Exoskeleton robots for upper-limb rehabilitation: State of the art and future prospects

Portable robots for upper-limb rehabilitation after stroke: a systematic review and meta-analysis

BACKGROUND

Robot-assisted upper-limb rehabilitation has been studied for many years, with many randomised controlled trials (RCTs) investigating the effects of robotic-assisted training on affected limbs. The current trend directs towards end-effector devices. However, most studies have focused on the effectiveness of rehabilitation devices, but studies on device sizes are relatively few.

GOAL

Systematically review the effect of a portable rehabilitation robot (PRR) on the rehabilitation effectiveness of paralysed upper limbs compared with non-robotic therapy.

METHODS

A meta-analysis was conducted on literature that included the Fugl-Meyer Assessment (FMA) obtained from the PubMed and Web of Science (WoS) electronic databases until June 2023.

RESULTS

A total of 9 studies, which included RCTs, were completed and a meta-analysis was conducted on 8 of them. The analysis involved 295 patients. The influence on upper-limb function before and after treatment in a clinical environment is analysed by comparing the experimental group using the portable upper-limb rehabilitation robot with the control group using conventional therapy. The result shows that portable robots prove to be effective (FMA: SMD = 0.696, 95% = 0.099 to.293, p < 0.05).

DISCUSSION

Both robot-assisted and conventional rehabilitation effects are comparable. In some studies, PRR performs better than conventional rehabilitation, but conventional treatments are still irreplaceable. Smaller size with better portability has its advantages, and portable upper-limb rehabilitation robots are feasible in clinical rehabilitation.

CONCLUSION

Although portable upper-limb rehabilitation robots are clinically beneficial, few studies have focused on portability. Further research should focus on modular design so that rehabilitation robots can be decomposed, which benefits remote rehabilitation and household applications.

Effects of within-day intervals on adaptation to visually induced motion sickness in a virtual-reality motorcycling simulator

This study investigated the effects of the time interval between virtual reality (VR) sessions on visually induced motion sickness (VIMS) reduction to better understand adaptation to and recovery from a nauseating VR experience. The participants experienced two 6-min VR sessions of a first-person motorcycle ride through a head-mounted display with (1) a 6-min interval, (2) an interval until the VIMS score reached zero, and (3) a 60-min interval. The results showed that for each condition, VIMS in the second session was aggravated, unchanged, or attenuated, respectively, indicating that additional resting time was necessary for VIMS adaptation. This study suggests that a certain type of multisensory learning attenuates VIMS symptoms within a relatively short time, requiring at least 20 min of additional resting time after subjective recovery from VIMS symptoms. This finding has important implications for reducing the time interval between repeated challenges when adapting to nauseating stimuli during VR experiences.

Machine learning methods in physical therapy: A scoping review of applications in clinical context

BACKGROUND

Machine learning (ML) efficiently processes large datasets, showing promise in enhancing clinical practice within physical therapy.

OBJECTIVE

The aim of this scoping review is to provide an overview of studies using ML approaches in clinical settings of physical therapy.

DATA SOURCES

A scoping review was performed in PubMed, EMBASE, PEDro, Cochrane, Web of Science, and Scopus.

SELECTION CRITERIA

We included studies utilizing ML methods. ML was defined as the utilization of computational systems to encode patterns and relationships, enabling predictions or classifications with minimal human interference.

DATA EXTRACTION AND DATA SYNTHESIS

Data were extracted regarding methods, data types, performance metrics, and model availability.

RESULTS

Forty-two studies were included. The majority were published after 2020 (n = 25). Fourteen studies (33.3%) were in the musculoskeletal physical therapy field, nine (21.4%) in neurological, and eight (19%) in sports physical therapy. We identified 44 different ML models, with random forest being the most used. Three studies reported on model availability. We identified several clinical applications for ML-based tools, including diagnosis (n = 14), prognosis (n = 7), treatment outcomes prediction (n = 7), clinical decision support (n = 5), movement analysis (n = 4), patient monitoring (n = 3), and personalized care plan (n = 2).

LIMITATION

Model performance metrics, costs, model interpretability, and explainability were not reported.

CONCLUSION

This scope review mapped the emerging landscape of machine learning applications in physical therapy. Despite the growing interest, the field still lacks high-quality studies on validation, model availability, and acceptability to advance from research to clinical practice.

Post Stroke Exercise Training: Intensity, Dosage, and Timing of Therapy

More intense, earlier exercise in rehabilitation results in improved motor outcomes following stroke. Timing and intensity of therapy delivery vary from study to study. For more intensive therapies, there are practical challenges in implementation. However, there are also opportunities for high intensity treatment through innovative approaches and new technologies. Timing of rehabilitation is important. As time post stroke increases, the dosage of therapy required to improve motor recovery outcomes increases. Very early rehabilitation may improve motor outcomes but should be delayed for at least 24 hours post stroke.

Use of noninvasive brain stimulation and neurorehabilitation devices to enhance poststroke recovery: review of the current evidence and pitfalls

Neurorehabilitation devices and technologies are crucial for enhancing stroke recovery. These include noninvasive brain stimulation devices that provide repetitive transcranial magnetic stimulation or transcranial direct current stimulation, which can remodulate an injured brain. Technologies such as robotics, virtual reality, and telerehabilitation are suitable add-ons or complements to physical therapy. However, the appropriate application of these devices and technologies, which target specific deficits and stages, for stroke therapy must be clarified. Accordingly, a literature review was conducted to evaluate the theoretical and practical evidence on the use of neurorehabilitation devices and technologies for stroke therapy. This narrative review provides a practical guide for the use of neurorehabilitation devices and describes the implications of use and potential integration of these devices into healthcare.

Robotic systems for upper-limb rehabilitation in multiple sclerosis: a SWOT analysis and the synergies with virtual and augmented environments

The robotics discipline is exploring precise and versatile solutions for upper-limb rehabilitation in Multiple Sclerosis (MS). People with MS can greatly benefit from robotic systems to help combat the complexities of this disease, which can impair the ability to perform activities of daily living (ADLs). In order to present the potential and the limitations of smart mechatronic devices in the mentioned clinical domain, this review is structured to propose a concise SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of robotic rehabilitation in MS. Through the SWOT Analysis, a method mostly adopted in business management, this paper addresses both internal and external factors that can promote or hinder the adoption of upper-limb rehabilitation robots in MS. Subsequently, it discusses how the synergy with another category of interaction technologies - the systems underlying virtual and augmented environments - may empower Strengths, overcome Weaknesses, expand Opportunities, and handle Threats in rehabilitation robotics for MS. The impactful adaptability of these digital settings (extensively used in rehabilitation for MS, even to approach ADL-like tasks in safe simulated contexts) is the main reason for presenting this approach to face the critical issues of the aforementioned SWOT Analysis. This methodological proposal aims at paving the way for devising further synergistic strategies based on the integration of medical robotic devices with other promising technologies to help upper-limb functional recovery in MS.

Simulation of a control method for active kinesiotherapy with an upper extremity rehabilitation exoskeleton without force sensor

Exoskeleton-aided active rehabilitation is a process that requires sensing and acting upon the motion intentions of the user. Typically, force sensors are used for this. However, they increase the weight and cost of these wearable devices. This paper presents the methodology for detecting users' intentions only with encoders integrated with the drives. It is unique compared to other algorithms, as enables active kinesiotherapy while adding no sensory systems. The method is based on comparing the measured motion with the one computed with the idealised model of the multibody system. The investigation assesses the method's performance and its robustness to model and measurement inaccuracies, as well as patients' unintended motions. Moreover, the PID parameters are selected to provide the optimal regulation based on the dynamics requirements. The research proves the presented concept of the control approach. For all the tests with the final settings, the system reacts to a change in the user's intention below one second and minimises the changes in proportion between the system's acceleration and the generated user's joint torque. The results are comparable to those obtained by EMG-based systems and significantly better than low-cost force sensors.

ExoMechHand prototype development and testing with EMG signals for hand rehabilitation

Rehabilitation is a major requirement to improve the quality of life and mobility of patients with disabilities. The use of rehabilitative devices without continuous supervision of medical experts is increasing manifold, mainly due to prolonged therapy costs and advancements in robotics. Due to ExoMechHand's inexpensive cost, high robustness, and efficacy for participants with median and ulnar neuropathies, we have recommended it as a rehabilitation tool in this study. ExoMechHand is coupled with three different resistive plates for hand impairment. For efficacy, ten unhealthy subjects with median or ulnar nerve neuropathies are considered. After twenty days of continuous exercise, three subjects showed improvement in their hand grip, range of motion of the wrist, or range of motion of metacarpophalangeal joints. The condition of the hand is assessed by features of surface-electromyography signals. A Machine-learning model based on these features of fifteen subjects is used for staging the condition of the hand. Machine-learning algorithms are trained to indicate the type of resistive plate to be used by the subject without the need for examination by the therapist. The extra-trees classifier came out to be the most effective algorithm with 98% accuracy on test data for indicating the type of resistive plate, followed by random-forest and gradient-boosting with accuracies of 95% and 93%, respectively. Results showed that the staging of hand condition could be analyzed by sEMG signal obtained from the flexor-carpi-ulnaris and flexor-carpi-radialis muscles in subjects with median and ulnar neuropathies.

Experimental Study of Fully Passive, Fully Active, and Active-Passive Upper-Limb Exoskeleton Efficiency: An Assessment of Lifting Tasks

Recently, robotic exoskeletons are gaining attention for assisting industrial workers. The exoskeleton power source ranges from fully passive (FP) to fully active (FA), or a mixture of both. The objective of this experimental study was to assess the efficiency of a new active-passive (AP) shoulder exoskeleton using statistical analyses of 11 quantitative measures from surface electromyography (sEMG) and kinematic data and a user survey for weight lifting tasks. Two groups of females and males lifted heavy kettlebells, while a shoulder exoskeleton helped them in modes of fully passive (FP), fully active (FA), and active-passive (AP). The AP exoskeleton outperformed the FP and FA exoskeletons because the participants could hold the weighted object for nearly twice as long before fatigue occurred. Future developments should concentrate on developing sex-specific controllers as well as on better-fitting wearable devices for women.

Exo Supportive Devices: Summary of Technical Aspects

Human societies have been trying to mitigate the suffering of individuals with physical impairments, with a special effort in the last century. In the 1950s, a new concept arose, finding similarities between animal exoskeletons, and with the goal of medically aiding human movement (for rehabilitation applications). There have been several studies on using exosuits with this purpose in mind. So, the current review offers a critical perspective and a detailed analysis of the steps and key decisions involved in the conception of an exoskeleton. Choices such as design aspects, base materials (structure), actuators (force and motion), energy sources (actuation), and control systems will be discussed, pointing out their advantages and disadvantages. Moreover, examples of exosuits (full-body, upper-body, and lower-body devices) will be presented and described, including their use cases and outcomes. The future of exoskeletons as possible assisted movement solutions will be discussed-pointing to the best options for rehabilitation.

Uncertainty-aware automated assessment of the arm impedance with upper-limb exoskeletons

Providing high degree of personalization to a specific need of each patient is invaluable to improve the utility of robot-driven neurorehabilitation. For the desired customization of treatment strategies, precise and reliable estimation of the patient's state becomes important, as it can be used to continuously monitor the patient during training and to document the rehabilitation progress. Wearable robotics have emerged as a valuable tool for this quantitative assessment as the actuation and sensing are performed on the joint level. However, upper-limb exoskeletons introduce various sources of uncertainty, which primarily result from the complex interaction dynamics at the physical interface between the patient and the robotic device. These sources of uncertainty must be considered to ensure the correctness of estimation results when performing the clinical assessment of the patient state. In this work, we analyze these sources of uncertainty and quantify their influence on the estimation of the human arm impedance. We argue that this mitigates the risk of relying on overconfident estimates and promotes more precise computational approaches in robot-based neurorehabilitation.

Patent Review of Lower Limb Rehabilitation Robotic Systems by Sensors and Actuation Systems Used

Robotic systems for lower limb rehabilitation are essential for improving patients' physical conditions in lower limb rehabilitation and assisting patients with various locomotor dysfunctions. These robotic systems mainly integrate sensors, actuation, and control systems and combine features from bionics, robotics, control, medicine, and other interdisciplinary fields. Several lower limb robotic systems have been proposed in the patent literature; some are commercially available. This review is an in-depth study of the patents related to robotic rehabilitation systems for lower limbs from the point of view of the sensors and actuation systems used. The patents awarded and published between 2013 and 2023 were investigated, and the temporal distribution of these patents is presented. Our results were obtained by examining the analyzed information from the three public patent databases. The patents were selected so that there were no duplicates after several filters were used in this review. For each patent database, the patents were analyzed according to the category of sensors and the number of sensors used. Additionally, for the main categories of sensors, an analysis was conducted depending on the type of sensors used. Afterwards, the actuation solutions for robotic rehabilitation systems for upper limbs described in the patents were analyzed, highlighting the main trends in their use. The results are presented with a schematic approach so that any user can easily find patents that use a specific type of sensor or a particular type of actuation system, and the sensors or actuation systems recommended to be used in some instances are highlighted.

Will Your Next Therapist Be a Robot?-A Review of the Advancements in Robotic Upper Extremity Rehabilitation

Several recent studies have indicated that upper extremity injuries are classified as a top common workplace injury. Therefore, upper extremity rehabilitation has become a leading research area in the last few decades. However, this high number of upper extremity injuries is viewed as a challenging problem due to the insufficient number of physiotherapists. With the recent advancements in technology, robots have been widely involved in upper extremity rehabilitation exercises. Although robotic technology and its involvement in the rehabilitation field are rapidly evolving, the literature lacks a recent review that addresses the updates in the robotic upper extremity rehabilitation field. Thus, this paper presents a comprehensive review of state-of-the-art robotic upper extremity rehabilitation solutions, with a detailed classification of various rehabilitative robots. The paper also reports some experimental robotic trials and their outcomes in clinics.

Does frequent use of an exoskeletal upper limb robot improve motor function in stroke patients?

PURPOSE

To determine how differences in frequency of the single-joint hybrid assistive limb (HAL-SJ) use affect the improvement of upper limb motor function and activities of daily living (ADL) in stroke patients.

MATERIALS AND METHODS

Subacute stroke patients were divided into the high or low frequency of HAL-SJ use groups. The two groups were matched by propensity score, and the degree of changes 30 days after initiating HAL-SJ use was compared. A logistic regression analysis was performed to examine whether frequent use would increase the number of subjects experiencing the efficacy of more than the minimal clinically important difference (MCID) of Fugl-Meyer assessment (FMA).

RESULTS

Twenty-five stroke patients were matched by propensity score, and nine pairs were matched. The high-frequency group showed a significantly superior increase to total FMA shoulder, elbow, forearm, and Barthel index compared with the low-frequency group. Logistic regression analysis revealed no significant associations between frequent use and MCID.

CONCLUSIONS

The frequency of HAL-SJ use may affect the improvement of motor function and ADL ability of the upper limb with exception of the fingers and wrist. However, the frequency of intervention was not effective enough to further increase the number of subjects with clinically meaningful changes in upper limb motor function.IMPLICATIONS FOR REHABILITATIONThe current study aimed to clarify how differences in the frequency of single-joint hybrid assistive limb (HAL-SJ) use can affect the improvement of upper-limb motor functions and ADL in subacute stroke patients.Our results implied that the frequency of HAL-SJ use may influence the recovery of upper limb function.However, even if HAL-SJ is used frequently, it does not mean that more patients will achieve clinically meaningful recovery.

Lightweight Bioinspired Exoskeleton for Wrist Rehabilitation Powered by Twisted and Coiled Artificial Muscles

Stroke, cerebral palsy, and spinal cord injuries represent the most common leading causes of upper limb impairment. In recent years, rehabilitation robotics has progressed toward developing wearable technologies to promote the portability of assistive devices and to enable home rehabilitation of the upper extremities. However, current wearable technologies mainly rely on electric motors and rigid links or soft pneumatic actuators and are usually bulky and cumbersome. To overcome the limitations of existing technologies, in this paper, a first prototype of a lightweight, ungrounded, soft exoskeleton for wrist rehabilitation powered by soft and flexible carbon fibers-based twisted and coiled artificial muscles (TCAMs) is proposed. The device, which weighs only 0.135 kg, emulates the arrangement and working mechanism of skeletal muscles in the upper extremities and is able to perform wrist flexion/extension and ulnar/radial deviation. The range of motion and the force provided by the exoskeleton is designed through simple kinematic and dynamic theoretical models, while a thermal model is used to design a thermal insulation system for TCAMs during actuation. The device’s ability to perform passive and active-resisted wrist rehabilitation exercises and EMG-based actuation is also demonstrated.

Human Factor Engineering Research for Rehabilitation Robots: A Systematic Review

The application of human factors engineering for rehabilitation robots is based on a "human-centered" design philosophy that strives to provide safe and efficient human-robot interaction training for patients rather than depending on rehabilitation therapists. Human factors engineering for rehabilitation robots is undergoing preliminary investigation. However, the depth and breadth of current research do not provide a complete human factor engineering solution for developing rehabilitation robots. This study aims to provide a systematic review of research at the intersection of rehabilitation robotics and ergonomics to understand the progress and state-of-the-art research on critical human factors, issues, and corresponding solutions for rehabilitation robots. A total of 496 relevant studies were obtained from six scientific database searches, reference searches, and citation-tracking strategies. After applying the selection criteria and reading the full text of each study, 21 studies were selected for review and classified into four categories based on their human factor objectives: implementation of high safety, implementation of lightweight and high comfort, implementation of high human-robot interaction, and performance evaluation index and system studies. Based on the results of the studies, recommendations for future research are presented and discussed.

Analysis and Validation of Sensitivity in Torque-Sensitive Actuators

Across different fields within robotics, there is a great need for lightweight, efficient actuators with human-like performance. Linkage-based passive variable transmissions and torque-sensitive transmissions have emerged as promising solutions to meet this need by significantly increasing actuator efficiency and power density, but their modeling and analysis remain an open research topic. In this paper, we introduce the sensitivity between input displacement and output torque as a key metric to analyze the performance of these complex mechanisms in dynamic tasks. We present the analytical model of sensitivity in the context of two different torque-sensitive transmission designs, and used this sensitivity metric to analyze the differences in their performance. Experiments with these designs implemented within a powered knee prosthesis were conducted, and results validated the sensitivity model as well as its role in predicting actuators' dynamic performance. Together with other design methods, sensitivity analysis is a valuable tool for designers to systematically analyze and create transmission systems capable of human-like physical behavior.

How does computed tomography inform our understanding of shoulder kinematics? A structured review

The objective of this structured review was to review how computed tomography (CT) scanning has been used to measure the kinematics of the shoulder. A literature search was conducted using Evidence-based Medicine Reviews (Embase) and PubMed. In total, 29 articles were included in the data extraction process. Forty percent of the studies evaluated healthy participants' shoulder kinematics. The glenohumeral joint was the most studied, followed by the scapulothoracic, acromioclavicular, and sternoclavicular joints. Three-dimensional computed tomography (3DCT) and 3DCT with biplane fluoroscopy are the two primary imaging techniques that have been used to measure shoulder joints' motion under different conditions. Finally, many discrepancies in the reporting of the examined motions were found. Different authors used different perspectives and planes to report similar motions, which results in confusion and misunderstanding of the actual examined motion. The use of 3DCT has been widely used in the examination of shoulder kinematics in a variety of populations with varying methods employed. Future work is needed to extend these methodologies to include more diverse populations, to examine the shoulder complex as a whole, and to standardize their reporting of motion examined to make study to study comparisons possible.

Assistance level quantification-based human-robot interaction space reshaping for rehabilitation training

Stroke has become a major disease that seriously threatens human health due to its high incidence and disability rates. Most patients undergo upper limb motor dysfunction after stroke, which significantly impairs the ability of stroke survivors in their activities of daily living (ADL). Robots provide an optional solution for stroke rehabilitation by attending therapy in the hospital and the community, however, the rehabilitation robot still has difficulty in providing needed assistance interactively like human clinicians in conventional therapy. For safe and rehabilitation training, a human-robot interaction space reshaping method was proposed based on the recovery states of patients. According to different recovery states, we designed seven experimental protocols suitable for distinguishing rehabilitation training sessions. To achieve assist-as-needed (AAN) control, a PSO-SVM classification model and an LSTM-KF regression model were introduced to recognize the motor ability of patients with electromyography (EMG) and kinematic data, and a region controller for interaction space shaping was studied. Ten groups of offline and online experiments and corresponding data processing were conducted, and the machine learning and AAN control results were presented, which ensured the effective and the safe upper limb rehabilitation training. To discuss the human-robot interaction in different training stages and sessions, we defined a quantified assistance level index that characterizes the rehabilitation needs by considering the engagement of the patients and had the potential to apply in clinical upper limb rehabilitation training.

Patient-Specific Exercises with the Development of an End-Effector Type Upper Limb Rehabilitation Robot

End-effector type upper limb rehabilitation robots (ULRRs) are connected to patients at one distal point, making them have simple structures and less complex control algorithms, and they can avoid abnormal motion and posture of the target anatomical joints and specific muscles. Given that the end-effector type ULRR focuses more on the rehabilitation of the combined motion of upper limb chain, assisting the patient to perform collaborative tasks, and its intervention has some advantages than the exoskeleton type ULRR, we developed a novel three-degree-of-freedom (DOF) end-effector type ULRR. The advantage of the mechanical design is that the designed end-effector type ULRR can achieve three DOFs by using a four-bar mechanism and a lifting mechanism; we also developed the patient-specific exercises including patient-passive exercise and patient-cooperative exercise, and the advantage of the developed patient-cooperative exercise is that we simplified the human-robot coupling system model into a single spring system instead of the mass-spring-damp system, which efficiently improved the response speed of the control system. In terms of the organization structure of the work, we introduced the end-effector type ULRR's mechanical design, control system, inverse solution of positions, patient-passive exercise based on the inverse solution of positions and the linear position interpolation of servo drives, and patient-cooperative exercise based on the spring model, in sequence. Experiments with three healthy subjects have been conducted, with results showing good trajectory tracking performance in patient-passive exercise and showing effective, flexible, and good real-time interactive performance in patient-cooperative exercise.

The Arrival of the Metaverse in Neurorehabilitation: Fact, Fake or Vision?

The metaverse is a new technology thought to provide a deeper, persistent, immersive 3D experience combining multiple different virtual approaches in a full continuum of physical–digital interaction spaces. Different from virtual reality (VR) and augmented reality (AR), the metaverse has a service-oriented solid model with an emphasis on social and content dimensions. It has widely been demonstrated that motor or cognitive deficits can be more effectively treated using VR/AR tools, but there are several issues that limit the real potential of immersive technologies applied to neurological patients. In this scoping review, we propose future research directions for applying technologies extracted from the metaverse in clinical neurorehabilitation. The multisensorial properties of the metaverse will boost the embodied cognition experience, thus influencing the internal body representations as well as learning strategies. Moreover, the immersive social environment shared with other patients will contribute to recovering social and psychoemotional abilities. In addition to the many potential pros, we will also discuss the cons, providing readers with the available information to better understand the complexity and limitations of the metaverse, which could be considered the future of neurorehabilitation.

IoT-Oriented Wireless Sensor Network and Sports Dance Movement Perception

The Internet of Things needs to connect different types of sensors in accordance with the agreement, and different agreements can be used for information and information exchange systems, which can facilitate the identification and control of intelligent systems. In many scenarios, location service application data are very important for obtaining accurate location information about nodes. In this paper, a wrist motion sensing sensor based on the PVDF piezoelectric film is developed. To realize the monitoring of wrist motion signals, this paper designs and manufactures a series of PVDF noninvasive sensors for motion perception. The characteristics of sports dance movements are reflected in the coordination between men and women, and the dance posture and movements must be synchronized with the music according to the level of music rhythm structure. The transfer of center of gravity is the main driving force of sports, and the gait of athletes is related to the transfer of center of gravity. Posture stability is the basic element of sports dance training. Only on this basis can it be possible to develop specific motion function trajectories and technical action forms.

Three-Dimensional Printing Component Used in Rehabilitation Exoskeleton

This work aims to develop a light symmetrical structure that can be realized through rapid prototyping techniques. The structure must meet some restrictions imposed by possible practical applications. It must withstand a moderate load, be able to adapt to a specific external shape, be relatively light, allow the execution of some changes according to user requirements, allow execution with the help of owned equipment, and allow relatively fast production (its structure and form). The major application for which the structure is designed is that of an exoskeleton for medical rehabilitation, realized by the authors. The creation of such an exoskeleton is followed by a series of research regarding different aspects of acceptability, reliability, ease of use, and the shortcomings that such a structure can cause. In this study, the authors focused on the mechanical part of the exoskeleton realization, which would fulfill some imposed kinematic and constructive conditions.

Sensorimotor Activities and Their Functional Connectivity Elicited by Robot-Assisted Passive Movements of Lower Limbs

Robot-assisted body movements are a useful approach for the rehabilitation of motor dysfunction. Various robots based on end-effector or exoskeleton type have been proposed. However, the effect of these robots on brain activity during assistive lower limb movements remains unclear. In this study, we evaluated brain activity results among robot-assisted passive movements, voluntary active movements, and kinesthetic motor imagery. We measured and compared the brain activities of 21 young, healthy individuals during three experimental conditions associated with lower limb movements (active, passive, and imagery conditions) using functional near-infrared spectroscopy (fNIRS). Our results showed that although different brain areas with significant activity were observed among the conditions, the temporal patterns of the activity in each recording channel and the spatial patterns of functional connectivity showed high similarity between robot-assisted passive movements and voluntary active movements. Conversely, the robot-assisted passive movements did not show any similarity to motor imagery. Overall, these findings suggest that the robotic assistive approach is useful for activating not only afferent processes associated with sensory feedback processing but also motor control-related efferent processes.

Enabling AI and Robotic Coaches for Physical Rehabilitation Therapy: Iterative Design and Evaluation with Therapists and Post-stroke Survivors

Artificial intelligence (AI) and robotic coaches promise the improved engagement of patients on rehabilitation exercises through social interaction. While previous work explored the potential of automatically monitoring exercises for AI and robotic coaches, the deployment of these systems remains a challenge. Previous work described the lack of involving stakeholders to design such functionalities as one of the major causes. In this paper, we present our efforts on eliciting the detailed design specifications on how AI and robotic coaches could interact with and guide patient’s exercises in an effective and acceptable way with four therapists and five post-stroke survivors. Through iterative questionnaires and interviews, we found that both post-stroke survivors and therapists appreciated the potential benefits of AI and robotic coaches to achieve more systematic management and improve their self-efficacy and motivation on rehabilitation therapy. In addition, our evaluation sheds light on several practical concerns (e.g. a possible difficulty with the interaction for people with cognitive impairment, system failures, etc.). We discuss the value of early involvement of stakeholders and interactive techniques that complement system failures, but also support a personalized therapy session for the better deployment of AI and robotic exercise coaches.

The Design and Control of a Footplate-Based Gait Robo-Assisted System for Lower Limb Actuator

Stroke causes disability in the lower-limb symmetry gait pattern in affected patients. The patients would not be able to regain their usual walking ability independently unless they benefit from rehabilitation therapies. Footplate-based gait robo-assisted systems can help patients to conduct effective training/exercising while tracking their progress of recovery and can dramatically reduce the clinical labor costs of physiotherapy. In the sense of simulation and not the design of the mechanical structure, this study aims to perform a combination of dynamic and control simulation of a five degrees-of-freedom footplate-based gait robo-assisted system established according to the Stewart platform structure for use in lower limb rehabilitation of stroke patients. The effectiveness and performance of the proposed mechanism were assessed through a clinical gait pattern of a healthy male individual. The proposed robo-assisted system enables the simulation of the hip and knee flexion/extension as well as the ankle dorsiflexion/plantar flexion of stroke patients to reproduce their typical symmetry gait pattern. The results were interpreted as the dynamic movement characteristics of the right and left thigh, leg, and foot compared to the clinical gait pattern with a mean percentage error of 6.70% to show the effectiveness and accuracy of the developed robo-assisted system for lower limb actuation in the simulation process.

Evaluation of Upper Limb Muscle Activation Using Musculoskeletal Model with Wearable Assistive Device

In recent years, wearable assistive device has been used to support upper arm movement training for rehabilitation purposes. A wearable assistive device could affect the muscle output during motor tasks to support upper limb disorder rehabilitation training. However, the investigation of muscle activity with the given assistive force is not widely investigated. In this study, the evaluation of upper limb muscle activities using musculoskeletal simulation systems with the developed wearable cable-driven assistive device has been carried out. An experimental protocol consisting of a series of motions was executed with five healthy subjects. Muscle activation on the brachioradialis, biceps, and triceps muscles was measured by using surface electromyography (EMG) and analyzed. The simulations with a musculoskeletal model to estimate muscle output with and without a wearable assistive device were performed for three tasks. An assistive upper arm device was integrated into the musculoskeletal model, and the desired assistive force is translated to the arm joint along with a tendon routing structure. Assisting movement by the wearable device was evaluated by measuring muscle activation with-assist and without-assist conditions. The results show that the use of the wearable assistive device can effectively assist in arm movement. Comparisons of measured EMG muscle data and the musculoskeletal model revealed that muscle force was generated throughout the arm. The integrated musculoskeletal model results show that muscle force values for two primary muscles (biceps and brachioradialis) were reduced during the simulated task when wearing the assistive device. These results are congruent with expectations, with the assistive device that supports the upper limb movement, providing practical assistance. The results highlight the importance of evaluating muscle output for the developed wearable assistive device to support the assistive movement. Lastly, the musculoskeletal simulation system could reduce the resource-intensive, and time consumed with the experimental testing could be achieved.

Design and ergonomic assessment of a passive head/neck supporting exoskeleton for overhead work use

Overhead work is an important risk factor associated with musculoskeletal disorders of the neck and shoulder region. This study aimed to propose and evaluate a passive head/neck supporting exoskeleton (HNSE) as a potential ergonomic intervention for overhead work applications. Fourteen male participants were asked to perform a simulated overhead task of fastening/unfastening nut in 4 randomized sessions, characterized by two variables: neck extension angle (40% and 80% of neck maximum range of motion) and exoskeleton condition (wearing and not wearing the HNSE). Using the HNSE, significantly alleviated perceived discomfort in the neck (p-value = 0.009), right shoulder (p-value = 0.05) and left shoulder (p-value = 0.02) and reduced electromyographic activity of the right (p-value = 0.005) and left (p-value = 0.01) sternocleidomastoid muscles. However, utilizing the exoskeleton caused a remarkable increase in right (p-value = 0.04) and left (p-value = 0.05) trapezius electromyographic activities. Performance was not significantly affected by the HNSE. Although the HNSE had promising effects with respect to discomfort and muscular activity in the static overhead task, future work is still needed to investigate its effect on performance and to provide support for the generalizability of study results.

Current State of Robotics in Hand Rehabilitation after Stroke: A Systematic Review

Among the methods of hand function rehabilitation after stroke, robot-assisted rehabilitation is widely used, and the use of hand rehabilitation robots can provide functional training of the hand or assist the paralyzed hand with activities of daily living. However, patients with hand disorders consistently report that the needs of some users are not being met. The purpose of this review is to understand the reasons why these user needs are not being adequately addressed, to explore research on hand rehabilitation robots, to review their current state of research in recent years, and to summarize future trends in the hope that it will be useful to researchers in this research area. This review summarizes the techniques in this paper in a systematic way. We first provide a comprehensive review of research institutions, commercial products, and literature. Thus, the state of the art and deficiencies of functional hand rehabilitation robots are sought and guide the development of subsequent hand rehabilitation robots. This review focuses specifically on the actuation and control of hand functional rehabilitation robots, as user needs are primarily focused on actuation and control strategies. We also review hand detection technologies and compare them with patient needs. The results show that the trends in recent years are more inclined to pursue new lightweight materials to improve hand adaptability, investigating intelligent control methods for human-robot interaction in hand functional rehabilitation robots to improve control robustness and accuracy, and VR virtual task positioning to improve the effectiveness of active rehabilitation training.

An Adaptive Integral Terminal Sliding Mode Controller to Track the Human Upper Limb during Front Crawl Swimming

AbstractInjuries are inevitable during swimming. The main goal for athletes especially competitive ones and coaches is to do the most mechanically effective motion patterns. In this case, biomechanical assessments could be beneficial in the management and prevention of injuries and pain in swimmers' vulnerable joints. As upper limb in swimming causes the highest propulsive force, the arm is exposed to more injuries. A skeletal model with 5 degrees of freedom is developed to simulate the swimmer's arm during front crawl swimming. This model includes shoulder and elbow joints with all of their degrees of freedom. An adaptive integral sliding mode (AITSM) controller is employed to track the desired joint trajectories during swimming. This controller can converge the tracking errors to zero in finite time. For tuning the controller gains regardless of the upper bounds of the system uncertainties, an adaptive controller is applied. Results demonstrate the performance of the AITSM strategy in tracking the desired trajectory of an underwater arm model during swimming. During the down sweep to catch phase, arm movements cause more stress in the shoulder than elbow. The applied moment at the shoulder is almost triple of elbow's moment. Therefore, the most vulnerable joint is the shoulder. By considering shoulder strength, the injury risk is predicted about 10% for the considered swimmer.

Robot-assisted distal training improves upper limb dexterity and function after stroke: a systematic review and meta-regression

INTRODUCTION

Stroke is one of the top 10 causes of death worldwide, and more than half of stroke patients face distal upper extremity dysfunction. Considering that robot-assisted training may be effective in improving distal upper extremity function, the review evaluated the effect of robot-assisted distal training on motor function, hand dexterity, and spasticity after stroke.

METHODS

Eleven databases were systematically searched for randomised controlled trials (RCTs) from inception until Aug 28, 2021. Meta-analysis and meta-regression were performed to investigate the overall effect and source of heterogeneity, respectively.

RESULTS

Twenty-two trials involving 758 participants were included in this systematic review. The overall effect of robot-assisted distal training on the motor function of the wrists and hands was significant improvement (MD = 3.92; 95% CI, 3.04-4.80; P < 0.001). The robot-assisted training had a significantly beneficial effect on other motor functions (MD = 2.84; 95% CI, 1.54-4.14; P < 0.001); dexterity (MD = 9.01; 95% CI, -12.07--5.95; P < 0.001), spasticity, upper extremity strength (SMD = 0.42; 95% CI, 0.07-0.78; P = 0.02) and activities of daily living (SMD = 0.70; 95% CI, 0.29-1.23; P < 0.001). A series of subgroup analyses showed preferable design and effective regime of training. Meta-regression indicated the statistically significant effect of the year of trial, country, and duration on the effectiveness of training.

CONCLUSION

Robot-assisted distal training has a significant effect on motor function, dexterity and spasticity of the upper extremity, compared to conventional therapy.

An Affordable Upper-Limb Exoskeleton Concept for Rehabilitation Applications

In recent decades, many researchers have focused on the design and development of exoskeletons. Several strategies have been proposed to develop increasingly more efficient and biomimetic mechanisms. However, existing exoskeletons tend to be expensive and only available for a few people. This paper introduces a new gravity-balanced upper-limb exoskeleton suited for rehabilitation applications and designed with the main objective of reducing the cost of the components and materials. Regarding mechanics, the proposed design significantly reduces the motor torque requirements, because a high cost is usually associated with high-torque actuation. Regarding the electronics, we aim to exploit the microprocessor peripherals to obtain parallel and real-time execution of communication and control tasks without relying on expensive RTOSs. Regarding sensing, we avoid the use of expensive force sensors. Advanced control and rehabilitation features are implemented, and an intuitive user interface is developed. To experimentally validate the functionality of the proposed exoskeleton, a rehabilitation exercise in the form of a pick-and-place task is considered. Experimentally, peak torques are reduced by 89% for the shoulder and by 84% for the elbow.

Active Disturbance Rejection Control Based Sinusoidal Trajectory Tracking for an Upper Limb Robotic Rehabilitation Exoskeleton

In this paper, a combined control strategy with extended state observer (ESO) and finite time stable tracking differentiator (FTSTD) has been proposed to perform flexion and extension motion repetitively and accurately in the sagittal plane for shoulder and elbow joints. The proposed controller improves the tracking accuracy, performs state estimation, and actively rejects disturbance. A sinusoidal trajectory as an input has been given to a two-link multiple-input multiple-output (MIMO) upper limb robotic rehabilitation exoskeleton (ULRRE) for a passive rehabilitation purpose. The efficacy of the controller has been tested with the help of performance indices such as integral time square error (ITSE), integral square error (ISE), integral time absolute error (ITAE), and integral of the absolute magnitude of error (IAE). The system model is obtained through the Euler–Lagrangian method, and the controller’s stability is also given. The proposed controller has been simulated for ±20% parameter variation with constant external disturbances to test the disturbance rejection ability and robustness against parametric uncertainties. The proposed controller has been compared with already developed ESO-based methods such as active disturbance rejection control (ADRC), nonlinear active disturbance rejection control (NLADRC), and improved active disturbance rejection control (I-ADRC). It has been found that the proposed method increases tracking performance, as evidenced by the above performance indices.

Reference theories and future perspectives on robot-assisted rehabilitation in people with neurological conditions: A scoping review and recommendations from the Italian Consensus Conference on Robotics in Neurorehabilitation (CICERONE)

BACKGROUND

Robot-based treatments are developing in neurorehabilitation settings. Recently, the Italian National Health Systems recognized robot-based rehabilitation as a refundable service. Thus, the Italian neurorehabilitation community promoted a national consensus on this topic.

OBJECTIVE

To conceptualize undisclosed perspectives for research and applications of robotics for neurorehabilitation, based on a qualitative synthesis of reference theoretical models.

METHODS

A scoping review was carried out based on a specific question from the consensus Jury. A foreground search strategy was developed on theoretical models (context) of robot-based rehabilitation (exposure), in neurological patients (population). PubMed and EMBASE® databases were searched and studies on theoretical models of motor control, neurobiology of recovery, human-robot interaction and economic sustainability were included, while experimental studies not aimed to investigate theoretical frameworks, or considering prosthetics, were excluded.

RESULTS

Overall, 3699 records were screened and finally 9 papers included according to inclusion and exclusion criteria. According to the population investigated, structured information on theoretical models and indications for future research was summarized in a synoptic table.

CONCLUSION

The main indication from the Italian consensus on robotics in neurorehabilitation is the priority to design research studies aimed to investigate the role of robotic and electromechanical devices in promoting neuroplasticity.

A Way of Bionic Control Based on EI, EMG, and FMG Signals

Creating highly functional prosthetic, orthotic, and rehabilitation devices is a socially relevant scientific and engineering task. Currently, certain constraints hamper the development of such devices. The primary constraint is the lack of an intuitive and reliable control interface working between the organism and the actuator. The critical point in developing these devices and systems is determining the type and parameters of movements based on control signals recorded on an extremity. In the study, we investigate the simultaneous acquisition of electric impedance (EI), electromyography (EMG), and force myography (FMG) signals during basic wrist movements: grasping, flexion/extension, and rotation. For investigation, a laboratory instrumentation and software test setup were made for registering signals and collecting data. The analysis of the acquired signals revealed that the EI signals in conjunction with the analysis of EMG and FMG signals could potentially be highly informative in anthropomorphic control systems. The study results confirm that the comprehensive real-time analysis of EI, EMG, and FMG signals potentially allows implementing the method of anthropomorphic and proportional control with an acceptable delay.

Review on Patient-Cooperative Control Strategies for Upper-Limb Rehabilitation Exoskeletons

Technology-supported rehabilitation therapy for neurological patients has gained increasing interest since the last decades. The literature agrees that the goal of robots should be to induce motor plasticity in subjects undergoing rehabilitation treatment by providing the patients with repetitive, intensive, and task-oriented treatment. As a key element, robot controllers should adapt to patients’ status and recovery stage. Thus, the design of effective training modalities and their hardware implementation play a crucial role in robot-assisted rehabilitation and strongly influence the treatment outcome. The objective of this paper is to provide a multi-disciplinary vision of patient-cooperative control strategies for upper-limb rehabilitation exoskeletons to help researchers bridge the gap between human motor control aspects, desired rehabilitation training modalities, and their hardware implementations. To this aim, we propose a three-level classification based on 1) “high-level” training modalities, 2) “low-level” control strategies, and 3) “hardware-level” implementation. Then, we provide examples of literature upper-limb exoskeletons to show how the three levels of implementation have been combined to obtain a given high-level behavior, which is specifically designed to promote motor relearning during the rehabilitation treatment. Finally, we emphasize the need for the development of compliant control strategies, based on the collaboration between the exoskeleton and the wearer, we report the key findings to promote the desired physical human-robot interaction for neurorehabilitation, and we provide insights and suggestions for future works.

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study

The electrical impedance myography method is widely used in solving bionic control problems and consists of assessing the change in the electrical impedance magnitude during muscle contraction in real time. However, the choice of electrode systems sizes is not always properly considered when using the electrical impedance myography method in the existing approaches, which is important in terms of electrical impedance signal expressiveness and reproducibility. The article is devoted to the determination of acceptable sizes for the electrode systems for electrical impedance myography using the Pareto optimality assessment method and the electrical impedance signals formation model of the forearm area, taking into account the change in the electrophysical and geometric parameters of the skin and fat layer and muscle groups when performing actions with a hand. Numerical finite element simulation using anthropometric models of the forearm obtained by volunteers' MRI 3D reconstructions was performed to determine a sufficient degree of the forearm anatomical features detailing in terms of the measured electrical impedance. For the mathematical description of electrical impedance relationships, a forearm two-layer model, represented by the skin-fat layer and muscles, was reasonably chosen, which adequately describes the change in electrical impedance when performing hand actions. Using this model, for the first time, an approach that can be used to determine the acceptable sizes of electrode systems for different parts of the body individually was proposed.

Development of Wrist Interface Based on Fully Actuated Coaxial Spherical Parallel Mechanism for Force Interaction

To develop a wrist robotic exoskeleton-type interface (REI) for force interaction, it should have a suitable range of motion similar to human wrist activities of daily living, large torque output performance, and low moving parts inertia for dynamic motion response to cover the human behavior frequency. In this paper, a wrist REI based on a fully actuated coaxial spherical parallel mechanism (CSPM) is proposed to satisfy the aforementioned features. The fully actuated CSPM-based wrist REI (FC-WREI) has the characteristics of pure rotation similar to the human wrist, high torque output by parallel torque synthesis, and low moving parts inertia due to the base arrangement of the actuators. Due to the mechanical advantages and design optimization, the FC-WREI maximally provides torque as much as 56.49–130.43% of the maximum isometric torque of the human wrist, while providing a consistent range of motion to the human wrist without interference problem. Moreover, it is confirmed that the inertia of the FC-WREI is up to 5.35 times lower than similar devices. These advantages of the FC-WREI mean that the device is applicable to various fields of REIs for force interaction.

A Hybrid Arm-Hand Rehabilitation Robot With EMG-Based Admittance Controller

Reach-and-grasp is one of the most fundamental activities in daily life, while few rehabilitation robots provide integrated and active training of the arm and hand for patients after stroke to improve their mobility. In this study, a novel hybrid arm-hand rehabilitation robot (HAHRR) was built for the reach-and-grasp task. This hybrid structure consisted of a cable-driven module for three-dimensional arm motion and an exoskeleton for hand motion, which enabled assistance of the arm and hand simultaneously. To implement active compliance control, an EMG-based admittance controller was applied to the HAHRR. Experimental results showed that the HAHRR with the EMG-based admittance controller could not only assist the subject in fulfilling the reach-and-grasp task, but also generate smoother trajectories compared with the force-sensing-based admittance controller. These findings also suggested that the proposed approach might be applicable to post-stroke arm-hand rehabilitation training.

Challenges and solutions for application and wider adoption of wearable robots

The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of this article is to address the current challenges that are limiting the application and wider adoption of wearable robots that are typically worn over the human body. We categorized the challenges into mechanical layout, actuation, sensing, body interface, control, human-robot interfacing and coadaptation, and benchmarking. For each category, we discuss specific challenges and the rationale for why solving them is important, followed by an overview of relevant recent works. We conclude with an opinion that summarizes possible solutions that could contribute to the wider adoption of wearable robots.

Design of a powered full-body exoskeleton for physical assistance of elderly people

The development of full-body exoskeletons has been limited due to design complexities, mechanical integration intricacies, and heavier weight, among others. Consequently, very few full-body powered exoskeletons were developed to address these challenges, in spite of increasing demand for physical assistance at full-body level. This article presents an overall design and development of a powered full-body exoskeleton called “FB-AXO.” Primarily, FB-AXO consists of two main subsystems, a lower-body and an upper-body subsystem connected together through waist and spine modules. FB-AXO is developed for the support of weaker ageing adults so that they can continue functioning their daily activities. At the onset of the project, a set of functional and design requirements has been formulated with an extensive end-user involvement and then used in realizing the FB-AXO. The final FB-AXO design comprises of 27 degrees of freedom, of which 10 are active and 17 are passive, having a total system weight of 25 kg. Overall, the article elaborates comprehensively the design, construction, and preliminary testing of FB-AXO. The work effectively addresses design challenges including kinematic compatibility and modularity with innovative solutions. The details of the mechanics, sensors, and electronics of the two subsystems along with specifics of human-exoskeleton interfaces and ranges of motion are also provided. The FB-AXO exoskeleton effectively demonstrated to assist full-body motions such as normal walking, standing, bending as well as executing lifting and carrying tasks to meet the daily living demands of older users.

Gaze-controlled Robot-assisted Painting in Virtual Reality for Upper-limb Rehabilitation

Stroke is the leading cause of adult disability. Robot-assisted rehabilitation systems show great promise for motor recovery after a stroke. In this work, we present a gazecontrolled robotic system for upper limb rehabilitation. Subjects perform a painting task in virtual reality. We designed a novel and challenging painting task to encourage motivation and engagement, as these are critical factors in treatment efficacy. Because the robotic system can be programmed to provide varying amounts of assistance or resistance to the subject, it can be applied to a wide range of patients at different phases of recovery. We describe here the system configured in two modes: resistive control and hierarchical control. The former is designed for later stages of recovery, where the patient's impaired limb has recovered some function. It can be configured to provide varying degrees of resistance by adjusting the properties of an admittance controller. The latter targets patients in more acute phases, where the impaired limb is less responsive. It provides a combination of assistive and corrective control. We pilot tested our system on 10 able-bodied subjects. Our results show that the system can provide varying degrees of resistive control, and that the integration of high level control modulated by gaze can improve engagement. These results suggest that the system may provide a more engaging environment for a wide range of rehabilitative therapies than currently available.

Predicting Intention of Motion During Rehabilitation Tasks of the Upper-Extremity

Rehabilitation promoting "assistance-as-needed" is considered a promising scheme of active rehabilitation, since it can promote neuroplasticity faster and thus reduce the time needed until restoration. To implement such schemes using robotic devices, it is crucial to be able to predict accurately and in real-time the intention of motion of the patient. In this study, we present an intention-of-motion model trained on healthy volunteers. The model is trained using kinematics and muscle activation time series data, and returns future predicted values for the kinematics. We also present the results of an analysis of the sensitivity of the accuracy of the model for different amount of training datasets and varying lengths of the prediction horizon. We demonstrate that the model is able to predict reliably the kinematics of volunteers that were not involved in its training. The model is tested with three types of motion inspired by rehabilibation tasks. In all cases, the model is predicting the arm kinematics with a Root Mean Square Error (RMSE) below 0.12m. Being a non person-specific model, it could be used to predict kinematics even for patients that are not able to perform any motion without assistance. The resulting kinematics, even if not fully representative of the specific patient, might be a preferable input for a robotic rehabilitator than predefined trajectories currently in use.

Prescribed Performance Control for the Upper-Limb Exoskeleton System in Passive Rehabilitation Training Tasks

In this study, a model-free adaptive sliding mode control method was developed in combination with the prescribed performance method. On this basis, this study attempted to fulfill the joint position tracking trajectory task for the one-degree of freedom (DOF) upper-limb exoskeleton in passive robot-assisted rehabilitation. The proposed method is capable of addressing the defect of the initial error in the controller design and the application by adopting a tuning function, as compared with other prescribed performance methods. Moreover, the method developed here was not determined by the dynamic model parameters, which merely exploit the input and output data. Theoretically, the stability exhibited by the proposed controller and the tracking performance can be demonstrated. From the experimental results, the root mean square of the tracking error is equal to 1.06 degrees, and the steady-state tracking error converges to 1.91 degrees. These results can verify the expected performance of the developed control method.

The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis

Background: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evidence regarding which variables might favor a better outcome and how this can be modulated by other factors. Methods: In this within-subject study, we evaluated the efficacy of a robot-assisted rehabilitation system in the recovery of upper limb functions. We performed a path analysis using a structural equation modeling approach in a large sample of 102 stroke patients (age 63.6 ± 13.1 years; 61% men) in the post-acute phase. They underwent 7 weeks of bilateral arm training assisted by an exoskeleton robot combined with a conventional treatment (consisting of simple physical activity together with occupational therapy). The upper extremity section of the Fugl-Meyer (FM-UE) scale at admission was used as a predictor of outcome, whereas age, gender, side of the lesion, days from the event, pain scale, duration of treatment, and number of sessions as mediators. Results: FM-UE at admission was a direct predictor of outcome, as measured by the motricity index of the contralateral upper limb and trunk control test, without any other mediating factors. Age, gender, days from the event, side of lesion, and pain scales were independently associated with outcomes. Conclusions: To the best of our knowledge, this is the first study assessing the relationship between clinical variables and outcomes induced by robot-assisted rehabilitation with a path-analysis model. We define a new route for motor recovery of stroke patients driven by exoskeleton-robot-assisted therapy, highlighting the role of FM-UE at admission as a useful predictor of outcome, although other variables need to be considered in the time-course of disease.

Recovering arm function in chronic stroke patients using combined anodal HD-tDCS and virtual reality therapy (ReArm): a study protocol for a randomized controlled trial

BACKGROUND

After a stroke, 80% of the chronic patients have difficulties to use their paretic upper limb (UL) in activities of daily life (ADL) even after rehabilitation. Virtual reality therapy (VRT) and anodal transcranial direct current stimulation (tDCS) are two innovative methods that have shown independently to positively impact functional recovery of the paretic UL when combined with conventional therapy. The objective of the project will be to evaluate the impact of adding anodal high-definition (HD)-tDCS during an intensive 3-week UL VRT and conventional therapy program on paretic UL function in chronic stroke.

METHODS

The ReArm project is a quadruple-blinded, randomized, sham-controlled, bi-centre, two-arm parallel, and interventional study design. Fifty-eight chronic (> 3 months) stroke patients will be recruited from the Montpellier and Nimes University Hospitals. Patients will follow a standard 3-week in-patient rehabilitation program, which includes 13 days of VRT (Armeo Spring, 1 × 30 min session/day) and conventional therapy (3 × 30 min sessions/day). Twenty-nine patients will receive real stimulation (4x1 anodal HD-tDCS montage, 2 mA, 20 min) to the ipsilesional primary motor cortex during the VRT session and the other 29 patients will receive active sham stimulation (2 mA, 30 s). All outcome measures will be assessed at baseline, at the end of rehabilitation and again 3 months later. The primary outcome measure will be the wolf motor function test. Secondary outcomes will include measures of UL function (Box and Block Test), impairment (Fugl Meyer Upper Extremity), compensation (Proximal Arm Non-Use), ADL (Actimetry, Barthel Index). Other/exploratory outcomes will include pain, fatigue, effort and performance, kinematics, and motor cortical region activation during functional motor tasks.

DISCUSSION

This will be the first trial to determine the impact of adding HD-tDCS during UL VRT and conventional therapy in chronic stroke patients. We hypothesize that improvements in UL function will be greater and longer-lasting with real stimulation than in those receiving sham.

TRIAL REGISTRATION

The ReArm project was approved by The French Research Ethics Committee, (Comité de Protection des Personnes-CPP SUD-EST II, N°ID-RCB: 2019-A00506-51, http://www.cppsudest2.fr/ ). The ReArm project was registered on ClinicalTrials.gov ( NCT04291573 , 2nd March 2020.