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

A wearable system to assist impaired-neck patients: Design and evaluation

Patients with neurological disorders, such as amyotrophic lateral sclerosis, Parkinson's disease, and cerebral palsy, often face challenges due to head-neck immobility. The conventional treatment approach involves using a neck collar to maintain an upright head position, but this can be cumbersome and restricts head-neck movements over prolonged periods. This study introduces a wearable robot capable of providing three anatomical head motions for training and assistance. The primary contributions of this research include the design of an optimized structure and the incorporation of human-robot interaction. Based on human head motion data, our primary focus centered on developing a robot capable of accommodating a significant range of neutral head movements. To ensure safety, impedance control was employed to facilitate human-robot interaction. A human study was conducted involving 10 healthy subjects who participated in an experiment to assess the robot's assistance capabilities. Passive and active modes were used to evaluate the robot's effectiveness, taking into account head-neck movement error and muscle activity levels. Surface electromyography signals (sEMG) were collected from the splenius capitis muscles during the experiment. The results demonstrated that the robot covered nearly 85% of the overall range of head rotations. Importantly, using the robot during rehabilitation led to reduced muscle activation, highlighting its potential for assisting individuals with post-stroke movement impairments.

Investigation with able-bodied subjects suggests Myosuit may potentially serve as a stair ascent training robot

Real world settings are seldomly just composed of level surfaces and stairs are frequently encountered in daily life. Unfortunately, ~ 90% of the elderly population use some sort of compensation pattern in order to negotiate stairs. Because the biomechanics required to successfully ascend stairs is significantly different from level walking, an independent training protocol is warranted. Here, we present as a preliminary investigation with 11 able-bodied subjects, prior to clinical trials, whether Myosuit could potentially serve as a stair ascent training robot. Myosuit is a soft wearable exosuit that was designed to assist the user via hip and knee extension during the early stance phase. We hypothesized that clinical studies could be carried out if the lower limb kinematics, sensory feedback via plantar force, and electromyography (EMG) patterns do not deviate from the user's physiological stair ascent patterns while reducing hip and knee extensor demand. Our results suggest that Myosuit conserves the user's physiological kinematic and plantar force patterns. Moreover, we observe approximately 20% and 30% decrease in gluteus maximus and vastus medialis EMG levels in the pull up phase, respectively. Collectively, Myosuit reduces the hip and knee extensor demand during stair ascent without any introduction of significant compensation patterns.

Neurorehabilitation robotics: how much control should therapists have?

Robotic technologies for rehabilitating motor impairments from neurological injuries have been the focus of intensive research and capital investment for more than 30 years. However, these devices have failed to convincingly demonstrate greater restoration of patient function compared to conventional therapy. Nevertheless, robots have value in reducing the manual effort required for physical therapists to provide high-intensity, high-dose interventions. In most robotic systems, therapists remain outside the control loop to act as high-level supervisors, selecting and initiating robot control algorithms to achieve a therapeutic goal. The low-level physical interactions between the robot and the patient are handled by adaptive algorithms that can provide progressive therapy. In this perspective, we examine the physical therapist's role in the control of rehabilitation robotics and whether embedding therapists in lower-level robot control loops could enhance rehabilitation outcomes. We discuss how the features of many automated robotic systems, which can provide repeatable patterns of physical interaction, may work against the goal of driving neuroplastic changes that promote retention and generalization of sensorimotor learning in patients. We highlight the benefits and limitations of letting therapists physically interact with patients through online control of robotic rehabilitation systems, and explore the concept of trust in human-robot interaction as it applies to patient-robot-therapist relationships. We conclude by highlighting several open questions to guide the future of therapist-in-the-loop rehabilitation robotics, including how much control to give therapists and possible approaches for having the robotic system learn from therapist-patient interactions.

Exoskeletons: A challenge for development

The development of exoskeletons is currently a lengthy process full of challenges. We are proposing a framework to accelerate the process and make the resulting exoskeletons more user-centered. The needed accomplishments in science are described in an effort to lay the foundation for future research projects. Since the early 2000s, exoskeletons have been discussed as an emerging technology in industrial, medical, or military applications. Those systems are designed to support people during manual tasks. At first, those systems lacked broad acceptance. Many models found their niches in ongoing developments and more diverse systems entering the market. There are still applications that are in dire need of such assistance. Due to the lack of experience with body-worn robotics, the development of such systems has been shaped by trial and error. The lack of legacy products results in longer development times. In this paper, a process to generate a framework is presented to display the required research to enable future exoskeleton designers. Owing to their proximity to the user's body, exoskeletons are highly complex systems that need sophisticated subsystems, such as kinematic, control, interaction design, or actuators, to be accepted by users. Due to the wide variety of fields and high user demands, a synchronized multidisciplinary effort is necessary. To achieve this, a process to develop a modular framework for exoskeleton design is proposed. It focuses on user- and use-case-centered solutions for matching kinematics, actuation, and control. To ensure the usefulness of the framework, an evaluation of the incorporated solutions is required.

Efficacy of Robot-Assisted Gait Therapy Compared to Conventional Therapy or Treadmill Training in Children with Cerebral Palsy: A Systematic Review with Meta-Analysis

BACKGROUND

Motor, gait and balance disorders reduce functional capabilities for activities of daily living in children with cerebral palsy (CP). Robot-assisted gait therapy (RAGT) is being used to complement conventional therapy (CT) or treadmill therapy (TT) in CP rehabilitation. The aim of this systematic review is to assess the effect of RAGT on gait, balance and functional independence in CP children, in comparison to CT or TT.

METHODS

We have conducted a systematic review with meta-analysis. A search in PubMed Medline, Web of Science, Scopus, CINAHL, PEDro and SciELO has been conducted for articles published until October 2022. Controlled clinical trials (CCT), in which RAGT was compared to TT or CT and assessed gait speed, step and stride length, width step, walking distance, cadence, standing ability, walking, running and jumping ability, gross motor function and functional independence in children with CP, have been included. Methodological quality was assessed with the PEDro scale and the pooled effect was calculated with Cohen's Standardized Mean Difference (SMD) and its 95% Confidence Interval (95% CI).

RESULTS

A total of 15 CCTs have been included, providing data from 413 participants, with an averaged methodological quality of 5.73 ± 1.1 points in PEDro. The main findings of this review are that RAGT shows better results than CT in the post-intervention assessment for gait speed (SMD 0.56; 95% CI 0.03 to 1.1), walking distance (SMD 2; 95% CI 0.36 to 3.65) and walking, running and jumping ability (SMD 0.63; 95% CI 0.12 to 1.14).

CONCLUSIONS

This study shows that the effect of RAGT is superior to CT on gait speed, walking distance and walking, running and jumping ability in post-intervention, although no differences were found between RAGT and TT or CT for the remaining variables.

Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors

Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based rehabilitation through human-in-the-loop control to tailor robot assistance towards reducing patients’ energy effort. However, it is usually assessed by indirect calorimetry which entails a certain degree of invasiveness and provides delayed data, which is not suitable for controlling robotic devices. This work proposes a deep learning-based tool for steady-state energy expenditure estimation based on more ergonomic sensors than indirect calorimetry. The study innovates by estimating the energy expenditure in assisted and non-assisted conditions and in slow gait speeds similarly to impaired subjects. This work explores and benchmarks the long short-term memory (LSTM) and convolutional neural network (CNN) as deep learning regressors. As inputs, we fused inertial data, electromyography, and heart rate signals measured by on-body sensors from eight healthy volunteers walking with and without assistance from an ankle-foot exoskeleton at 0.22, 0.33, and 0.44 m/s. LSTM and CNN were compared against indirect calorimetry using a leave-one-subject-out cross-validation technique. Results showed the suitability of this tool, especially CNN, that demonstrated root-mean-squared errors of 0.36 W/kg and high correlation (ρ > 0.85) between target and estimation (R¯2 = 0.79). CNN was able to discriminate the energy expenditure between assisted and non-assisted gait, basal, and walking energy expenditure, throughout three slow gait speeds. CNN regressor driven by kinematic and physiological data was shown to be a more ergonomic technique for estimating the energy expenditure, contributing to the clinical assessment in slow and robotic-assisted gait and future research concerning human-in-the-loop control.

Optimal Assistance Timing to Induce Voluntary Dorsiflexion Movements: A Preliminary Study in Healthy Participants

Swing-phase dorsiflexion assistance with robotic ankle–foot orthosis could improve toe clearance and limb shortening such that compensatory movements are suppressed. However, facilitating voluntary effort under assistance remains a challenge. In our previous study, we examined assistance effects of swing-phase dorsiflexion with different delay times after toe-off on a dorsiflexion-restricted gait with a high-dorsiflexion assistive system. Results showed that later dorsiflexion assistance could lead to an increase in the tibialis anterior’s surface electromyography but could also deteriorate compensatory movement. Thus, we concluded that there is a suitable assistance timing to simultaneously achieve voluntary effort and optimal gait. In the present research, we derived a method to identify a suitable dorsiflexion assistance delay time via a multiple linear regression analysis on ankle data of stroke patients with a pathological gait with insufficient dorsiflexion. With the identification method, an experiment was conducted on six healthy participants with restricted dorsiflexion. Results showed that the identified assistance timing improved the amplitude of the tibialis anterior’s surface electromyography while also suppressing limb shortening during circumduction and hip hiking. Although a practical study of stroke survivors is required, observations from this research indicate the potential to successfully induce voluntary efforts with the identified dorsiflexion assistance timing.

Wearable Lower-Limb Exoskeleton for Children With Cerebral Palsy: A Systematic Review of Mechanical Design, Actuation Type, Control Strategy, and Clinical Evaluation

Children with a neurological disorder such as cerebral palsy (CP) severely suffer from a reduced quality of life because of decreasing independence and mobility. Although there is no cure yet, a lower-limb exoskeleton (LLE) has considerable potential to help these children experience better mobility during overground walking. The research in wearable exoskeletons for children with CP is still at an early stage. This paper shows that the number of published papers on LLEs assisting children with CP has significantly increased in recent years; however, no research has been carried out to review these studies systematically. To fill up this research gap, a systematic review from a technical and clinical perspective has been conducted, based on the PRISMA guidelines, under three extended topics associated with "lower limb", "exoskeleton", and "cerebral palsy" in the databases Scopus and Web of Science. After applying several exclusion criteria, seventeen articles focused on fifteen LLEs were included for careful consideration. These studies address some consistent positive evidence on the efficacy of LLEs in improving gait patterns in children with CP. Statistical findings show that knee exoskeletons, brushless DC motors, the hierarchy control architecture, and CP children with spastic diplegia are, respectively, the most common mechanical design, actuator type, control strategy, and clinical characteristics for these LLEs. Clinical studies suggest ankle-foot orthosis as the primary medical solution for most CP gait patterns; nevertheless, only one motorized ankle exoskeleton has been developed. This paper shows that more research and contribution are needed to deal with open challenges in these LLEs.

Effects of Assisted Dorsiflexion Timing on Voluntary Efforts and Compensatory Movements: A Feasibility Study in Healthy Participants

In previous research, we found that modulating the assistance timing of dorsiflexion may affect a user's voluntary efforts. This could constitute a focus area based on assistive strategies that could be developed to foster patients' voluntary efforts. In this present study, we conducted an experiment to verify the effects of ankle dorsiflexion assistance under different timings using a high-dorsiflexion assistive system. Nine healthy and young participants wore a dorsiflexion-restrictive device that enabled them to use circumduction or steppage gaits. On the basis of the transition from the stance to the swing phase of the gait, the assistance timings of the high-dorsiflexion assistive system were set to have delays, which ranged from 0 to 300 ms. The index results from eight out of nine participants evaluated compensatory movements and revealed positive strong/moderate correlations with assistance delay times (r = 0.627-0.965, p <.001), whereas the other participants also performed compensatory movement when dorsiflexion assistance timing was late. Meanwhile, the results from tibialis anterior surface electromyography from six out of nine participants showed positive strong/moderate correlations with dorsiflexion assistance delay times (r = 0.598-0.922, p <.001), indicating that tuning the assistance timing did foster these participants' voluntary dorsiflexion movements. This result indicates that there should be a trade-off between ensuring voluntary dorsiflexion movements and preventing incorrect gait patterns at different assistance timings. The findings of this feasibility study indicate the potential of developing an adaptive control method to ensure voluntary efforts during robot-assisted gait rehabilitation based on assistance timing modification. A new assistance mechanism should also be required to stimulate and motivate a patient's voluntary efforts and should reinforce the effects of active gait rehabilitation.

Control System Design of an Underactuated Dynamic Body Weight Support System Using Its Stability

This paper discusses the stability of systems controlling patient body weight support systems which are used in gait re-education. These devices belong to the class of underactuated mechanical systems. This is due to the application of elastic shock-absorbing connections between the active part of the system and the passive part which impacts the patient. The model takes into account properties of the system, such as inertia, attenuation and susceptibility to the elements. Stability is an essential property of the system due to human-device interaction. In order to demonstrate stability, Lyapunov's theory of stability, which is based on the model of system dynamics, was applied. The stability of the control system based on a model that requires knowledge of the structure and parameters of the equations of motion was demonstrated. Due to inaccuracies in the modeling of the rope (one of the basic elements of the device), an adaptive control system was introduced and its stability was also proved. The authors conducted simulation and experimental tests that illustrate the functionality of the analyzed control systems.

Exoskeleton robots for lower limb assistance: A review of materials, actuation, and manufacturing methods

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.

Robust LQR-Based Neural-Fuzzy Tracking Control for a Lower Limb Exoskeleton System with Parametric Uncertainties and External Disturbances

The design of an accurate control scheme for a lower limb exoskeleton system has few challenges due to the uncertain dynamics and the unintended subject's reflexes during gait rehabilitation. In this work, a robust linear quadratic regulator- (LQR-) based neural-fuzzy (NF) control scheme is proposed to address the effect of payload uncertainties and external disturbances during passive-assist gait training. Initially, the Euler-Lagrange principle-based nonlinear dynamic relations are established for the coupled system. The input-output feedback linearization approach is used to transform the nonlinear relations into a linearized state-space form. The architecture of the adaptive neuro-fuzzy inference system (ANFIS) and used membership function are briefly explained. While varying mass parameters up to 20%, three robust neural-fuzzy datasets are formulated offline with the joint error vector and LQR control input. Thereafter, to deal with external interferences, an error dynamics with a disturbance estimator is presented using an online adaptation of the firing strength matrix. The Lyapunov theory is carried out to ensure the asymptotic stability of the coupled human-exoskeleton system in view of the proposed controller. The gait tracking results for the proposed control scheme (RLQR-NF) are presented and compared with the exponential reaching law-based sliding mode (ERL-SM) controller. Furthermore, to investigate the robustness of the proposed control over LQR control, a comparative performance analysis is presented for two cases of parametric uncertainties and external disturbances. The first case considers the 20% raise in mass values with a trigonometric form of disturbances, and the second case includes the effect of the 30% increment in mass values with a random form of disturbances. The simulation runs have shown the promising gait tracking aspects of the designed controller for passive-assist gait training.

Exoskeleton Active Walking Assistance Control Framework Based on Frequency Adaptive Dynamics Movement Primitives

This paper introduces a novel exoskeleton active walking assistance control framework based on frequency adaptive dynamics movement primitives (FADMPs). The FADMPs proposed in this paper is an online learning and prediction algorithm which is able to online estimate the fundamental frequency of human joint trajectory, learn the shape of joint trajectory and predict the future joint trajectory during walking. The proposed active walking assistance control framework based on FADMPs is a model-based controller which relies on the human joint torque estimation. The assistance torque provided by exoskeleton is estimated by human lower limb inverse dynamics model which is sensitive to the noise in the joint motion trajectory. To estimate a smooth joint torque profile, the joint motion trajectory must be filtered first by a lowpass filter. However, lowpass filter will introduce an inevitable phase delay in the filtered trajectory. Both simulations and experiments in this paper show that the phase delay has a significant effect on the performance of exoskeleton active assistance. The active assistant control framework based on FADMPs aims at improving the performance of active assistance control by compensating the phase delay. Both simulations and experiments on active walking assistance control show that the performance of active assistance control can be further improved when the phase delay in the filtered trajectory is compensated by FADMPs.