Gait Assistance Research Articles

Nabiximols plus robotic assisted gait training in improving motor performances in people with Multiple Sclerosis.

BackgroundMultiple sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system, affecting ambulation even in people with only mild neurological signs. Patients with MS frequently experience spasticity, which contributes significantly to impair their motor functions, including ambulation, owing to muscle stiffness, spasms, and pain. ObjectivesTo clarify the role of delta-9-tetrahydrocannabinol(THC):cannabidiol(CBD) oromucosal spray, coupled to robot-aided gait training (RAGT) using the Lokomat©Pro to improve functional ambulation in patients with MS. MethodsWe compared 20 patients with MS, who were treated with THC:CBD oromucosal spray in add-on to the ongoing oral antispastic therapy (OAT) (group A), with 20 individuals with MS (matched for clinical-demographic characteristics) who were treated only with OAT (group B). Both the groups underwent RAGT using the Lokomat-Pro (three 45-minute sessions per week). Our primary outcome measures were the Functional Independence Measure (FIM) and the 10 meters walking test (10MWT). As secondary outcome measures we evaluated the brain cortical excitability by using Transcranial Magnetic Stimulation. Both parameters were taken before and after the end of the RAGT. ResultsFIM improved in group A more than in group B (p<0.001). Moreover, 10MWT decreased in group A more than in group B (p<0.001). These clinical findings were paralleled by a more evident reshape of intracortical excitability in both upper and lower limbs, as suggested by motor evoked potential amplitude increase (p<0.001), intracortical inhibition strengthening (p<0.001), and intracortical facilitation decrease (p=0.01) in group A as compared to group B. ConclusionsOur results suggest that the combined THC:CBD-RAGT approach could be useful in improving gait performance in patients with MS.

A new lower limb portable exoskeleton for gait assistance in neurological patients: a proof of concept study

BackgroundFew portable exoskeletons following the assist-as-needed concept have been developed for patients with neurological disorders. Thus, the main objectives of this proof-of-concept study were 1) to explore the safety and feasibility of an exoskeleton for gait rehabilitation in stroke and multiple sclerosis patients, 2) to test different algorithms for gait assistance and measure the resulting gait changes and 3) to evaluate the user’s perception of the device.MethodsA cross-sectional study was conducted. Five patients were recruited (4 patients with stroke and 1 with multiple sclerosis). A robotic, one-degree-of-freedom, portable lower limb exoskeleton known as the Marsi Active Knee (MAK) was designed. Three control modes (the Zero Force Control mode, Mode 1 and Mode 3) were implemented. Spatiotemporal gait parameters were measured by the 10-m walking test (10MWT), the Gait Assessment and Intervention Tool (G.A.I.T.) and Tinetti Performance Oriented Mobility Assessment (gait subscale) before and after the trials. A modified QUEST 2.0 questionnaire was administered to determine each participant’s opinion about the exoskeleton. The data acquired by the MAK sensors were normalized to a gait cycle, and adverse effects were recorded.ResultsThe MAK exoskeleton was used successfully without any adverse effects. Better outcomes were obtained in the 10MWT and G.A.I.T. when Mode 3 was applied compared with not wearing the device at all. In 2 participants, Mode 3 worsened the results. Additionally, Mode 3 seemed to improve the 10MWT and G.A.I.T. outcomes to a greater extent than Mode 1. The overall score for the user perception of the device was 2.8 ± 0.4 95% CI.ConclusionsThe MAK exoskeleton seems to afford positive preliminary results regarding safety, feasibility, and user acceptance. The efficacy of the MAK should be studied in future studies, and more advanced improvements in safety must be implemented.

Evaluating Immediate Benefits of Assisting Knee Extension With a Soft Inflatable Exosuit

Wearable robots such as powered exoskeletons and exosuits have been developed for gait assistance and rehabilitation. However, effects of knee extension assistance during the swing phase and initial stance of walking remains largely unknown. This work studies the changes in gait patterns for seven healthy participants and three impaired participants when knee extension in the swing and initial stance phases is assisted by a soft inflatable exosuit. The kinematics, surface electromyographic (sEMG) activity, and ground reaction forces (GRFs) for seven healthy participants during treadmill walking are recorded. Reductions in knee angle and sEMG activity of the quadriceps are observed. The knee angles, GRFs, spatiotemporal parameters, and compensatory gait patterns are studied for the three impaired participants for treadmill walking. Reductions in the knee angle, hip flexion, step length, and step time are observed. Compensatory gait patterns for the three participants varied for all participants. A timed up-and-go (TUG) test is also performed with the impaired participants during overground walking. A reduced TUG execution time is observed, indicating potential improvement in functional mobility. Overall, this work provides preliminary evidence on the benefits of a soft-exosuit in supporting healthy individuals and improving the rehabilitation of stroke survivors by assisting knee extension in the swing and initial stance phases.

Oxygen Consumption While Walking With Multijoint Neuromuscular Electrical Stimulation After Stroke

This case study evaluated the effect of implanted multijoint neuromuscular electrical stimulation gait assistance on oxygen consumption relative to walking without neuromuscular electrical stimulation after stroke. The participant walked slowly with an asymmetric gait pattern after stroke. He completed repeated 6-min walk tests at a self-selected walking speed with and without hip, knee, and ankle stimulation assistance. His walking speed with neuromuscular electrical stimulation more than doubled from 0.28 ± 0.01 m/sec to 0.58 ± 0.04 m/sec, whereas average step length and cadence increased by 0.12 m and 24 steps/min, respectively. As a result, energy cost of walking with neuromuscular electrical stimulation decreased by 0.19 ml O2/kg per meter as compared with walking without stimulation while oxygen consumption increased by 1.1 metabolic equivalent of tasks (3.9 ml O2/kg per minute). These metabolic demands are similar to those reported for stroke survivors capable of walking at equivalent speeds without stimulation, suggesting the increase in oxygen consumption and decreased energy cost result from improved efficiency of faster walking facilitated by neuromuscular electrical stimulation. Although the effect of neuromuscular electrical stimulation on gait economy has implications for community walking within the user's metabolic reserves, this case study's results should be interpreted with caution and the hypothesis that multijoint neuromuscular electrical stimulation improves metabolic efficiency should be tested in a wide population of stroke survivors with varied deficits.

Synchronized Tactile Stimulation on Upper Limbs Using a Wearable Robot for Gait Assistance in Patients With Parkinson's Disease.

This study aimed to investigate whether using a wearable robot applying interactive rhythmic stimulation on the upper limbs of patients with Parkinson's disease (PD) could affect their gait. The wearable robot presented tactile stimuli on the patients' upper limbs, which was mutually synchronized with the swing of their upper limbs. We conducted an evaluation experiment with PD patients (n = 30, Modified Hoehn-Yahr = 1–3, on-state) to investigate the assistance effect by the robot and the immediate after-effect of intervention. The participants were instructed to walk 30 m under four different conditions: (1) not wearing the robot before the intervention (Pre-condition), (2) wearing the robot without the rhythm assistance (RwoA condition), (3) wearing the robot with rhythm assistance (RwA condition), and (4) not wearing the robot immediately after the intervention (Post-condition). These conditions were conducted in this order over a single day. The third condition was performed three times and the others, once. The arm swing amplitude, stride length, and velocity were increased in the RwA condition compared to the RwoA condition. The coefficient of variance (CV) of the stride duration was decreased in the RwA condition compared to the RwoA condition. These results revealed that the assistance by the robot increased the gait performance of PD patients. In addition, the stride length and velocity were increased and the stride duration CV was decreased in the Post-condition compared to the Pre-condition. These results show that the effect of robot assistance on the patient's gait remained immediately after the intervention. These findings suggest that synchronized rhythmic stimulation on the upper limbs could influence the gait of PD patients and that the robot may assist with gait rehabilitation in these patients.

Effects of exoskeletal gait assistance on the recovery motion following tripping.

Physical assistant robots improve the user’s ability to walk. However, they also potentially affect recovery motion following tripping. The assist algorithm should not interfere with the recovery motion, and should enhance the ability of the user to recover after tripping. Thus, in this study, we investigated the recovery motion affected by the assist robot after tripping. We compared the recovery motion with different reaction algorithms. Principal component analysis revealed the effects of the reaction algorithm. Correspondingly, principal components were related to the recovery motion during two steps following tripping. Specifically, the effects of the reaction algorithm were related to a principal component that represented the motion of the second step after tripping and that increased the margin of stability. Furthermore, the margin of stability became significantly large when the assistive torque was applied during the recovery motion. The result of this study suggests that the assist robot can potentially enhances the recovery motion of its user following tripping.

Implementation of LPV H∞ Loop-Shaping Control for a Variable Stiffness Actuator

Abstract Compliant actuators have been increasingly used for active joints in lower-limb exoskeletons or orthoses because they help to guarantee a safe human interaction. One example of such compliant motors is the variable stiffness actuator (VSA). The design of a torque controller for such an actuator is a crucial task in order to provide patients with physical gait assistance and overcome the mechanical limitations of the VSA. Our goal is to implement a torque controller for our mechanical-rotary variable impedance actuator (MeRIA) used in future lower-limb exoskeletons. In the torque control design, we derive a gain-scheduled controller for the polytopic linear parameter-varying (LPV) model of the actuator. This controller is based on the classical H∞ loop-shaping approach. Measurements on the hardware-in-the-loop system in time and frequency domain show that the designed controller provides adequate performance over the whole varying stiffness range. Additionally, the controller provides H∞ robustness with respect to coprime factor uncertainty for the polytopic system. Thus, the torque controller fulfills major safety requirements, and can further be used for human-in-the-loop tests and applications with a lower-limb exoskeleton.

Walking faster and farther with a soft robotic exosuit: Implications for post-stroke gait assistance and rehabilitation.

Objective: Soft robotic exosuits can improve the mechanics and energetics of walking after stroke. Building on this prior work, we evaluated the effects of the first prototype of a portable soft robotic exosuit. Methods: Exosuit-induced changes in the overground walking speed, distance, and energy expenditure of individuals post-stroke were evaluated statistically and compared to minimal clinically important difference scores. Results: Compared to walking without the exosuit worn, the n}{}< 5 kg exosuit did not substantially modify speed, distance, or energy expenditure when worn unpowered. In contrast, when powered on to provide an average 22.87 n}{}pm 0.58 %bodyweight of paretic plantarflexor force assistance during stance phase and assist the paretic dorsiflexors during swing phase to reduce drop-foot, study participants walked a median 0.14 n}{}pm 0.06 m/s faster during the 10-meter walk test and traveled 32 n}{}pm 8 m farther during the six minute walk test (n}{}P < 0.05). Conclusions: Individuals post-stroke can leverage the paretic plantarflexor and dorsiflexor assistance provided by soft robotic exosuits to achieve clinically-meaningful increases in speed and distance.

A clinical pilot study on posture stabilization via light contact with cane-type companion robot

In this paper, toward robotic gait assistance, we investigate the feasibility of a cane-type assistive mobile robot accompanying the user autonomously through a clinical pilot experiment. As widely known, gait ability is important for all people to keep their quality of life. However, for people having weakened lower limbs such as elderly people, their postural sway during walking could be insuppressible and cause falling. To support the gait motion of elderly people, our group has been developing a series of hand-holding cane robots named Intelligent Cane. Such assistive robots are expected to remove barriers to the independent lives of elderly people. Recently, we have focused on the potential of a companion robot that follows the user ahead and can be touched or grasped for bracing whenever the user needs it. In order to demonstrate proof of our concept through an experiment with a motion capture system, we propose a user companion strategy that enables our cane robot to keep a constant relative distance between the robot and the user walking on a treadmill. We evaluate the accuracy of the user companion in an experiment where a user walks on a treadmill. Then, we conduct a clinical experiment with three healthy subjects walking on with the treadmill with our cane robot as a pilot study. Through the clinical experiment, we evaluate a postural stabilization effect of physical interaction with the robot and discuss the feasibility of our robotic gait assistance methodology.

A Dual-Modal Attention-Enhanced Deep Learning Network for Quantification of Parkinson's Disease Characteristics.

It is well known that most patients with Parkinson's disease (PD) have different degree of movement disorders, such as shuffling, festination and akinetic episodes, which could degenerate the life quality of PD patients. Therefore, it is very useful to develop a computerized tool to provide an objective evaluation of PD patients' gait. In this study, we implemented a novel gait evaluating approach to provide not only a binary classification of PD gaits and normal walking, but also a quantification of the PD gaits to relate them to the PD severity level. The proposed system is a dual-modal deep-learning-based model, where left and right gait is modeled separately by a convolutional neural network (CNN) followed by an attention-enhanced long short-term memory (LSTM) network. The left and right samples for model training and testing were segmented sequentially from multiple 1D vertical ground reaction force (VGRF) signals according to the detected gait cycle. Experimental results indicate that our model can provide state-of-the-art performance in terms of classification accuracy. It is expected that the proposed model can be a useful gait assistance to provide a quantitative evaluation of PD gaits with high confidence and accuracy if trained suitably.

Delayed Output Feedback Control for Gait Assistance and Resistance Using a Robotic Exoskeleton

In this study, we propose an interaction control framework for gait assistance and resistance using a robotic exoskeleton. We define a smoothed state variable that represents joint angle movements while walking. Furthermore, a self-feedback controller is designed with the delayed output state. By applying an appropriate time-delay and positive or negative feedback gain to the state variable, we can generate assistive or resistive torque stably without any gait phase or environment recognition. The time-delayed selffeedback controller reflects the movement of the wearer's joints at every moment of control, thereby stably coping with sudden task transitions (e.g., walk-stop-walk, forward-backward walking) as well as walking speed or environment changes. Case studies involved gait assistance with a knee exoskeleton and gait assistance and resistance with a hip exoskeleton. We performed various preliminary tests including metabolic energy measurements and a comparison of the positive or negative power of the generated torque profiles. The results show the flexibility and effectiveness of the proposed interaction control method for gait assistive or resistive training.

Predictive Optimization of Assistive Force in Admittance Control-Based Physical Interaction for Robotic Gait Assistance

In this letter, we introduce our approach to walking assistance for elderly adults through predictive optimization of gait assistive force. We focus on providing supportive interaction force to the user during walking with a robotic assistive device with an admittance controlled mobile base. Appropriate physical human-robot interaction (pHRI) could be beneficial in reducing the risk associated with immobility such as disuse syndrome by encouraging physical activities with proper assistance. We propose an optimization algorithm based on a model predictive control approach in order to provide desirable assistive forces according to the estimated user's state during walking. Using a simplified human gait model with a linear inverted pendulum, we formulate the optimization of the assistive forces as a linear quadratic programming problem that can be suitable for real-time pHRI. Numerical simulations and experimental results demonstrate the feasibility of our gait support strategy in achieving appropriate compliant interactions during walking, fall prevention, and suitable positioning for user companion.

Bio-Inspired Balance Control Assistance Can Reduce Metabolic Energy Consumption in Human Walking.

The amount of research on developing exoskeletons for human gait assistance has been growing in the recent years. However, the control design of exoskeletons for assisting human walking remains unclear. This paper presents a novel bio-inspired reflex-based control for assisting human walking. In this approach, the leg force is used as a feedback signal to adjust hip compliance. The effects of modulating hip compliance on walking gait is investigated through joint kinematics, leg muscle activations and overall metabolic costs for eight healthy young subjects. Reduction in the average metabolic cost and muscle activation are achieved with fixed hip compliance. Compared to the fixed hip compliance, improved assistance as reflected in more consistent reduction in muscle activities and more natural kinematic behaviour are obtained using the leg force feedback. Furthermore, smoother motor torques and less peak power are two additional advantages obtained by compliance modulation. The results show that the proposed control method which is inspired by human posture control can not only facilitate the human gait, but also reduce the exoskeleton power consumption. This demonstrates that the proposed bio-inspired controller allows a synergistic interaction between human and robot.

Research on Terrain Identification of the Smart Prosthetic Ankle by Fuzzy Logic.

This research suggests a fuzzy-logic based terrain identification method and the smart prosthetic ankle system, which automatically controls its ankle angle, based on the detected terrain environment, to assist comfortable gait performance of transtibial amputee. Suggested terrain identification method uses shank angle from three different stages of the stance phase in gait cycle (foot-flat, heel-strike, and toe-off) as input for the fuzzy-logic calculation, and detects five different terrain environment (flat, up-slope, down-slope, up-stairs, and down-stairs) within a single step of gait. Suggested smart prosthetic ankle system comprises of 1) load-cell to measure GRF (ground reaction force), 2) IMU (inertial measurement unit) sensor to measure shank angle, 3) actuator and four bar-linkage mechanism to control ankle angle accordingly for detected terrain environment, and 4) MCU (microcontroller unit) to carry out calculations and control algorithm for ankle actuation. To verify the accuracy of the terrain identification method of the system, the experiment was conducted, which consisted of four transtibial amputees to walk on five different terrain conditions, and the result has shown 97.5% detection accuracy. Compared to previous studies, our suggested smart prosthetic ankle system, along with its terrain identification algorithm, uses lesser number of sensors and step cycle to accurately detect gait environment, which may lead to providing better gait assistance and practical convenience for transtibial amputees.

Delayed Output Feedback Control for Gait Assistance With a Robotic Hip Exoskeleton

In this paper, we propose a new and simple control strategy for gait assistance with a hip exoskeleton robot. This controller is based on the time delayed, self-feedback known for stabilizing oscillatory systems under certain conditions. In this controller, there are no separate estimators for the gait phase nor the environment, yet the controller can be generalized to operate under various walking conditions (e.g., stair and ramp walking). We first define a state variable representing the current leg's movement with hip joint angles. A simple assistance control can be described in closed-loop form with the delayed state feedback. By assigning the appropriate time-delay and self-feedback gain, we can generate assistive torques stably under the interaction between human and exoskeleton. The controller provides immediate and smooth assistance to user movement by reflecting the change of leg motion at every control period. The proposed joint-angle-based delayed-feedback assistance controller can operate under various walking speeds and environmental changes (e.g., stairs and ramps) without the need for additional sensors, computational processing, and parameter adjustment. Using a simple leg swing model, we perform a stability analysis under a simplified condition to provide insights into the effects of the time-delayed feedback in oscillatory systems. Then, we experimentally validate the efficacy of the proposed assistance controller by measuring the metabolic energy expenditure for level treadmill walking. We also test and analyze the generated assistive torques and power under the different walking conditions to show the generalizability of the controller.

A Soft Wearable Robotic Ankle-Foot-Orthosis for Post-Stroke Patients

We propose a soft robotic ankle-foot-orthosis for poststroke patients, which is inexpensive, lightweight, easy to wear, and capable of gait assistance for rehabilitation not only in the clinic but also in daily life. The device includes a 3D-printed flexible brace and an ankle support that allows natural flexion and extension of the ankle but provides support in the vertical direction preventing the structure from buckling. A bi-directional tendon-driven actuator was used for assisting both dorsiflexion and plantarflexion. The device also contains a wearable gait sensing module for measuring the leg trajectory and the foot pressures in real time for feedback control. Since the device is powered by a rechargeable battery and communicates with the main controller wirelessly, it is fully untethered, making it mobile and comfortable. Using the measured sensor data and the biomechanics of the legs, the realtime gait phase is detected, and then a gait assistance algorithm for both dorsiflexion and plantarflexion provides an accurate prediction of a control phase and timing although there are variations in the gait trajectories among individuals. As a feasibility test, the walking experiment was conducted with a post-stroke patient. The result showed improvement in both gait propulsion and foot-drop prevention.

Human–Robot–Environment Interaction Interface for Smart Walker Assisted Gait: AGoRA Walker

The constant growth of the population with mobility impairments has led to the development of several gait assistance devices. Among these, smart walkers have emerged to provide physical and cognitive interactions during rehabilitation and assistance therapies, by means of robotic and electronic technologies. In this sense, this paper presents the development and implementation of a human–robot–environment interface on a robotic platform that emulates a smart walker, the AGoRA Walker. The interface includes modules such as a navigation system, a human detection system, a safety rules system, a user interaction system, a social interaction system and a set of autonomous and shared control strategies. The interface was validated through several tests on healthy volunteers with no gait impairments. The platform performance and usability was assessed, finding natural and intuitive interaction over the implemented control strategies.

Early term effects of robotic assisted gait training on ambulation and functional capacity in patients with spinal cord injury

Background/aimThe aim of the study was to determine the effects of robotic-assisted gait training on ambulation and functional capacity in patients with spinal cord injury.Materials and methods In total, 88 patients were included and were randomly divided into two groups. The first group underwent 16 sessions of robotic therapy training for 8 weeks and conventional therapy for 5 days a week. The second group underwent conventional treatment. The Walking Index for Spinal Cord Injury II was used to evaluate functional ambulation, and the functional independence measure score was used to assess patients’ functional independence levels in a blind manner.Results A significant improvement was observed in both groups according to Walking Index for Spinal Cord Injury II and functional independence measure scores (P < 0.001). However, a significantly higher improvement according to the Walking Index for Spinal Cord Injury II (P = 0.011) and functional independence measure scores (P = 0.022) was seen in the robotic group than in the control group.ConclusionsRobotic-assisted gait training combined with conventional therapy was found to be superior to the conventional therapy in terms of gait function and level of disability.

Musculoskeletal simulation framework for impairment-based exoskeletal assistance post-stroke.

Assistive technology for the lower extremities has shown great promise towards improving gait function in people following neuromuscular injuries. However, our previous work assisting knee flexion torque in post-stroke Stiff-Knee gait found that augmenting strength can induce secondary complications such as spasticity due to stretching of the rectus femoris. In this work we explore whether we could have obtained improved knee flexion but avoided a spastic response by simulating combinations of hip and knee flexion torques using musculoskeletal modeling and simulation. We explore previously collected data on a case-by-case basis to determine individual-specific quadriceps reflex thresholds based on estimated rectus femoris muscle fiber stretch velocities. We then implemented a forward simulation framework to identify the subject-specific hip-knee assistance prescription to improve knee range of motion without initiating a spastic response. The obtained subject-specific assistive prescription informs the development of new gait assistance strategies for post-stroke gait and could be extended to other neuromuscular gait impairments.

Robotic Ankle–Foot Orthosis With a Variable Viscosity Link Using MR Fluid

This paper proposes a novel semiactive ankle–foot orthosis (AFO) called SmartAFO equipped with an elastic link mechanism. The design of the device is based on the understanding of gait biomechanics for gait assistance against paralysis and other gait abnormalities affecting the ankle joint function. The elastic link at the core of the developed AFO is a 1-degree-of-freedom linear-motion system, capable of regulating its viscosity via a magnetorheological fluid and an electromagnetic coil. The link is also integrated with a compression spring that allows it to store and release energy based on its coil current. This design enabled a semiactive AFO that can mitigate foot slap and toe drag without adversely affecting push-off or other gait phases. We present the development of SmartAFO and the results of experiments conducted on healthy people to verify its support functions compared to a commercial AFO. The results showed that SmartAFO can provide controllable braking torque at the heel contact, avoid ankle motion obstruction during the push-off phase, and support toe lift during the swing phase.