Balance recovery for lower limb exoskeleton in standing posture based on orbit energy analysis

Introduction: The need for effective balance control in lower limb rehabilitation exoskeletons is critical for ensuring stability and safety during rehabilitation training. Current research into specialized balance recovery strategies is limited, highlighting a gap in biomechanics-inspired control methods. Methods: We introduce a new metric called "Orbit Energy" (OE), which assesses the balance state of the human-exoskeleton system based on the dynamics of the overall center of mass. Our control framework utilizes OE to choose appropriate balance recovery strategies, including torque controls at the ankle and hip joints. Results: The efficacy of our control algorithm was confirmed through Matlab Simulink simulations, which analyzed the recovery of balance under various disturbance forces and conditions. Further validation came from physical experiments with human subjects wearing the exoskeleton, where a significant reduction in muscle activation was observed during balance maintenance under external disturbances. Discussion: Our findings underscore the potential of biomechanics-inspired metrics like OE in enhancing exoskeleton functionality for rehabilitation purposes. The introduction of such metrics could lead to more targeted and effective balance recovery strategies, ultimately improving the safety and stability of exoskeleton use in rehabilitation settings.

Active Human-Following Control of an Exoskeleton Robot With Body Weight Support

This article presents an active human-following control of the lower limb exoskeleton for gait training. First, to improve safety, considering the human balance, the OpenPose-based visual feedback is used to estimate the individual's pose, then, the active human-following algorithm is proposed for the exoskeleton robot to achieve the body weight support and active human-following. Second, taking the human's intention and voluntary efforts into account, we develop a long short-term memory (LSTM) network to extract surface electromyography (sEMG) to build the estimation model of joints' angles, that is, the multichannel sEMG signals can be correlated with flexion/extension (FE) joints' angles of the human lower limb. Finally, to make the robot motion adapt to the locomotion of subjects under uncertain nonlinear dynamics, an adaptive control strategy is designed to drive the exoskeleton robot to track the desired locomotion trajectories stably. To verify the effectiveness of the proposed control framework, several recruited subjects participated in the experiments. Experimental results show that the proposed joints' angles estimation model based on the LSTM network has a higher estimation accuracy and predicted performance compared with the existing deep neural network, and good simultaneous locomotion tracking performance is achieved by the designed control strategy, which indicates that the proposed control can assist subjects to perform gait training effectively.

Overground Walking With a Transparent Exoskeleton Shows Changes in Spatiotemporal Gait Parameters

Lower-limb gait training (GT) exoskeletons have been successfully used in rehabilitation programs to overcome the burden of locomotor impairment. However, providing suitable net interaction torques to assist patient movements is still a challenge. Previous transparent operation approaches have been tested in treadmill-based GT exoskeletons to improve user-robot interaction. However, it is not yet clear how a transparent lower-limb GT system affects user's gait kinematics during overground walking, which unlike treadmill-based systems, requires active participation of the subjects to maintain stability. In this study, we implemented a transparent operation strategy on the ExoRoboWalker, an overground GT exoskeleton, to investigate its effect on the user's gait. The approach employs a feedback zero-torque controller with feedforward compensation for the exoskeleton's dynamics and actuators' impedance. We analyzed the data of five healthy subjects walking overground with the exoskeleton in transparent mode (ExoTransp) and non-transparent mode (ExoOff) and walking without exoskeleton (NoExo). The transparent controller reduced the user-robot interaction torque and improved the user's gait kinematics relative to ExoOff. No significant difference in stride length is observed between ExoTransp and NoExo (p = 0.129). However, the subjects showed a significant difference in cadence between ExoTransp (50.9± 1.1 steps/min) and NoExo (93.7 ± 8.7 steps/min) (p = 0.015), but not between ExoTransp and ExoOff (p = 0.644). Results suggest that subjects wearing the exoskeleton adjust their gait as in an attention-demanding task changing the spatiotemporal gait characteristics likely to improve gait balance.

Feasibility and Application of the B.E.A.T. Testbed for Assessing the Effects of Lower Limb Exoskeletons on Human Balance

Assessing the performance of exoskeletons in assisting human balance is important for their design process. This study proposes a novel testbed, the B.E.A.T (Balance Evaluation Automated Testbed) to address this aim. We applied the B.E.A.T to evaluate how the presence of a lower limb exoskeleton influenced human balance. The B.E.A.T. consists of a robotic platform, standardized protocols, and performance indicators. Fifteen healthy subjects were enrolled and subjected to repeatable step-type ground perturbations in different directions using the multi-axis robotic platform. Each participant performed three trials, both with and without the exoskeleton (EXO and No-EXO conditions). Nine performance indicators, divided into kinematic and body stability indicators, were computed. The reliability of performance indicators was assessed by computing the Inter Class Correlation (ICC). The indicators showed good (0.60 ≤ ICC < 0.75) to excellent (ICC ≥ 0.75) reliability. The comparison between the EXO and No-EXO conditions revealed a significant increase in the joint range of motion and the center of pressure displacement while wearing the exoskeleton. The main differences between the EXO and No-EXO conditions were found in the range of motion of the knee joints, with an increment up to 17° in the sagittal plane.

Stiffness modulation of a cable-driven leg exoskeleton for effective human–robot interaction

With the widespread development of leg exoskeletons to provide external force-based repetitive training for gait rehabilitation, the prospect of undesired movement adaptation due to applied forces and imposed constraints require adequate investigation. A cable-driven leg exoskeleton, CDLE, presents a lightweight, flexible, and redundantly actuated architecture that enables the possibility of system parameters modulation to alter human–robot interaction while applying the desired forces. In this work, multi-joint stiffness performance of CDLE is formulated to systematically analyze human–CDLE interaction. Further, potential alterations in CDLE architecture are presented to tune human–CDLE interaction that favors the desired human leg movement during a gait rehabilitation paradigm.

Robotic orthoses for gait rehabilitation: An overview of mechanical design and control strategies

The application of robotic devices in providing physiotherapies to post-stroke patients and people suffering from incomplete spinal cord injuries is rapidly expanding. It is crucial to provide valid rehabilitation for people who are experiencing abnormality in their gait performance; therefore, design and development of newer robotic devices for the purpose of facilitating patients' recovery is being actively researched. In order to advance the traditional gait treatment among patients, exoskeletons and orthoses were introduced over the last two decades. This article presents a thorough review of existing robotic gait rehabilitation devices. The latest advancements in the mechanical design, types of control and actuation are also covered. The study comprehends discussions on robotic rehabilitation devices developed both for the training on treadmill and over-ground training. The assist-as-needed strategy for the gait training is particularly emphasized while reviewing various control strategies applied to these robotic devices. This study further reviews experimental investigations and clinical assessments of different control strategies and mechanism designs of robotic gait rehabilitation devices using experimental and clinical trials.

Design of Hybrid Phase Sliding Mode Control Scheme for Lower Extremity Exoskeleton

Aiming at a pneumatic artificial muscle (PAM) lower extremity exoskeleton, a control mechanism based on hybrid phase sliding mode control (SMC) is proposed. First of all, the human gait cycle is mainly divided into the swing phase and stance phase, and the lower extremity exoskeleton phase models are established by the Euler–Lagrange method, respectively. Secondly, the lower limb exoskeleton is inevitably affected in the diverse working environment, and the exoskeleton model has nonlinear and strong coupling characteristics, which both increase the control difficulty. In this situations, a robust sliding mode control method is designed based on an Extended State Observer (ESO). Thirdly, the pneumatic muscle takes time to contract and relax, and then the joint input torque cannot jump when the gait phase changes, hence, the smoothing switching of the assistive control scheme is introduced to solve it. The smoothing switching time is detected by a phase detector, and the phase detector is designed by the plantar pressure information. Finally the comparative simulation shows that this control strategy has the advantages of fast time, high control precision and no jump during control torque switching. Pneumatic artificial muscle contraction rate curve shows that the pneumatic muscles’ motion range meets the control requirement of the exoskeleton.

A Hierarchical Safety Control Strategy for Exoskeleton Robot Based on Maximum Correntropy Kalman Filter and Bounding Box

Exoskeleton robots have been widely used in many fields at present. When wearing the exoskeleton to operate, the wearer may be unconscious of the position of exoskeleton or affected by the surrounding environment, causing collision between two arms of exoskeleton or between arms and environment. The collision may result in the exoskeleton destroyed or even the wearer injured. This paper proposes a hierarchical safety control strategy for exoskeleton robots based on maximum correntropy Kalman filter and bounding box to ensure safe operation. Accurate joint angle prediction can be obtained by filtering out non-Gaussian impulsive noise using maximum correntropy criterion as evaluation criterion. Relative position relationship of the arms can be derived based on bounding box to realize hierarchical safe control. Enough experiments have been carried out, and the results validated the feasibility of the proposed method.

Power Assist Control Based on Human Motion Estimation Using Motion Sensors for Powered Exoskeleton without Binding Legs

In this study, we propose a novel power assist control method for a powered exoskeleton without binding its legs. The proposed method uses motion sensors on the wearer’s torso and legs to estimate his/her motion to enable the powered exoskeleton to assist with the estimated motion. It can detect the start of walking motion quickly because it does not prevent the motion of the wearer’s knees at the beginning of the walk. A nine-axis motion sensor on the wearer’s body is designed to work robustly in very hot and humid spaces, where an electromyograph is not reliable due to the wearer’s sweat. Moreover, the sensor avoids repeated impact during the walk because it is attached to the body of the wearer. Our powered exoskeleton recognizes the motion of the wearer based on a database and accordingly predicts the motion of the powered exoskeleton that supports the wearer. Experiments were conducted to prove the validity of the proposed method.

The Effects on Muscle Activity and Discomfort of Varying Load Carriage With and Without an Augmentation Exoskeleton

Load carriage is a key risk factor for Muscular Skeletal Disorders (MSDs). As one way to decrease such injuries, some exoskeletons have been developed for regular load carriage. We examined the ergonomic potential of an augmentation exoskeleton. Nine subjects completed eight trials of carrying tasks, using four loading levels (0, 15, 30, and 45 kg) and two carrying conditions (with and without the exoskeleton). Electromyography (EMG) and the extended NASA-TLX rating scales were investigated and analyzed by linear mixed modeling and two-way ANOVA methods. Noraxon MR3.8, SPSS19.0, and MATLAB R2014b software were adapted. The results show that most of the muscle mean activities increased significantly (p < 0.05) with exoskeleton assistance. However, the interactive effects illustrate a decreasing trend with increase of load level. The mean discomfort rating scale values were generally higher, but subjects generally preferred using the exoskeleton in heavier loading tasks. The exoskeleton can effectively augment the performance of humans in heavy load carriage. The main reasons for higher muscle activity are from inflexible structures and inharmonious human–robot interactions. In order to decrease the MSD risks and increase comfort, optimal human–robot control strategies and adaptable kinematic design should be improved.

Design and evaluation of a modular lower limb exoskeleton for rehabilitation

This paper deals with the evaluation of an exoskeleton designed for assisting individuals to rehabilitate compromised lower limb movements resulting from stroke or incomplete spinal cord injury. The exoskeleton is composed of lightweight tubular structures and six free joints that provide a modular feature to the system. This feature allows the exoskeleton to be adapted to assist the movement of one or more patient joints. The actuation of the exoskeleton is also modular, and can be performed passively, by means of springs and dampers, or actively through actuators. In addition, its telescopic tubular links, developed to adjust the size of the links in order to align the joints of the exoskeleton with patient joints, allows the exoskeleton to be adjustable to fit different patients. Experiments considering the interaction between a healthy subject and the exoskeleton are performed to evaluate the influence of the exoskeleton structure on kinematic and muscular activity profiles during walking.

Variable Damping Force Tunnel for Gait Training Using ALEX III

Haptic feedback affects not only the quality of training but can also influence the physical design of robotic gait trainers by determining how much force needs to be applied to the user and the nature of the force. This paper presents the design of a variable damping force tunnel and explores the effect of the shape and strength of the damping field using ALEX III, a treadmill-based exoskeleton developed at Columbia University. The study consists of 32 healthy subjects who were trained for 40 minutes in the device. The subjects were trained to follow a footpath with a 50% increase in step height, so the foot would have 1.5 times the ground clearance. Subjects were assigned to one of four groups: linear high, linear low, parabolic high, and parabolic low. Linear or parabolic denotes the shape of the damping field, and high or low denotes the rate of change (strength) of the field based on error. It is shown that the new controller is capable of inducing gait adaptations in healthy individuals while walking in the device. All groups showed adaptations in step height, while only the high strength groups showed changes in normalized error area, a measure of how closely the desired path was followed.

An Open-Structure Treadmill Gait Trainer: From Research to Application

Lower limb rehabilitation robots are designed to enhance gait function in individuals with motor impairments. Although numerous rehabilitation robots have been developed, only few of these robots have been used in practical health care, particularly in China. The objective of this study is to construct a lower limb rehabilitation robot and bridge the gap between research and application. Open structure to facilitate practical application was created for the whole robot. Three typical movement patterns of a single leg were adopted in designing the exoskeletons, and force models for patient training were established and analyzed under three different conditions, respectively, and then a control system and security strategy were introduced. After establishing the robot, a preliminary experiment on the actual use of a prototype by patients was conducted to validate the functionality of the robot. The experiment showed that different patients and stages displayed different performances, and results on the trend variations across patients and across stages confirmed the validity of the robot and suggested that the design may lead to a system that could be successful in the treatment of patients with walking disorders in China. Furthermore, this study could provide a reference for a similar application design.

Robot-Assisted Rehabilitation of Ankle Plantar Flexors Spasticity: A 3-Month Study with Proprioceptive Neuromuscular Facilitation

In this paper, we aim to investigate the effect of proprioceptive neuromuscular facilitation (PNF)-based rehabilitation for ankle plantar flexors spasticity by using a Robotic Ankle-foot Rehabilitation System (RARS). A modified robot-assisted system was proposed, and seven poststroke patients with hemiplegic spastic ankles participated in a 3-month robotic PNF training. Their impaired sides were used as the experimental group, while their unimpaired sides as the control group. A robotic intervention for the experimental group started from a 2-min passive stretching to warming-up or relaxing the soleus and gastrocnemius muscles and also ended with the same one. Then a PNF training session including 30 trials was activated between them. The rehabilitation trainings were carried out three times a week as an addition to their regular rehabilitation exercise. Passive range of motion, resistance torque, and stiffness were measured in both ankles before and after the interventions. The changes in Achilles tendon length, walking speed, and lower limb function were also evaluated by the same physician or physiotherapist for each participant. Biomechanical measurements before interventions showed significant difference between the experimental group and the control group due to ankle spasticity. For the control group, there was no significant difference in the 3 months with no robotic intervention. But for the experimental group, passive dorsiflexion range of motion increased (p < 0.01), resistance torque under different dorsiflexion angle levels (0°, 10°, and 20°) decreased (p < 0.05, p < 0.001, and p < 0.001, respectively), and quasi-static stiffness under different dorsiflexion angle levels (0°, 10°, and 20°) also decreased (p < 0.01, p < 0.001, and p < 0.001, respectively). Achilles's tendon length shortened (p < 0.01), while its thickness showed no significant change (p > 0.05). The robotic rehabilitation also improved the muscle strength (p < 0.01) and muscle control performance (p < 0.001). In addition, improvements were observed in clinical and functional measurements, such as Timed Up-and-Go (p < 0.05), normal walking speed (p > 0.05), and fast walking speed (p < 0.05). These results indicated that the PNF-based robotic intervention could significantly alleviate lower limb spasticity and improve the motor function in chronic stroke participant. The robotic system could potentially be used as an effective tool in poststroke rehabilitation training.

Directed Functional Connectivity in Fronto-Centroparietal Circuit Correlates With Motor Adaptation in Gait Training

Lower-extremity robotic exoskeletons are used in gait rehabilitation to achieve functional motor recovery. To date, little is known about how gait training and post-training are characterized in brain signals and their causal connectivity. In this work, we used time-domain partial Granger causality (PGC) analysis to elucidate the directed functional connectivity of electroencephalogram (EEG) signals of healthy adults in robot-assisted gait training (RAGT). Our results confirm the presence of EEG rhythms and corticomuscular relationships during standing and walking using spectral and coherence analyses. The PGC analysis revealed enhanced connectivity close to sensorimotor areas ( C₃ and CP₃ ) during standing, whereas additional connectivities involve the centroparietal ( CP _z) and frontal ( F _z ) areas during walking with respect to standing. In addition, significant fronto-centroparietal causal effects were found during both training and post-training. Strong correlations were also found between kinematic errors and fronto-centroparietal connectivity during training and post-training. This study suggests fronto-centroparietal connectivity as a potential neuromarker for motor learning and adaptation in RAGT.

Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?

Gait abnormalities following neurological disorders are often disabling, negatively affecting patients' quality of life. Therefore, regaining of walking is considered one of the primary objectives of the rehabilitation process. To overcome problems related to conventional physical therapy, in the last years there has been an intense technological development of robotic devices, and robotic rehabilitation has proved to play a major role in improving one's ability to walk. The robotic rehabilitation systems can be classified into stationary and overground walking systems, and several studies have demonstrated their usefulness in patients after severe acquired brain injury, spinal cord injury and other neurological diseases, including Parkinson's disease, multiple sclerosis and cerebral palsy. In this review, we want to highlight which are the most widely used devices today for gait neurological rehabilitation, focusing on their functioning, effectiveness and challenges. Novel and promising rehabilitation tools, including the use of virtual reality, are also discussed.

Locomotor Adaptation to an Asymmetric Force on the Human Pelvis Directed Along the Right Leg

In this work, we study locomotor adaptation in healthy adults when an asymmetric force vector is applied to the pelvis directed along the right leg. A cable-driven Active Tethered Pelvic Assist Device (A-TPAD) is used to apply an external force on the pelvis, specific to a subject's gait pattern. The force vector is intended to provide external weight bearing during walking and modify the durations of limb supports. The motivation is to use this paradigm to improve weight bearing and stance phase symmetry in individuals with hemiparesis. An experiment with nine healthy subjects was conducted. The results show significant changes in the gait kinematics and kinetics while the healthy subjects developed temporal and spatial asymmetry in gait pattern in response to the applied force vector. This was followed by aftereffects once the applied force vector was removed. The adaptation to the applied force resulted in asymmetry in stance phase timing and lower limb muscle activity. We believe this paradigm, when extended to individuals with hemiparesis, can show improvements in weight bearing capability with positive effects on gait symmetry and walking speed.

Directed neural connectivity changes in robot-assisted gait training: a partial Granger causality analysis

Now-a-days robotic exoskeletons are often used to help in gait training of stroke patients. However, such robotic systems have so far yielded only mixed results in benefiting the clinical population. Therefore, there is a need to investigate how gait learning and de-learning get characterised in brain signals and thus determine neural substrate to focus attention on, possibly, through an appropriate brain-computer interface (BCI). To this end, this paper reports the analysis of EEG data acquired from six healthy individuals undergoing robot-assisted gait training of a new gait pattern. Time-domain partial Granger causality (PGC) method was applied to estimate directed neural connectivity among relevant brain regions. To validate the results, a power spectral density (PSD) analysis was also performed. Results showed a strong causal interaction between lateral motor cortical areas. A frontoparietal connection was found in all robot-assisted training sessions. Following training, a causal "top-down" cognitive control was evidenced, which may indicate plasticity in the connectivity in the respective brain regions.

Effects of complementary auditory feedback in robot-assisted lower extremity motor adaptation

This study investigates how complementary auditory feedback may affect short-term gait modifications induced by four training sessions with a robotic exoskeleton. Healthy subjects walked on a treadmill and were instructed to match a modified gait pattern derived from their natural one, while receiving assistance by the robot (kinetic guidance). The main question we wanted to answer is whether the most commonly used combination of feedback (i.e., haptic and visual) could be either enhanced by adding auditory feedback or successfully substituted with a combination of kinetic guidance and auditory feedback. Participants were randomly assigned to one of four groups, all of which received kinetic guidance. The control group received additional visual feedback, while the three experimental groups were each provided with a different modality of auditory feedback. The third experimental group also received the same visual feedback as the control group. Differences among the training modalities in gait kinematics, timing and symmetry were assessed in three post-training sessions.