapid advancements in exoskeleton hardware technologies, successful assessment and accurate control remain challenging. This study introduces a modular sensor-based system to enhance biomechanical evaluation and control in lower-limb exoskeletons, utilizing advanced sensor technologies and fuzzy logic. We aim to surpass the limitations of current biomechanical evaluation methods confined to laboratories and to address the high costs and complexity of exoskeleton control systems. The system integrates inertial measurement units, force-sensitive resistors, and load cells into instrumented crutches and 3D-printed insoles. These components function both independently and collectively to capture comprehensive biomechanical data, including the anteroposterior center of pressure and crutch ground reaction forces. This data is processed through a central unit using fuzzy logic algorithms for real-time gait phase estimation and exoskeleton control. Validation experiments with three participants, benchmarked against gold-standard motion capture and force plate technologies, demonstrate our system's capability for reliable gait phase detection and precise biomechanical measurements. By offering our designs open-source and integrating cost-effective technologies, this study advances wearable robotics and promotes broader innovation and adoption in exoskeleton research.
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Research on lower limb exoskeleton (LLE) for rehabilitation have developed rapidly to meet the need of the population with neurologic injuries. LLEs for rehabilitation include therapeutic LLEs that aim to restore walking ability for patients, and assistive LLEs that offer support on activities in daily life. A substantial part of them can serve both purposes. However, these devices are yet to reach the final goal of performing human-machine joint movement agilely and smartly. Control strategy plays an important role in achieving their designed goal. At present, control strategies face three major challenges: how to detect human intention, how to do motion control with given intentions, and how to optimize control parameters to suit different individuals. As a contribution, this paper offers an overview on the state-of-the-art control strategies for rehabilitation LLEs by classifying them into eight categories, each of which is presented with a technical summary and tabulated information of representative papers. Moreover, current approaches addressing the three challenges are discussed in a macroscopic perspective. Finally, it has been explored which requirements the future control strategies should meet for maximizing the performance of rehabilitation LLEs.
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In this article, various investigations on soft exoskeletons are presented and their functional and structural characteristics are analyzed. The present work is oriented to the studies of the last decade and covers the upper and lower joints, specifically the shoulder, elbow, wrist, hand, hip, knee, and ankle. Its functionality, applicability, and main characteristics are exposed, such as degrees of freedom, force, actuators, power transmission methods, control systems, and sensors. The purpose of this work is to show the current trend in the development of soft exoskeletons, in addition to specifying the essential characteristics that must be considered in its design and the challenges that its construction implies.
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The field of robot-assisted physical rehabilitation and robotics technology for providing support to the elderly population is rapidly evolving. Lower limb robot aided rehabilitation and assistive technology have been a focus for the engineering community during the last three decades as several robotic lower limb exoskeletons have been proposed in the literature as well as some being commercially available. Numerous manufacturing techniques and materials have been developed for lower limb exoskeletons during the last two decades, resulting in the design of a variety of robot exoskeletons for gait assistance for elderly and disabled people. One of the most important aspects of developing exoskeletons is the selection of the most appropriate proper material. The material selection strongly influences the overall weight and performance of the exoskeleton robot. The most suitable fabrication method for material is also an important parameter for the development of lower limb robot exoskeletons. In addition to the materials and manufacturing methods, the actuation method plays a vital role in the development of these robot exoskeletons. Even though various materials, manufacturing methods and actuators are reported in the literature for these lower limb robot exoskeletons, there are still avenues of improvement in these three domains. In this review, we have examined various lower limb robotic exoskeletons, concentrating on the three main aspects of material, manufacturing, and actuation. We have focused on the advantages and drawbacks of various materials and manufacturing practices as well as actuation methods. A discussion on future directions of research is provided for the engineering community covering the material, manufacturing and actuation methods.
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A patient who unexpectedly sustains a lower leg injury often uses crutches for walking, to both assist the patient and prevent further injury until a full recovery is made. In this study, a novel crutch walk training system was developed; a head-mounted display (HMD) was introduced to present a virtual obstacle for trainees using crutches. Through repetitions of the training, it was expected that the trainees would improve their overall body stability. Healthy subjects participated in experimental training exercises using the developed training system. As a result, the participants acquired the skill of walking well with crutches without losing their body balance significantly, even in the event of facing a virtual obstacle, during the five training sessions.
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