A survey on robotic devices for upper limb rehabilitation

Operation Safety of a 2-DoF Planar Mechanism for Arm Rehabilitation

The operation safety of rehabilitation devices must be addressed early in the development process and before being tested on people. In this paper, the operation safety of a 2-DoF (degrees of freedom) planar mechanism for arm rehabilitation is addressed. Then, the safety and efficiency of the device operation is assessed through the Transmission Index (TI) distribution in its workspace. Furthermore, the produced stresses on the human arm are assessed via the FEM (finite element method) when the rehabilitation device reaches five critical positions within its workspace. The TI distribution showed that the proposed design has a proper behaviour from a force transmission point of view, avoiding any singular configuration that might cause a control failure and subsequent risk for the user and supporting the user’s motion with a good efficiency throughout its operational workspace. The FEM analysis showed that Nurse operation is safe for the human arm since a negligible maximum stress of 6.55 × 103 N/m2 is achieved by the human arm when the device is located on the evaluated critical positions.

Bio-Inspired Conceptual Mechanical Design and Control of a New Human Upper Limb Exoskeleton

Safe operation, energy efficiency, versatility and kinematic compatibility are the most important aspects in the design of rehabilitation exoskeletons. This paper focuses on the conceptual bio-inspired mechanical design and equilibrium point control (EP) of a new human upper limb exoskeleton. Considering the upper limb as a multi-muscle redundant system, a similar over-actuated but cable-driven mechatronic system is developed to imitate upper limb motor functions. Additional torque adjusting systems at the joints allow users to lift light weights necessary for activities of daily living (ADL) without increasing electric motor powers of the device. A theoretical model of the “ideal” artificial muscle exoskeleton is also developed using Hill’s natural muscle model. Optimal design parameters of the exoskeleton are defined using the differential evolution (DE) method as a technique of a multi-objective optimization. The proposed cable-driven exoskeleton was then fabricated and tested on a healthy subject. Results showed that the proposed system fulfils the desired aim properly, so that it can be utilized in the design of rehabilitation robots. Further studies may include a spatial mechanism design, which is especially important for the shoulder rehabilitation, and development of reinforcement learning control algorithms to provide more efficient rehabilitation treatment.

Wearable Robots: An Original Mechatronic Design of a Hand Exoskeleton for Assistive and Rehabilitative Purposes

Robotic devices are being employed in more and more sectors to enhance, streamline, and augment the outcomes of a wide variety of human activities. Wearable robots arise indeed as of-vital-importance tools for telerehabilitation or home assistance targeting people affected by motor disabilities. In particular, the field of “Robotics for Medicine and Healthcare” is attracting growing interest. The development of such devices is a primarily addressed topic since the increasing number of people in need of rehabilitation or assistive therapies (due to population aging) growingly weighs on the healthcare systems of the nation. Besides, the necessity to move to clinics represents an additional logistic burden for patients and their families. Among the various body parts, the hand is specially investigated since it most ensures the independence of an individual, and thus, the restoration of its dexterity is considered a high priority. In this study, the authors present the development of a fully wearable, portable, and tailor-made hand exoskeleton designed for both home assistance and telerehabilitation. Its purpose is either to assist patients during activities of daily living by running a real-time intention detection algorithm or to be used for remotely supervised or unsupervised rehabilitation sessions by performing exercises preset by therapists. Throughout the mechatronic design process, special attention has been paid to the complete wearability and comfort of the system to produce a user-friendly device capable of assisting people in their daily life or enabling recorded home rehabilitation sessions allowing the therapist to monitor the state evolution of the patient. Such a hand exoskeleton system has been designed, manufactured, and preliminarily tested on a subject affected by spinal muscular atrophy, and some results are reported at the end of the article.

Validation of a Hybrid Exoskeleton for Upper Limb Rehabilitation. A Preliminary Study

Recovery of therapeutic or functional ambulatory capacity in patients with rotator cuff injury is a primary goal of rehabilitation. Wearable powered exoskeletons allow patients to perform repetitive practice with large movements to maximize recovery, even immediately after the acute event. The aim of this paper is to describe the usability, acceptability and acceptance of a hybrid exoskeleton for upper-limb passive rehabilitation using the System Usability Scale (SUS) questionnaire. This equipment, called ExoFlex, is defined as a hybrid exoskeleton since it is made up of rigid and soft components. The exoskeleton mechanical description is presented along with its control system and the way motion is structured in rehabilitation sessions. Seven patients (six women and one man) have participated in the evaluation of this equipment, which are in the range of 50 to 79 years old. Preliminary evidence of the acceptance and usability by both patients and clinicians are very promising, obtaining an average score of 80.71 in the SUS test, as well as good results in a questionnaire that evaluates the clinicians' perceived usability of ExoFlex.

Nonlinear time delay estimation based model reference adaptive impedance control for an upper-limb human-robot interaction

A nonlinear Time Delay Estimation (TDE) based model reference adaptive impedance controller was developed for Tarbiat Modares University Upper Limbs Rehabilitation Robot (TUERR). The proposed controller uses a stable reference impedance model, which produces desired dynamic relationship between applied force and position error for the robot End-effector to track the desired trajectory. TDE based model reference adaptive controller estimates unknown system dynamics and uncertainties, and the adaption law modifies the controller gains. Using a Lyapunov function was shown trajectory tracking errors in the overall system are bounded. In addition, a performance-based velocity profile proposed to modify the pace of trajectory planning considering the deviation from the desired path. Finally, the performance of the presented controller and rehabilitation process is experimentally investigated for TUERR.

Assistive Sliding Mode Control of a Rehabilitation Robot with Automatic Weight Adjustment

There are approximately 13 million new stroke cases worldwide each year. Research has shown that robotics can provide practical and efficient solutions for expediting post-stroke patient recovery. This simulation study aimed to design a sliding mode controller (SMC) for an end-effector-based rehabilitation robot. A genetic algorithm (GA) was designed for automatic controller weight adjustment. The optimal weights were obtained by minimizing a cost function comprising the end-effector position error, robot input, robot input-rate, and patient input. To promote safe tuner optimization, a model of the human arm was incorporated to generate the human joint torque. A computed-torque proportional derivative controller (CTPD) was designed for the human arm to approximate the central nervous system (CNS) motor control. This controller was adjusted to simulate rehabilitation effects and patient adaptation. The tuner was optimized for a trajectory tracking task with an assistive high-level control scheme. The simulation results showed lower cost compared to seven manual weight settings. The optimal weights provided good tracking performance and suitable robot inputs. This research provides a framework to conduct various simulations before testing our controller on human subjects. The preliminary results of this study will be used as the starting point for online adaptive controller tuning, which will be examined in our future research.

The Rehabilitation Effects of Myoelectric Powered Wearable Orthotics on Improving Upper Extremity Function in Persons with SCI

Upper extremity (UE) weakness and/or paralysis following spinal cord injury (SCI) can lead to a limited capacity to perform activities of daily living (ADL). Such disability significantly reduces an individual's level of independence. Further, restoration of UE motor function in people with SCI remains a high priority in rehabilitation and the field of assistive technology. The overall goal of this study was to evaluate the effects of a myoelectric-powered wearable orthosis (MPWO) manufactured by MyoMo, Inc. (Boston, MA) for UE movement assistance on ameliorating UE motor function in order to improve ADL and quality of life in people with SCI. Two male participants with chronic incomplete SCI (iSCI), a 75- and a 31-year-old with AIS D and B, respectively, underwent 18 sessions (over 6 weeks) of UE movement rehabilitation using the MPWO. Handgrip strength, active range of motion (AROM) of the hand, response time to initiate a movement, and muscles activations were examined before and after the rehabilitation training using the MPWO. The response time to initiate UE movements decreased, and handgrip strength and AROM improved after training with the MPWO. These preliminary data suggest that rehabilitation with the use of the UE-MPWO device could enhance the participants' UE activities that led to improved function.Clinical Relevance- These preliminary results from two individuals with iSCI suggest that training with UE-MPWO assistive devices may improve UE utilization during ADL for individuals with muscle weakness or paralysis but still possessing residual voluntary muscle activation capabilities.

Upper Extremity Functional Improvements in Persons with SCI Resulted from Daily Utilization of Myoelectric Powered Wearable Orthotics

Spinal cord injury (SCI) is a medically complex and life-disrupting condition. It is estimated that 17,700 new traumatic SCI cases are reported each year in the United States. Approximately half of those cases, involves paralysis, sensory loss, and impaired motor control in the upper extremity (UE) and lower extremities. Such impairments could affect the person's independence as well as their family members and caregiver. The limitation at the UE can significantly limit the general activities of daily living (ADL). The purpose of this paper is to determine the daily utilization effects on changing the handgrip AROM and handgrip forces before and after providing upper extremity in-clinic rehabilitation along with at-home utilization using an UE myoelectric powered wearable orthosis (UE-MPWO) in a person with incomplete spinal cord injury (iSCI). This device helps restore function to the weakened or paralyzed UE muscles. We demonstrate that the handgrip AROM and handgrip force improved after 6-weeks of training with the UE-MPWO. The overall goal of this study was to evaluate the effects of UE-MPWO (MyoPro) when utilized for in-clinic rehabilitation combined with at-home daily use in improving UE movement and function of people with iSCI.Clinical Relevance- The results of in-clinic rehabilitation combined with at-home daily utilization suggest that this UE-MPWO may improve UE function. The examined UE-MPWO could represent a relatively good example as a rehabilitation and assistive tool for persons with iSCI.

The iHand clinical trial protocol: multi-center uncontrolled intervention study to examine the therapeutic effect of a soft-robotic glove as assistive device to support people with impaired hand strength during activities of daily living (Preprint)

Background

Decline of hand function, especially reduced hand strength, is a common problem that can be caused by many disorders and results in difficulties performing activities of daily living. A wearable soft robotic glove may be a solution, enabling use of the affected arm and hand repeatedly during functional daily activities and providing intensive and task-specific training simultaneously with assistance of hand function.

Objective

We aim to investigate the therapeutic effect of an assistive soft robotic glove (Carbonhand).

Methods

This multicenter uncontrolled intervention study consists of 3 preassessments (T0, T1, and T2), a postassessment (T3), and a follow-up assessment (T4). Participants are patients who experience hand function limitations. For the intervention, participants will use the glove during activities of daily living at home for 6 weeks, with a recommended use of at least 180 minutes per week. The primary outcome measure is handgrip strength, and secondary outcome measures are related to functional arm and hand abilities, amount of glove use, and quality of life.

Results

The first participant was included on June 25, 2019. Currently, the study has been extended due to the COVID-19 pandemic; data collection and analysis are expected to be completed in 2022.

Conclusions

The Carbonhand system is a wearable assistive device, allowing performance of functional activities to be enhanced directly during functional daily activities. At the same time, active movement of the user is encouraged as much as possible, which has potential to provide highly intensive and task-specific training. As such, it is one of the first assistive devices to incorporate assist-as-needed principles. This is the first powered clinical trial that investigates the unique application of an assistive grip-supporting soft robotic glove outside of clinical settings with the aim to have a therapeutic effect.

Trial Registration

Netherlands Trial Register NTR NL7561; https://www.trialregister.nl/trial/7561

International Registered Report Identifier (IRRID)

DERR1-10.2196/34200

Development of a revolute-type kinematic model for human upper limb using a matrix approach

A mathematical model is proposed for a revolute joint mechanism with an n-degree of freedom (DOF). The matrix approach is used for finding the relation between two consecutive links to determine desired link parameters such as position, velocity and acceleration using the forward kinematic approach. The matrix approach was confirmed for a proposed 10 DOF revolute type (R-type) human upper limb model with servo motors at each joint. Two DOFs are considered each at shoulder, elbow and wrist joint, followed by four DOF for the fingers. Two DOFs were considered for metacarpophalangeal (mcp) and one DOF each for proximal interphalangeal (pip) and distal interphalangeal (dip) joints. MATLAB script function was used to evaluate the mathematical model for determining kinematic parameters for all the proposed human upper limb model joints. The simplified method for kinematic analysis proposed in this paper will further simplify the dynamic modeling of any mechanism for determining joint torques and hence, easy to design control system for joint movements.

Home-based self-help telerehabilitation of the upper limb assisted by an electromyography-driven wrist/hand exoneuromusculoskeleton after stroke

BACKGROUND

Most stroke survivors have sustained upper limb impairment in their distal joints. An electromyography (EMG)-driven wrist/hand exoneuromusculoskeleton (WH-ENMS) was developed previously. The present study investigated the feasibility of a home-based self-help telerehabilitation program assisted by the aforementioned EMG-driven WH-ENMS and its rehabilitation effects after stroke.

METHODS

Persons with chronic stroke (n = 11) were recruited in a single-group trial. The training progress, including the training frequency and duration, was telemonitored. The clinical outcomes were evaluated using the Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), Wolf Motor Function Test (WMFT), Motor Functional Independence Measure (FIM), and Modified Ashworth Scale (MAS). Improvement in muscle coordination was investigated in terms of the EMG activation level and the Co-contraction Index (CI) of the target muscles, including the abductor pollicis brevis (APB), flexor carpi radialis-flexor digitorum (FCR-FD), extensor carpi ulnaris-extensor digitorum (ECU-ED), biceps brachii (BIC), and triceps brachii (TRI). The movement smoothness and compensatory trunk movement were evaluated in terms of the following two kinematic parameters: number of movement units (NMUs) and maximal trunk displacement (MTD). The above evaluations were conducted before and after the training.

RESULTS

All of the participants completed the home-based program with an intensity of 63.0 ± 1.90 (mean ± SD) min/session and 3.73 ± 0.75 (mean ± SD) sessions/week. After the training, motor improvements in the entire upper limb were found, as indicated by the significant improvements (P < 0.05) in the FMA, ARAT, WMFT, and MAS; significant decreases (P < 0.05) in the EMG activation levels of the APB and FCR-FD; significant decreases (P < 0.05) in the CI of the ECU-ED/FCR-FD, ECU-ED/BIC, FCR-FD/APB, FCR-FD/BIC, FCR-FD/TRI, APB/BIC and BIC/TRI muscle pairs; and significant reductions (P < 0.05) in the NMUs and MTD.

CONCLUSIONS

The results suggested that the home-based self-help telerehabilitation program assisted by EMG-driven WH-ENMS is feasible and effective for improving the motor function of the paretic upper limb after stroke. Trial registration ClinicalTrials.gov. NCT03752775; Date of registration: November 20, 2018.

Robotic devices for paediatric rehabilitation: a review of design features

Children with physical disabilities often have limited performance in daily activities, hindering their physical development, social development and mental health. Therefore, rehabilitation is essential to mitigate the adverse effects of the different causes of physical disabilities and improve independence and quality of life. In the last decade, robotic rehabilitation has shown the potential to augment traditional physical rehabilitation. However, to date, most robotic rehabilitation devices are designed for adult patients who differ in their needs compared to paediatric patients, limiting the devices' potential because the paediatric patients' needs are not adequately considered. With this in mind, the current work reviews the existing literature on robotic rehabilitation for children with physical disabilities, intending to summarise how the rehabilitation robots could fulfil children's needs and inspire researchers to develop new devices. A literature search was conducted utilising the Web of Science, PubMed and Scopus databases. Based on the inclusion-exclusion criteria, 206 publications were included, and 58 robotic devices used by children with a physical disability were identified. Different design factors and the treated conditions using robotic technology were compared. Through the analyses, it was identified that weight, safety, operability and motivation were crucial factors to the successful design of devices for children. The majority of the current devices were used for lower limb rehabilitation. Neurological disorders, in particular cerebral palsy, were the most common conditions for which devices were designed. By far, the most common actuator was the electric motor. Usually, the devices present more than one training strategy being the assistive strategy the most used. The admittance/impedance method is the most popular to interface the robot with the children. Currently, there is a trend on developing exoskeletons, as they can assist children with daily life activities outside of the rehabilitation setting, propitiating a wider adoption of the technology. With this shift in focus, it appears likely that new technologies to actuate the system (e.g. serial elastic actuators) and to detect the intention (e.g. physiological signals) of children as they go about their daily activities will be required.

Wheelchair-Mounted Upper Limb Robotic Exoskeleton with Adaptive Controller for Activities of Daily Living

Neuro-muscular disorders and diseases such as cerebral palsy and Duchenne Muscular Dystrophy can severely limit a person's ability to perform activities of daily living (ADL). Exoskeletons can provide an active or passive support solution to assist these groups of people to perform ADL. This study presents an artificial neural network-trained adaptive controller mechanism that uses surface electromyography (sEMG) signals from the human forearm to detect hand gestures and navigate an in-house-built wheelchair-mounted upper limb robotic exoskeleton based on the user's intent while ensuring safety. To achieve the desired position of the exoskeleton based on human intent, 10 hand gestures were recorded from 8 participants without upper limb movement disabilities. Participants were tasked to perform water bottle pick and place activities while using the exoskeleton, and sEMG signals were collected from the forearm and processed through root mean square, median filter, and mean feature extractors prior to training a scaled conjugate gradient backpropagation artificial neural network. The trained network achieved an average of more than 93% accuracy, while all 8 participants who did not have any prior experience of using an exoskeleton were successfully able to perform the task in less than 20 s using the proposed artificial neural network-trained adaptive controller mechanism. These results are significant and promising thus could be tested on people with muscular dystrophy and neuro-degenerative diseases.

Degree of muscle-and-tendon tonus effects on kinesthetic illusion in wrist joints toward advanced rehabilitation robotics

Due to increasing demand for rehabilitation and therapy for cerebrovascular diseases, patients require advanced development of medical rehabilitation robots. In our laboratory, we focus on the formation capability of the substitute neural path caused by brain plasticity using the kinesthetic illusion (KI), which is effective for therapies using robots. In KI, people perceive an illusionary limb movement without an actual movement when a vibration stimulus is applied to a limb’s tendons. In previous research, the optimal frequency that induces the maximum KI has a correlation factor of about 0.5 with the tendon’s natural frequency when a human subject is in a state of laxity. However, we do not know whether the above finding can be applied to actual rehabilitation because muscles and tendons are sometimes in tonus during rehabilitation, a state that varies the natural frequency. In this study, we investigate the correlation between the optimal and natural frequencies of tendon by systematically changing their tension to clarify the effects on the illusion induced by the muscle and the tendon when they are in tonus. We identified a negative correlation between the optimal and natural frequencies when they are in tonus, although a positive correlation appeared when they are in laxity. This result suggests that KI’s optimal frequency should be changed based on the degree of the tendon and muscle tonus. Therefore, our present findings provide a suitable vibration frequency that induces KI due to the degree of the tendon and muscle tonus during robot therapies.

Education 4.0: Teaching the Basis of Motor Imagery Classification Algorithms for Brain-Computer Interfaces

Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. As a consequence, there is a growing demand for educational material that introduces science and engineering students to technologies, such as Artificial Intelligence (AI) and Brain–Computer Interfaces (BCI). Thus, our contribution towards the development of this material is to create a test bench for BCI given the basis and analysis on how they can be discriminated against. This is shown using different AI methods: Fisher Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), Restricted Boltzmann Machines (RBM) and Self-Organizing Maps (SOM), allowing students to see how input changes alter their performance. These tests were done against a two-class Motor Image database. First, using a large frequency band and no filtering eye movement. Secondly, the band was reduced and the eye movement was filtered. The accuracy was analyzed obtaining values around 70∼80% for all methods, excluding SVM and SOM mapping. Accuracy and mapping differentiability increased for some subjects for the second scenario 70∼85%, meaning either their band with the most significant information is on that limited space or the contamination because of eye movement was better mitigated by the regression method. This can be translated to saying that these methods work better under limited spaces. The outcome of this work is useful to show future scientists and engineers how BCI experiments are conducted while teaching them the basics of some AI techniques that can be used in this and other several experiments that can be carried on the framework of Education 4.0.

Effect of Robot-Assisted Therapy on Participation of People with Limited Upper Limb Functioning: A Systematic Review with GRADE Recommendations

Background

Previous studies have suggested that robot-assisted therapy (RT) is effective in treating impairment and that it may also improve individuals' participation.

Objective

To investigate the effect of RT on the participation of individuals with limited upper limb functioning (PROSPERO: CRD42019133880). Data Sources: PEDro, Embase, MEDLINE, CINAHL, Cochrane, AMED, and Compendex. Inclusion Criteria. We selected randomized or quasirandomized controlled studies comparing the effects of RT with minimal or other interventions on participation of individuals with limited upper limb functioning. Data Extraction and Synthesis. Methodological quality of the included studies was assessed using the 0-10 PEDro scale, and effect estimates were reported using standardized mean differences (SMDs) with 95% confidence intervals (CIs), and the certainty of the current evidence was assessed using the GRADE.

Results

Twelve randomized controlled studies involving 845 participants were included. The estimates of medium effects between RT and minimal intervention (MI) at a short-term follow-up were pooled, but there are no short-term effects between RT and OI. Standardized differences in means were as follows: 0.6 (95% CI 0.1 to 1.2) and 0.2 (95% CI -0.0 to 0.4). There were also no effects of additional RT in the short- or medium-term follow-up periods. Standardized differences in means were as follows: -0.6 (95% CI -1.1 to -0.1) and 0.2 (95% CI -0.3 to 0.8). The methodological quality of the included studies potentially compromised the effect estimates of RT. The existing evidence was very low-quality with many confounding variables between studies.

Conclusions

For patients with upper limb neurological dysfunction, low-quality evidence supports RT over MI in terms of improving individual participation in the short term. The existing low- to very low-quality evidence does not support RT over OI in either the short- or medium-term follow-up periods with respect to community participation.

Design and Experimental Characterization of L-CADEL v2, an Assistive Device for Elbow Motion

An experimental characterization is presented for an improved version of a wearable assistive device for elbow motion. The design is revised with respect to requirements for elbow motion assistance, looking at applications both in rehabilitation therapies and exercising of elderly people. A laboratory prototype is built with lightweight, portable, easy-to-use features that are verified with test results, whose discussion is also provided as a characterization of operating performance.

Design and Development of an Upper Limb Rehabilitative Robot with Dual Functionality

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called ‘u-Rob’ that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer’s interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot.

A scoping review of design requirements for a home-based upper limb rehabilitation robot for stroke

BACKGROUND

Home-based robotic therapy is a trend of post-stroke upper limb rehabilitation. Although home-based upper limb rehabilitation robots have been developed over several decades, no design specification has been published.

OBJECTIVES

To identify and synthesize design requirements considering user and technology needs for a home-based upper limb rehabilitation robot through a scoping review.

METHOD

Studies published between 1 January 2000 and 10 June 2020 in Scopus, Web of Science and PubMed database regarding design requirements for upper limb rehabilitation robots from of stroke survivors or therapists were identified and analyzed. We use 'requirement' as something that is needed or wanted. Two physiotherapists ranked the requirements identified from literature review.

RESULTS

Nine studies were selected for review. They identified 42 requirements regarding functionality (n = 11, 26.2% of total requirements), usability (n = 16, 38.0% of total requirements), software (n = 14, 33.3% of total requirements) and safety (n = 1, 2.4% of total requirements). The main implementation barriers with respect to adherence and monitoring were space, operation, and cost.

CONCLUSION

This is the first research to summarize the design requirements for home-based upper limb rehabilitation robots for stroke survivors. The need for a safe, comfortable, easy to use device which can be individualized and promote specific movements and tasks emerged. The result of this paper captures the design requirements that can be used in future for the development of a design specification. It provides designers and researchers guidance about the real-world needs for home-based upper limb rehabilitation robots for stroke.

Improving patient rehabilitation performance in exercise games using collaborative filtering approach

BACKGROUND

Virtual reality is utilised in exergames to help patients with disabilities improve on the movement of their limbs. Exergame settings, such as the game difficulty, play important roles in the rehabilitation outcome. Similarly, suboptimal exergames' settings may adversely affect the accuracy of the results obtained. As such, the improvement in patients' movement performances falls below the desired expectations. In this paper, a recommender system is incorporated to suggest the most preferred movement setting for each patient, based on the movement history of the patient.

METHOD

The proposed recommender system (ResComS) suggests the most suitable setting necessary to optimally improve patients' rehabilitation performances. In the course of developing the recommender system, three methods are proposed and compared: ReComS (K-nearest neighbours and collaborative filtering algorithms), ReComS+ (k-means, K-nearest neighbours, and collaborative filtering algorithms) and ReComS++ (bacterial foraging optimisation, k-means, K-nearest neighbours, and collaborative filtering algorithms). The experimental datasets are collected using the Medical Interactive Recovery Assistant (MIRA) software platform.

RESULT

Experimental results, validated by the patients' exergame performances, reveal that the ReComS++ approach predicts the best exergame settings for patients with 85.76% accuracy.

Exoskeleton-Assisted Anthropomorphic Movement Training (EAMT) for Poststroke Upper Limb Rehabilitation: A Pilot Randomized Controlled Trial

OBJECTIVE

To investigate the feasibility of exoskeleton-assisted anthropomorphic movement training (EAMT) and its effects on upper extremity motor impairment, function, and kinematics after stroke.

DESIGN

A single-blind pilot randomized controlled trial.

SETTING

Stroke rehabilitation inpatient unit.

PARTICIPANTS

Participants with a hemiplegia (N=20) due to a first-ever, unilateral, subacute stroke who had a score of 8-47 on the Fugl-Meyer Assessment for Upper Extremity (FMA-UE).

INTERVENTIONS

The exoskeleton group received EAMT therapy that provided task-specific training under anthropomorphic trajectories and postures. The control group received conventional upper limb therapy. For both groups, therapy was delivered at the same intensity, frequency, and duration: 45 minutes daily, 5 days per week, for 4 weeks.

MAIN OUTCOME MEASURES

Primary outcome: feasibility analysis.

SECONDARY OUTCOMES

FMA-UE, Action Research Arm Test (ARAT), modified Barthel Index (MBI), and kinematic metrics during exoskeleton therapy.

RESULTS

Twenty participants with subacute stroke were recruited and completed all therapy sessions. EAMT therapy was feasible and acceptable for the participants. The recruitment rate, retention rate, and number of therapists required for EAMT therapy were acceptable compared with other robotic trials. EAMT was determined to be safe, as no adverse event occurred except tolerable muscle fatigue in 2 participants. There were significant between-group differences in the change scores of FMA-UE (difference, 4.30 points; P=.04) and MBI (difference, 8.70 points; P=.03) in favor of EAMT therapy. No significant between-group difference was demonstrated for the change scores of ARAT (P=.18). Participants receiving EAMT showed significant improvements in kinematic metrics after treatment (P<.01).

CONCLUSIONS

Our results indicate that EAMT is a feasible approach and may improve upper extremity motor impairment, activities of daily living, and kinematics after stroke. However, fully powered randomized controlled trials are warranted to confirm the results of this pilot study and explore the underlying mechanisms by which EAMT therapy might work.

Attention Enhancement for Exoskeleton-Assisted Hand Rehabilitation Using Fingertip Haptic Stimulation

Active enrollment in rehabilitation training yields better treatment outcomes. This paper introduces an exoskeleton-assisted hand rehabilitation system. It is the first attempt to combine fingertip cutaneous haptic stimulation with exoskeleton-assisted hand rehabilitation for training participation enhancement. For the first time, soft material 3D printing techniques are adopted to make soft pneumatic fingertip haptic feedback actuators to achieve cheaper and faster iterations of prototype designs with consistent quality. The fingertip haptic stimulation is synchronized with the motion of our hand exoskeleton. The contact force of the fingertips resulted from a virtual interaction with a glass of water was based on data collected from normal hand motions to grasp a glass of water. System characterization experiments were conducted and exoskeleton-assisted hand motion with and without the fingertip cutaneous haptic stimulation were compared in an experiment involving healthy human subjects. Users' attention levels were monitored in the motion control process using a Brainlink EEG-recording device and software. The results of characterization experiments show that our created haptic actuators are lightweight (6.8 ± 0.23 g each with a PLA fixture and Velcro) and their performance is consistent and stable with small hysteresis. The user study experimental results show that participants had significantly higher attention levels with additional haptic stimulations compared to when only the exoskeleton was deployed; heavier stimulated grasping weight (a 300 g glass) was associated with significantly higher attention levels of the participants compared to when lighter stimulated grasping weight (a 150 g glass) was applied. We conclude that haptic stimulations increase the involvement level of human subjects during exoskeleton-assisted hand exercises. Potentially, the proposed exoskeleton-assisted hand rehabilitation with fingertip stimulation may better attract user's attention during treatment.

Upper Limb Home-Based Robotic Rehabilitation During COVID-19 Outbreak

The coronavirus disease (COVID-19) outbreak requires rapid reshaping of rehabilitation services to include patients recovering from severe COVID-19 with post-intensive care syndromes, which results in physical deconditioning and cognitive impairments, patients with comorbid conditions, and other patients requiring physical therapy during the outbreak with no or limited access to hospital and rehabilitation centers. Considering the access barriers to quality rehabilitation settings and services imposed by social distancing and stay-at-home orders, these patients can be benefited from providing access to affordable and good quality care through home-based rehabilitation. The success of such treatment will depend highly on the intensity of the therapy and effort invested by the patient. Monitoring patients' compliance and designing a home-based rehabilitation that can mentally engage them are the critical elements in home-based therapy's success. Hence, we study the state-of-the-art telerehabilitation frameworks and robotic devices, and comment about a hybrid model that can use existing telerehabilitation framework and home-based robotic devices for treatment and simultaneously assess patient's progress remotely. Second, we comment on the patients' social support and engagement, which is critical for the success of telerehabilitation service. As the therapists are not physically present to guide the patients, we also discuss the adaptability requirement of home-based telerehabilitation. Finally, we suggest that the reformed rehabilitation services should consider both home-based solutions for enhancing the activities of daily living and an on-demand ambulatory rehabilitation unit for extensive training where we can monitor both cognitive and motor performance of the patients remotely.

Effectiveness of robotic-assisted therapy for upper extremity function in children and adolescents with cerebral palsy: a systematic review protocol

INTRODUCTION

The application of advanced technologies in paediatric rehabilitation to improve performance and enhance everyday functioning shows considerable promise. The aims of this systematic review are to investigate the effectiveness of robotic-assisted therapy for upper extremity function in children and adolescents with cerebral palsy and to extend the scope of intervention from empirical evidence.

METHODS AND ANALYSIS

Multiple databases, including MEDLINE (Ovid), PubMed, CINAHL, Scopus, Web of Science, Cochrane Library and IEEE Xplore, will be comprehensively searched for relevant randomised controlled trials and non-randomised studies. The grey literature will be accessed on the ProQuest Dissertations & Theses Global database, and a hand search from reference lists of previous articles will be performed. The papers written in English language will be considered, with no limitation on publication date. Two independent reviewers will identify eligible studies, evaluate the level of evidence (the Oxford Centre for Evidence-Based Medicine) and appraise methodological quality and risk of bias (the Standard quality assessment criteria for evaluating primary research papers from a variety of fields (QualSyst tool); the Grading of Recommendations Assessment, Development and Evaluation). Data will be appropriately extracted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. A narrative synthesis will be provided to summarise the results, and a meta-analysis will be conducted if there is sufficient homogeneity across outcomes.

PROSPERO REGISTRATION NUMBER

CRD42020205818.

ETHICS AND DISSEMINATION

Ethical approval is not required for this study. The findings will be disseminated via a peer-reviewed journal and international conferences.

Evidence of neuroplasticity with robotic hand exoskeleton for post-stroke rehabilitation: a randomized controlled trial

Background

A novel electromechanical robotic-exoskeleton was designed in-house for the rehabilitation of wrist joint and Metacarpophalangeal (MCP) joint.

Objective

The objective was to compare the rehabilitation effectiveness (clinical-scales and neurophysiological-measures) of robotic-therapy training sessions with dose-matched conventional therapy in patients with stroke.

Methods

A pilot prospective parallel randomized controlled study at clinical settings was designed for patients with stroke within 2 years of chronicity. Patients were randomly assigned to receive an intervention of 20 sessions of 45 min each, five days a week for four weeks, in Robotic-therapy Group (RG) (n = 12) and conventional upper-limb rehabilitation in Control-Group (CG) (n = 11). We intended to evaluate the effects of a novel exoskeleton based therapy on the functional rehabilitation outcomes of upper-limb and cortical-excitability in patients with stroke as compared to the conventional-rehabilitation. Clinical-scales– Modified Ashworth Scale, Active Range of Motion, Barthel-Index, Brunnstrom-stage and Fugl-Meyer (FM) scale and neurophysiological measures of cortical-excitability (using Transcranial Magnetic Stimulation) –Motor Evoked Potential and Resting Motor threshold, were acquired pre- and post-therapy.

Results

No side effects were noticed in any of the patients. Both RG and CG showed significant (p < 0.05) improvement in all clinical motor-outcomes except Modified Ashworth Scale in CG. RG showed significantly (p < 0.05) higher improvement over CG in Modified Ashworth Scale, Active Range of Motion and Fugl-Meyer scale and FM Wrist-/Hand component. An increase in cortical-excitability in ipsilesional-hemisphere was found to be statistically significant (p < 0.05) in RG over CG, as indexed by a decrease in Resting Motor Threshold and increase in the amplitude of Motor Evoked Potential. No significant changes were shown by the contralesional-hemisphere. Interhemispheric RMT-asymmetry evidenced significant (p < 0.05) changes in RG over CG indicating increased cortical-excitability in ipsilesional-hemisphere along with interhemispheric changes.

Conclusion

Robotic-exoskeleton training showed improvement in motor outcomes and cortical-excitability in patients with stroke. Neurophysiological changes in RG could most likely be a consequence of plastic reorganization and use-dependent plasticity.

Trial registry number: ISRCTN95291802

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00867-7.

Robotic-assisted gait rehabilitation following stroke: a systematic review of current guidelines and practical clinical recommendations

INTRODUCTION

Stroke is the third leading cause of adult disability worldwide, and lower extremity motor impairment is one of the major determinants of long-term disability. Although robotic therapy is becoming more and more utilized in research protocols for lower limb stroke rehabilitation, the gap between research evidence and its use in clinical practice is still significant. The aim of this study was to determine the scope, quality, and consistency of guidelines for robotic lower limb rehabilitation after stroke, in order to provide clinical recommendations.

EVIDENCE ACQUISITION

We systematically reviewed stroke rehabilitation guideline recommendations between January 1, 2010 and October 31, 2020. We explored electronic databases (N.=4), guideline repositories and professional rehabilitation networks (N.=12). Two independent reviewers used the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, and brief syntheses were used to evaluate and compare the different recommendations, considering only the most recent version.

EVIDENCE SYNTHESIS

From the 1219 papers screened, ten eligible guidelines were identified from seven different regions/countries. Four of the included guidelines focused on stroke management, the other six on stroke rehabilitation. Robotic rehabilitation is generally recommended to improve lower limb motor function, including gait and strength. Unfortunately, there is still no consensus about the timing, frequency, training session duration and the exact characteristics of subjects who could benefit from robotics.

CONCLUSIONS

Our systematic review shows that the introduction of robotic rehabilitation in standard treatment protocols seems to be the future of stroke rehabilitation. However, robot assisted gait training (RAGT) for stroke needs to be improved with new solutions and in clinical practice guidelines, especially in terms of applicability.

Kinematic of the Position and Orientation Synchronization of the Posture of a n DoF Upper-Limb Exoskeleton with a Virtual Object in an Immersive Virtual Reality Environment

Exoskeletons are an external structural mechanism with joints and links that work in tandem with the user, which increases, reinforces, or restores human performance. Virtual Reality can be used to produce environments, in which the intensity of practice and feedback on performance can be manipulated to provide tailored motor training. Will it be possible to combine both technologies and have them synchronized to reach better performance? This paper consists of the kinematics analysis for the position and orientation synchronization between an n DoF upper-limb exoskeleton pose and a projected object in an immersive virtual reality environment using a VR headset. To achieve this goal, the exoskeletal mechanism is analyzed using Euler angles and the Pieper technique to obtain the equations that lead to its orientation, forward, and inverse kinematic models. This paper extends the author’s previous work by using an early stage upper-limb exoskeleton prototype for the synchronization process.

Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke

The quality of arm movements typically improves in the sub-acute phase of stroke affecting the upper extremity. Here, we used whole arm kinematic analysis during reaching movements to distinguish whether these improvements are due to true recovery or to compensation. Fifty-three participants with post-acute stroke performed ∼80 reaching movement tests during 4 weeks of training with the ArmeoSpring exoskeleton. All participants showed improvements in end-effector performance, as measured by movement smoothness. Four ArmeoSpring angles, shoulder horizontal (SH) rotation, shoulder elevation (SE), elbow rotation, and forearm rotation, were recorded and analyzed. We first characterized healthy joint coordination patterns by performing a sparse principal component analysis on these four joint velocities recorded during reaching tests performed by young control participants. We found that two dominant joint correlations [SH with elbow rotation and SE with forearm rotation] explained over 95% of variance of joint velocity data. We identified two clusters of stroke participants by comparing the evolution of these two correlations in all tests. In the "Recoverer" cluster (N = 19), both joint correlations converged toward the respective correlations for control participants. Thus, Recoverers relearned how to generate smooth end-effector movements while developing joint movement patterns similar to those of control participants. In the "Compensator" cluster (N = 34), at least one of the two joint correlations diverged from the corresponding correlation of control participants. Compensators relearned how to generate smooth end-effector movements by discovering various new compensatory movement patterns dissimilar to those of control participants. New compensatory patterns included atypical decoupling of the SE and forearm joints, and atypical coupling of the SH rotation and elbow joints. There was no difference in clinical impairment level between the two groups either at the onset or at the end of training as assessed with the Upper Extremity Fugl-Meyer scale. However, at the start of training, the Recoverers showed significantly faster improvements in end-effector movement smoothness than the Compensators. Our analysis can be used to inform neurorehabilitation clinicians on how to provide movement feedback during practice and suggest avenues for refining exoskeleton robot therapy to reduce compensatory patterns.

Effects of a Soft Robotic Hand for Hand Rehabilitation in Chronic Stroke Survivors

OBJECTIVES

Soft robotic hands are proposed for stroke rehabilitation in terms of their high compliance and low inherent stiffness. We investigated the clinical efficacy of a soft robotic hand that could actively flex and extend the fingers in chronic stroke subjects with different levels of spasticity.

METHODS

Sixteen chronic stroke subjects were recruited into this single-group study. Subjects underwent 20 sessions of 1-hour EMG-driven soft robotic hand training. Training effect was evaluated by the pre-training and post-training assessments with the clinical scores: Action Research Arm Test(ARAT), Fugl-Meyer Assessment for Upper Extremity(FMA-UE), Box-and-Block test(BBT), Modified Ashworth Scale(MAS), and maximum voluntary grip strength.

RESULTS

For all the recruited subjects (n = 16), significant improvement of upper limb function was generally observed in ARAT (increased mean=2.44, P = 0.032), FMA-UE (increased mean=3.31, P = 0.003), BBT (increased mean=1.81, P = 0.024), and maximum voluntary grip strength (increased mean=2.14 kg, P < 0.001). No significant change was observed in terms of spasticity with the MAS (decreased mean=0.11, P = 0.423). Further analysis showed subjects with mild or no finger flexor spasticity (MAS<2, n = 9) at pre-training had significant improvement of upper limb function after 20 sessions of training. However, for subjects with moderate and severe finger flexor spasticity (MAS=2,3, n = 7) at pre-training, no significant change in clinical scores was shown and only maximum voluntary grip strength had significant increase.

CONCLUSION

EMG-driven rehabilitation training using the soft robotic hand with flexion and extension could be effective for the functional recovery of upper limb in chronic stroke subjects with mild or no spasticity.

Robotic assistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review

PURPOSE

Stroke, spinal cord injury and other neuromuscular disorders lead to impairments in the human body. Upper limb impairments, especially hand impairments affect activities of daily living (ADL) and reduce the quality of life. The purpose of this review is to compare and evaluate the available robotic rehabilitation and assistive devices that can lead to motor recovery or maintain the current motor functional level.

METHODS

A systematic review was conducted of the literature published in the years from 2016-2021, to focus on the most recent rehabilitation and assistive devices available in the market or research environments.

RESULTS

A total of 230 studies published between 2016 and 2021 were identified from various databases. 107 were excluded with various reasons. Twenty-eight studies were taken into detailed review, to determine the efficacy of robotic devices in improving upper limb impairments or maintaining the current level from getting worse.

CONCLUSION

It was concluded that with a good strategy and treatment plan; appropriate and regular use of these robotic rehabilitation and assistive devices do lead to improvements in current conditions of most of the subjects and prolonged use may lead to motor recovery.Implications for RehabilitationStroke, accidents, spinal cord injuries and other neuromuscular disorders lead to impairments. Upper limb impairments have a tremendous adverse affect on ADL and reduces quality of life drastically.Advancement in technology has led to the designing of many robotic assistive and rehabilitation devices to assist in motor recovery or aid in ADL.This review analyses different available devices for rehabilitation and assistance and points out that use of these devices in time does help in motor recovery. Most of the studies reviewed showed improvements for the user.Future devices should be more portable and easier to use from home.

Upper Limb Rehabilitation Tools in Virtual Reality Based on Haptic and 3D Spatial Recognition Analysis: A Pilot Study

With aging, cerebrovascular diseases can occur more often. Stroke cases involve hemiplegia, which causes difficulties in performing activities of daily living. Existing rehabilitation treatments are based on the subjective evaluation of the therapist as the need for non-contact care arises; it is necessary to develop a system that can self-rehabilitate and offer objective analysis. Therefore, we developed rehabilitation tools that enable self-rehabilitation exercises in a virtual space based on haptics. Thirty adults without neurological damage were trained five times in a virtual environment, and the time, number of collisions, and coordinates were digitized and stored in real time. An analysis of variance (ANOVA) of the time and distance similarity changes revealed that as the number of rounds increased, no changes or increases occurred (p ≥ 0.05), and the collisions and paths were stable as the training progressed (p < 0.05). ANOVA showed a high correlation (0.90) with a decrease in the number of crashes and time required. It was meaningful to users when performing rehabilitation training more than four times and significantly impacted the analysis. This study analyzed the upper limb and cognitive rehabilitation of able-boded people in three-dimensional space in a virtual environment; the performance difficulty could be controlled through variations in rehabilitation models.

Review: How Can Intelligent Robots and Smart Mechatronic Modules Facilitate Remote Assessment, Assistance, and Rehabilitation for Isolated Adults With Neuro-Musculoskeletal Conditions?

Worldwide, at the time this article was written, there are over 127 million cases of patients with a confirmed link to COVID-19 and about 2.78 million deaths reported. With limited access to vaccine or strong antiviral treatment for the novel coronavirus, actions in terms of prevention and containment of the virus transmission rely mostly on social distancing among susceptible and high-risk populations. Aside from the direct challenges posed by the novel coronavirus pandemic, there are serious and growing secondary consequences caused by the physical distancing and isolation guidelines, among vulnerable populations. Moreover, the healthcare system's resources and capacity have been focused on addressing the COVID-19 pandemic, causing less urgent care, such as physical neurorehabilitation and assessment, to be paused, canceled, or delayed. Overall, this has left elderly adults, in particular those with neuromusculoskeletal (NMSK) conditions, without the required service support. However, in many cases, such as stroke, the available time window of recovery through rehabilitation is limited since neural plasticity decays quickly with time. Given that future waves of the outbreak are expected in the coming months worldwide, it is important to discuss the possibility of using available technologies to address this issue, as societies have a duty to protect the most vulnerable populations. In this perspective review article, we argue that intelligent robotics and wearable technologies can help with remote delivery of assessment, assistance, and rehabilitation services while physical distancing and isolation measures are in place to curtail the spread of the virus. By supporting patients and medical professionals during this pandemic, robots, and smart digital mechatronic systems can reduce the non-COVID-19 burden on healthcare systems. Digital health and cloud telehealth solutions that can complement remote delivery of assessment and physical rehabilitation services will be the subject of discussion in this article due to their potential in enabling more effective and safer NMSDK rehabilitation, assistance, and assessment service delivery. This article will hopefully lead to an interdisciplinary dialogue between the medical and engineering sectors, stake holders, and policy makers for a better delivery of care for those with NMSK conditions during a global health crisis including future pandemics.

DEVELOPMENT AND ANALYSIS OF A BILATERAL END-EFFECTER UPPER LIMB REHABILITATION ROBOT

Studies have shown that rehabilitation training with the unaffected side guiding affected side is more consistent with the natural movement pattern of human upper limb compared with unilateral rehabilitation training, which is conducive to improve rehabilitation effect of the affected limb motor function. In this paper, a bilateral end-effector upper limb rehabilitation robot (BEULRR) based on two modern commercial manipulators is developed first, then the kinematics, reachability, and dexterity analysis of BEULRR are performed, respectively. Finally, a bilateral symmetric training protocol with the unaffected side guiding the affected side is proposed and evaluated through healthy human subject experiment testing based on BEULRR. The simulation results show that the developed BEULRR could perform spatial rehabilitation training and its rehabilitation training workspace can fully cover the physiological workspace of human upper limb. The preliminary experiment results from the healthy human subject show that the BEULRR system could provide reliable bilateral symmetric training protocol. These simulation and experiment results demonstrated that the developed BEULRR system could be used in bilateral rehabilitation training application, and also show that the BEULRR system has the potential to be applied to clinical rehabilitation training in the further step. In the close future, the proposed BEULRR and bilateral symmetric training protocol are planned to be applied in elderly volunteers and patients with upper limb motor dysfunction for further evaluating.

Physical Human-Robot Collaboration: Robotic Systems, Learning Methods, Collaborative Strategies, Sensors, and Actuators

This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and collaborative strategies for physical human-robot collaboration (pHRC). This article starts with an overview of some robotic systems with cutting-edge technologies (sensors and actuators) suitable for pHRC operations and the intelligent assist devices employed in pHRC. Sensors being among the essential components to establish communication between a human and a robotic system are surveyed. The sensor supplies the signal needed to drive the robotic actuators. The survey reveals that the design of new generation collaborative robots and other intelligent robotic systems has paved the way for sophisticated learning techniques and control algorithms to be deployed in pHRC. Furthermore, it revealed the relevant components needed to be considered for effective pHRC to be accomplished. Finally, a discussion of the major advances is made, some research directions, and future challenges are presented.

Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges

Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human-machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on underlying neuromotor mechanisms in people with Duchenne. Novel wearable robotics devices are being tailored to specific patient populations, such as traumatic brain injury, stroke, and amputated individuals. In addition, developments in robot-assisted rehabilitation may enhance motor learning and generate movement repetitions by decoding the brain activity of patients during therapy. This is further facilitated by artificial intelligence algorithms coupled with faster electronics. The practical impact of integrating such technologies with neural rehabilitation treatment can be substantial. They can potentially empower nontechnically trained individuals-namely, family members and professional carers-to alter the programming of neural rehabilitation robotic setups, to actively get involved and intervene promptly at the point of care. This narrative review considers existing and emerging neural rehabilitation technologies through the perspective of replacing or restoring functions, enhancing, or improving natural neural output, as well as promoting or recruiting dormant neuroplasticity. Upon conclusion, we discuss the future directions for neural rehabilitation research, diagnosis, and treatment based on the discussed technologies and their major roadblocks. This future may eventually become possible through technological evolution and convergence of mutually beneficial technologies to create hybrid solutions.

A randomized controlled trial on the effects induced by robot-assisted and usual-care rehabilitation on upper limb muscle synergies in post-stroke subjects

Muscle synergies are hypothesized to reflect connections among motoneurons in the spinal cord activated by central commands and sensory feedback. Robotic rehabilitation of upper limb in post-stroke subjects has shown promising results in terms of improvement of arm function and motor control achieved by reassembling muscle synergies into a set more similar to that of healthy people. However, in stroke survivors the potentially neurophysiological changes induced by robot-mediated learning versus usual care have not yet been investigated. We quantified upper limb motor deficits and the changes induced by rehabilitation in 32 post-stroke subjects through the movement analysis of two virtual untrained tasks of object placing and pronation. The sample analyzed in this study is part of a larger bi-center study and included all subjects who underwent kinematic analysis and were randomized into robot and usual care groups. Post-stroke subjects who followed robotic rehabilitation showed larger improvements in axial-to-proximal muscle synergies with respect to those who underwent usual care. This was associated to a significant improvement of the proximal kinematics. Both treatments had negative effects in muscle synergies controlling the distal district. This study supports the definition of new rehabilitative treatments for improving the neurophysiological recovery after stroke.

Decoding of Ankle Joint Movements in Stroke Patients Using Surface Electromyography

Stroke is a cerebrovascular disease (CVD), which results in hemiplegia, paralysis, or death. Conventionally, a stroke patient requires prolonged sessions with physical therapists for the recovery of motor function. Various home-based rehabilitative devices are also available for upper limbs and require minimal or no assistance from a physiotherapist. However, there is no clinically proven device available for functional recovery of a lower limb. In this study, we explored the potential use of surface electromyography (sEMG) as a controlling mechanism for the development of a home-based lower limb rehabilitative device for stroke patients. In this experiment, three channels of sEMG were used to record data from 11 stroke patients while performing ankle joint movements. The movements were then decoded from the sEMG data and their correlation with the level of motor impairment was investigated. The impairment level was quantified using the Fugl-Meyer Assessment (FMA) scale. During the analysis, Hudgins time-domain features were extracted and classified using linear discriminant analysis (LDA) and artificial neural network (ANN). On average, 63.86% ± 4.3% and 67.1% ± 7.9% of the movements were accurately classified in an offline analysis by LDA and ANN, respectively. We found that in both classifiers, some motions outperformed others (p < 0.001 for LDA and p = 0.014 for ANN). The Spearman correlation (ρ) was calculated between the FMA scores and classification accuracies. The results indicate that there is a moderately positive correlation (ρ = 0.75 for LDA and ρ = 0.55 for ANN) between the two of them. The findings of this study suggest that a home-based EMG system can be developed to provide customized therapy for the improvement of functional lower limb motion in stroke patients.

A Modular Design for Distributed Measurement of Human-Robot Interaction Forces in Wearable Devices

Measurement of interaction forces distributed across the attachment interface in wearable devices is critical for understanding ergonomic physical human–robot interaction (pHRI). The main challenges in sensorization of pHRI interfaces are (i) capturing the fine nature of force transmission from compliant human tissue onto rigid surfaces in the wearable device and (ii) utilizing a low-cost and easily implementable design that can be adapted for a variety of human interfaces. This paper addresses both challenges and presents a modular sensing panel that uses force-sensing resistors (FSRs) combined with robust electrical and mechanical integration principles that result in a reliable solution for distributed load measurement. The design is demonstrated through an upper-arm cuff, which uses 24 sensing panels, in conjunction with the Harmony exoskeleton. Validation of the design with controlled loading of the sensorized cuff proves the viability of FSRs in an interface sensing solution. Preliminary experiments with a human subject highlight the value of distributed interface force measurement in recognizing the factors that influence ergonomic pHRI and elucidating their effects. The modular design and low cost of the sensing panel lend themselves to extension of this approach for studying ergonomics in a variety of wearable applications with the goal of achieving safe, comfortable, and effective human–robot interaction.

Wireless Motion Capture System for Upper Limb Rehabilitation

This work is devoted to the presentation of a Wireless Sensor System implementation for upper limb rehabilitation to function as a complementary system for a patient’s progress supervision during rehabilitation exercises. A cost effective motion capture sensor node composed by a 9 Degrees-of-Freedom (DoF) Inertial Measurement Unit (IMU) is mounted on the patient’s upper limb segments and sends wirelessly the corresponding measured signals to a base station. The sensor orientation and the upper limb individual segments movement in 3-Dimensional (3D) space are derived by processing the sensors’ raw data. For the latter purpose, a biomechanical model which resembles that of a kinematic model of a robotic arm based on the Denavit-Hartenberg (DH) configuration is used to approximate in real time the upper limb movements. The joint angles of the upper limb model are estimated from the extracted sensor node’s orientation angles. The experimental results of a human performing common rehabilitation exercises using the proposed motion capture sensor node are compared with the ones using an off-the-shelf sensor. This comparison results to very low error rates with the root mean square error (RMSE) being about 0.02 m.

Design and Experimental Characterization of a Cable-Driven Elbow Assisting Device

This paper presents the design and an experimental characterization of CADEL, a cable-driven elbow assisting device. The device design is presented to be portable and user-oriented solution and its kinematic model is formulated for functionality analysis. A first prototype and its experimental setup are discussed with the peculiarities of the novel solutions. Two operation modes are investigated with and without load in experimental testing. The performance characterization and feasibility are discussed referring to both the numerical and experimental results.

Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots

End-effector-based robotic systems provide easy-to-set-up motion support in rehabilitation of stroke and spinal-cord-injured patients. However, measurement information is obtained only about the motion of the limb segments to which the systems are attached and not about the adjacent limb segments. We demonstrate in one particular experimental setup that this limitation can be overcome by augmenting an end-effector-based robot with a wearable inertial sensor. Most existing inertial motion tracking approaches rely on a homogeneous magnetic field and thus fail in indoor environments and near ferromagnetic materials and electronic devices. In contrast, we propose a magnetometer-free sensor fusion method. It uses a quaternion-based algorithm to track the heading of a limb segment in real time by combining the gyroscope and accelerometer readings with position measurements of one point along that segment. We apply this method to an upper-limb rehabilitation robotics use case in which the orientation and position of the forearm and elbow are known, and the orientation and position of the upper arm and shoulder are estimated by the proposed method using an inertial sensor worn on the upper arm. Experimental data from five healthy subjects who performed 282 proper executions of a typical rehabilitation motion and 163 executions with compensation motion are evaluated. Using a camera-based system as a ground truth, we demonstrate that the shoulder position and the elbow angle are tracked with median errors around 4 cm and 4°, respectively; and that undesirable compensatory shoulder movements, which were defined as shoulder displacements greater ±10 cm for more than 20% of a motion cycle, are detected and classified 100% correctly across all 445 performed motions. The results indicate that wearable inertial sensors and end-effector-based robots can be combined to provide means for effective rehabilitation therapy with likewise detailed and accurate motion tracking for performance assessment, real-time biofeedback and feedback control of robotic and neuroprosthetic motion support.

Systematic review of guidelines to identify recommendations for upper limb robotic rehabilitation after stroke

INTRODUCTION

Upper limb motor impairment is one of the most frequent stroke consequences. Robot therapy may represent a valid option for upper limb stroke rehabilitation, but there are still gaps between research evidence and their use in clinical practice. The aim of this study was to determine the quality, scope, and consistency of guidelines clinical practice recommendations for upper limb robotic rehabilitation in stroke populations.

EVIDENCE ACQUISITION

We searched for guideline recommendations on stroke published between January 1st, 2010 and January 1st, 2020. Only the most recent guidelines for writing group were selected. Electronic databases (N.=4), guideline repertories and professional rehabilitation networks (N.=12) were searched. We systematically reviewed and assessed guidelines containing recommendation statements about upper limb robotic rehabilitation for adults with stroke (PROSPERO registration number: CRD42020173386).

EVIDENCE SYNTHESIS

Four independent reviewers used the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, and textual syntheses were used to appraise and compare recommendations. From 1324 papers that were screened, eight eligible guidelines were identified from six different regions/countries. Half of the included guidelines focused on stroke management, the other half on stroke rehabilitation. Rehabilitation assisted by robotic devices is generally recommended to improve upper limb motor function and strength. The exact characteristics of patients who could benefit from this treatment as well as the correct timing to use it are not known.

CONCLUSIONS

This systematic review has identified many opportunities to modernize and otherwise improve stroke patients' upper limb robotic therapy. Rehabilitation assisted by robot or electromechanical devices for stroke needs to be improved in clinical practice guidelines in particular in terms of applicability.

Robot enhanced stroke therapy optimizes rehabilitation (RESTORE): a pilot study

BACKGROUND

Robotic rehabilitation after stroke provides the potential to increase and carefully control dosage of therapy. Only a small number of studies, however, have examined robotic therapy in the first few weeks post-stroke. In this study we designed robotic upper extremity therapy tasks for the bilateral Kinarm Exoskeleton Lab and piloted them in individuals with subacute stroke. Pilot testing was focused mainly on the feasibility of implementing these new tasks, although we recorded a number of standardized outcome measures before and after training.

METHODS

Our team developed 9 robotic therapy tasks to incorporate feedback, intensity, challenge, and subject engagement as well as addressing both unimanual and bimanual arm activities. Subacute stroke participants were assigned to a robotic therapy (N = 9) or control group (N = 10) in a matched-group manner. The robotic therapy group completed 1-h of robotic therapy per day for 10 days in addition to standard therapy. The control group participated only in standard of care therapy. Clinical and robotic assessments were completed prior to and following the intervention. Clinical assessments included the Fugl-Meyer Assessment of Upper Extremity (FMA UE), Action Research Arm Test (ARAT) and Functional Independence Measure (FIM). Robotic assessments of upper limb sensorimotor function included a Visually Guided Reaching task and an Arm Position Matching task, among others. Paired sample t-tests were used to compare initial and final robotic therapy scores as well as pre- and post-clinical and robotic assessments.

RESULTS

Participants with subacute stroke (39.8 days post-stroke) completed the pilot study. Minimal adverse events occurred during the intervention and adding 1 h of robotic therapy was feasible. Clinical and robotic scores did not significantly differ between groups at baseline. Scores on the FMA UE, ARAT, FIM, and Visually Guided Reaching improved significantly in the robotic therapy group following completion of the robotic intervention. However, only FIM and Arm Position Match improved over the same time in the control group.

CONCLUSIONS

The Kinarm therapy tasks have the potential to improve outcomes in subacute stroke. Future studies are necessary to quantify the benefits of this robot-based therapy in a larger cohort.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04201613, Registered 17 December 2019-Retrospectively Registered, https://clinicaltrials.gov/ct2/show/NCT04201613 .

A Survey of Robots in Healthcare

In recent years, with the current advancements in Robotics and Artificial Intelligence (AI), robots have the potential to support the field of healthcare. Robotic systems are often introduced in the care of the elderly, children, and persons with disabilities, in hospitals, in rehabilitation and walking assistance, and other healthcare situations. In this survey paper, the recent advances in robotic technology applied in the healthcare domain are discussed. The paper provides detailed information about state-of-the-art research in care, hospital, assistive, rehabilitation, and walking assisting robots. The paper also discusses the open challenges healthcare robots face to be integrated into our society.