A survey on robotic devices for upper limb rehabilitation

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.

Synthesize Personalized Training for Robot-Assisted Upper Limb Rehabilitation With Diversity Enhancement

For upper limb rehabilitation, the robot-assisted technique in combination with serious games requires well-specified training plans. For the best quality of the rehabilitation process, customized game levels for each user are desired, while it is labor-intensive to design and adjust game levels for different individuals. We work on generating training content for a desktop end-effector rehabilitation robot and propose a method to automatically generate individualized training plans. By modeling the search of the training motions as finding optimal hand paths and trajectories, we introduce solving the design problem with a multi-objective optimization (MO) solver. We further improve the MO solver to enhance the diversity of the solutions. With the proposed approach, our system is capable of automatically generating various training plans considering the training intensity and dexterity of each joint in the upper limb. In addition, the enhanced diversity avoids repeated training plans, which helps motivate the user in the rehabilitation. We test our method with different requirements on the training plans and validate the solutions.

An analysis of stimulation methods used in rehabilitation equipment for children with cerebral palsy

Objective

This paper summarizes the research progress into stimulation methods used in rehabilitation equipment for pediatric cerebral palsy (CP) for the past 20 years from 2003 to 2023. We also provide ideas for innovative research and development of artificial intelligence-based rehabilitation equipment.

Methods

Through a certain search strategy, Keywords are searched in the China National Knowledge Network Database (CNKI), the Wanfang Database knowledge service platform, the Chongqing VIP information service, PubMed, Web of Science, Cochrane, ScienceDirect, Medline, Embase, and IEEE database. A total of 3,049 relevant articles were retrieved, and 49 articles were included that mentioned research and development of rehabilitation equipment. We excluded articles that were not specific to children with CP, were duplicated or irrelevant literature, were missing data, the full article was not available, the article did not describe the method of stimulation used with the rehabilitation equipment on children with CP, were not Chinese and English, and were the types of reviews and commentaries.

Results

Physical stimulation is the main stimulation method of rehabilitation equipment for children with CP. Force stimulation is the main mode of physical stimulation, and there are 17 articles that have verified the clinical efficacy of force stimulation-based equipment.

Conclusion

Research on the stimulation mode of pediatric cerebral palsy rehabilitation equipment is likely to focus on simulating the force of the Chinese medicine called "tuina manipulation." When this method is combined with artificial intelligence and personalized direction we believe this will lay the foundation for future development of a novel therapy for children with CP.

Combined robot-assisted therapy virtual reality for upper limb rehabilitation in stroke survivors: a systematic review of randomized controlled trials

BACKGROUND

Upper limb impairments are among the most common consequences following a stroke. Recently, robot-assisted therapy (RT) and virtual reality (VR) have been used to improve upper limb function in stroke survivors.

OBJECTIVES

This review aims to investigate the effects of combined RT and VR on upper limb function in stroke survivors and to provide recommendations for researchers and clinicians in the medical field.

METHODS

We searched PubMed, SCOPUS, REHABDATA, PEDro, EMBASE, and Web of Science from inception to March 28, 2024. Randomized controlled trials (RCTs) involving stroke survivors that compared combined RT and VR interventions with either passive (i.e., sham, rest) or active (i.e., traditional therapy, VR, RT) interventions and assessed outcomes related to upper limb function (e.g., strength, muscle tone, or overall function) were included. The Cochrane Collaboration tool was used to evaluate the methodological quality of the included studies.

RESULTS

Six studies were included in this review. In total, 201 patients with stroke (mean age 57.84 years) were involved in this review. Four studies were considered 'high quality', while two were considered as 'moderate quality' on the Cochrane Collaboration tool. The findings showed inconsistent results for the effects of combined RT and VR interventions on upper limb function poststroke.

CONCLUSION

In conclusion, there are potential effects of combined RT and VR interventions on improving upper limb function, but further research is needed to confirm these findings, understand the underlying mechanisms, and assess the consistency and generalizability of the results.

Understanding the Sociocultural Challenges and Opportunities for Affordable Wearables to Support Poststroke Upper-Limb Rehabilitation: Qualitative Study

Background

People who survive a stroke in many cases require upper-limb rehabilitation (ULR), which plays a vital role in stroke recovery practices. However, rehabilitation services in the Global South are often not affordable or easily accessible. For example, in Bangladesh, the access to and use of rehabilitation services is limited and influenced by cultural factors and patients' everyday lives. In addition, while wearable devices have been used to enhance ULR exercises to support self-directed home-based rehabilitation, this has primarily been applied in developed regions and is not common in many Global South countries due to potential costs and limited access to technology.

Objective

Our goal was to better understand physiotherapists', patients', and caregivers' experiences of rehabilitation in Bangladesh, existing rehabilitation practices, and how they differ from the rehabilitation approach in the United Kingdom. Understanding these differences and experiences would help to identify opportunities and requirements for developing affordable wearable devices that could support ULR in home settings.

Methods

We conducted an exploratory study with 14 participants representing key stakeholder groups. We interviewed physiotherapists and patients in Bangladesh to understand their approaches, rehabilitation experiences and challenges, and technology use in this context. We also interviewed UK physiotherapists to explore the similarities and differences between the 2 countries and identify specific contextual and design requirements for low-cost wearables for ULR. Overall, we remotely interviewed 8 physiotherapists (4 in the United Kingdom, 4 in Bangladesh), 3 ULR patients in Bangladesh, and 3 caregivers in Bangladesh. Participants were recruited through formal communications and personal contacts. Each interview was conducted via videoconference, except for 2 interviews, and audio was recorded with consent. A total of 10 hours of discussions were transcribed. The results were analyzed using thematic analysis.

Results

We identified several sociocultural factors that affect ULR and should be taken into account when developing technologies for the home: the important role of family, who may influence the treatment based on social and cultural perceptions; the impact of gender norms and their influence on attitudes toward rehabilitation and physiotherapists; and differences in approach to rehabilitation between the United Kingdom and Bangladesh, with Bangladeshi physiotherapists focusing on individual movements that are necessary to build strength in the affected parts and their British counterparts favoring a more holistic approach. We propose practical considerations and design recommendations for developing ULR devices for low-resource settings.

Conclusions

Our work shows that while it is possible to build a low-cost wearable device, the difficulty lies in addressing sociotechnical challenges. When developing new health technologies, it is imperative to not only understand how well they could fit into patients', caregivers', and physiotherapists' everyday lives, but also how they may influence any potential tensions concerning culture, religion, and the characteristics of the local health care system.

The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions

In recent years, there has been a notable increase in the clinical adoption of instrumental upper limb kinematic assessment. This trend aligns with the rising prevalence of cerebrovascular impairments, one of the most prevalent neurological disorders. Indeed, there is a growing need for more objective outcomes to facilitate tailored rehabilitation interventions following stroke. Emerging technologies, like head-mounted virtual reality (HMD-VR) platforms, have responded to this demand by integrating diverse tracking methodologies. Specifically, HMD-VR technology enables the comprehensive tracking of body posture, encompassing hand position and gesture, facilitated either through specific tracker placements or via integrated cameras coupled with sophisticated computer graphics algorithms embedded within the helmet. This review aims to present the state-of-the-art applications of HMD-VR platforms for kinematic analysis of the upper limb in post-stroke patients, comparing them with conventional tracking systems. Additionally, we address the potential benefits and challenges associated with these platforms. These systems might represent a promising avenue for safe, cost-effective, and portable objective motor assessment within the field of neurorehabilitation, although other systems, including robots, should be taken into consideration.

Resist-as-Needed ADL Training With SPINDLE for Patients With Tremor

Individuals with neurological disorders often exhibit altered manual dexterity and muscle weakness in their upper limbs. These motor impairments with tremor lead to severe difficulties in performing Activities of Daily Living (ADL). There is a critical need for ADL-focused robotic training that improves individual's strength when engaging with dexterous ADL tasks. This research introduces a new approach to training ADLs by employing a novel robotic rehabilitation system, Spherical Parallel INstrument for Daily Living Emulation (SPINDLE), which incorporates Virtual Reality (VR) to simulate ADL tasks. The study results present the feasibility of training individuals with movements similar to ADLs while interacting with the SPINDLE. A new game-based robotic training paradigm is suggested to perform ADL tasks at various intensity levels of resistance as needed. The proposed system can facilitate the training of various ADLs requiring 3-dimensional rotational movements by providing optimal resistance and visual feedback. We envision this system can be utilized as a table-top home device by restoring the impaired motor function of individuals with tremor and muscle weakness, guiding to improved ADL performance and quality of life.

A Sensor-Based Upper Limb Treatment in Hemiplegic Patients: Results from a Randomized Pilot Study

In post-stroke patients, the disabling motor deficit mainly affects the upper limb. The focus of rehabilitation is improving upper limb function and reducing long-term disability. This study aims to evaluate the feasibility of using the Gloreha Aria (R-Lead), a sensor-based upper limb in-hospital rehabilitation, compared with conventional physiotherapist-led training in subacute hemiplegic patients. Twenty-one patients were recruited and randomised 1:1 to a sensor-based group (treatment group TG) or a conventional group (control group, CG). All patients performed 30 sessions of 30 min each of dedicated upper limb rehabilitation. The Fugl-Meyer Assessment for Upper Extremity (FMA-UE) was the primary evaluation., both as a motor score and as individual items. Secondary evaluations were Functional Independence Measure; global disability assessed with the Modified Barthel Index; Motor Evaluation Scale for UE in stroke; power grip; and arm, shoulder, and hand disability. All the enrolled patients, 10 in the TG and 11 in the CG, completed all hand rehabilitation sessions during their hospital stay without experiencing any adverse events. FMA-UE scores in upper limb motor function improved in both groups [delta change CG (11.8 ± 9.2) vs. TG (12.7 ± 8.6)]. The score at T1 for FMA joint pain (21.8 vs. 24 best score) suggests the use of the Gloreha Aria (R-Lead) as feasible in improving arm function abilities in post-stroke patients.

Does Exerting Grasps Involve a Finite Set of Muscle Patterns? A Study of Intra- and Intersubject Variability of Forearm sEMG Signals in Seven Grasp Types

Surface Electromyography (sEMG) signals are widely used as input to control robotic devices, prosthetic limbs, exoskeletons, among other devices, and provide information about someone's intention to perform a particular movement. However, the redundant action of 32 muscles in the forearm and hand means that the neuromotor system can select different combinations of muscular activities to perform the same grasp, and these combinations could differ among subjects, and even among the trials done by the same subject. In this work, 22 healthy subjects performed seven representative grasp types (the most commonly used). sEMG signals were recorded from seven representative forearm spots identified in a previous work. Intra- and intersubject variability are presented by using four sEMG characteristics: muscle activity, zero crossing, enhanced wavelength and enhanced mean absolute value. The results confirmed the presence of both intra- and intersubject variability, which evidences the existence of distinct, yet limited, muscle patterns while executing the same grasp. This work underscores the importance of utilizing diverse combinations of sEMG features or characteristics of various natures, such as time-domain or frequency-domain, and it is the first work to observe the effect of considering different muscular patterns during grasps execution. This approach is applicable for fine-tuning the control settings of current sEMG devices.

Exploring new horizons: Emerging therapeutic strategies for pediatric stroke

Pediatric stroke presents unique challenges, and optimizing treatment strategies is essential for improving outcomes in this vulnerable population. This review aims to provide an overview of new, innovative, and potential treatments for pediatric stroke, with a primary objective to stimulate further research in this field. Our review highlights several promising approaches in the realm of pediatric stroke management, including but not limited to stem cell therapy and robotic rehabilitation. These innovative interventions offer new avenues for enhancing functional recovery, reducing long-term disability, and tailoring treatments to individual patient needs. The findings of this review underscore the importance of ongoing research and development of innovative treatments in pediatric stroke. These advancements hold significant clinical relevance, offering the potential to improve the lives of children affected by stroke by enhancing the precision, efficacy, and accessibility of therapeutic interventions. Embracing these innovations is essential in our pursuit of better outcomes and a brighter future for pediatric stroke care.

Design Optimization of a Soft Robotic Rehabilitation Glove Based on Finger Workspace Analysis

The finger workspace is crucial for performing various grasping tasks. Thus, various soft rehabilitation gloves have been developed to assist individuals with paralyzed hands in activities of daily living (ADLs) or rehabilitation training. However, most soft robotic glove designs are insufficient to assist with various hand postures because most of them use an underactuated mechanism for design simplicity. Therefore, this paper presents a methodology for optimizing the design of a high-degree-of-freedom soft robotic glove while not increasing the design complexity. We defined the required functional workspace of the index finger based on ten frequently used grasping postures in ADLs. The design optimization was achieved by simulating the proposed finger-robot model to obtain a comparable workspace to the functional workspace. In particular, the moment arm length for extension was optimized to facilitate the grasping of large objects (precision disk and power sphere), whereas a torque-amplifying routing design was implemented to aid the grasping of small objects (lateral pinch and thumb-two-finger pinch). The effectiveness of the optimized design was validated through testing with a stroke survivor and comparing the assistive workspace. The observed workspace demonstrated that the optimized glove design could assist with nine out of the ten targeted grasping posture functional workspaces. Furthermore, the assessment of the grasping speed and force highlighted the glove's usability for various rehabilitation activities. We also present and discuss a generalized methodology to optimize the design parameters of a soft robotic glove that uses an underactuated mechanism to assist the targeted workspace. Overall, the proposed design optimization methodology serves as a tool for developing advanced hand rehabilitation robots, as it offers insight regarding the importance of routing optimization in terms of the workspace.

An Optimized Stimulation Control System for Upper Limb Exoskeleton Robot-Assisted Rehabilitation Using a Fuzzy Logic-Based Pain Detection Approach

The utilization of robotic systems in upper limb rehabilitation has shown promising results in aiding individuals with motor impairments. This research introduces an innovative approach to enhance the efficiency and adaptability of upper limb exoskeleton robot-assisted rehabilitation through the development of an optimized stimulation control system (OSCS). The proposed OSCS integrates a fuzzy logic-based pain detection approach designed to accurately assess and respond to the patient's pain threshold during rehabilitation sessions. By employing fuzzy logic algorithms, the system dynamically adjusts the stimulation levels and control parameters of the exoskeleton, ensuring personalized and optimized rehabilitation protocols. This research conducts comprehensive evaluations, including simulation studies and clinical trials, to validate the OSCS's efficacy in improving rehabilitation outcomes while prioritizing patient comfort and safety. The findings demonstrate the potential of the OSCS to revolutionize upper limb exoskeleton-assisted rehabilitation by offering a customizable and adaptive framework tailored to individual patient needs, thereby advancing the field of robotic-assisted rehabilitation.

Therapeutic robots for post-stroke rehabilitation

Stroke is a prevalent, severe, and disabling health-care issue on a global scale, inevitably leading to motor and cognitive deficits. It has become one of the most significant challenges in China, resulting in substantial social and economic burdens. In addition to the medication and surgical interventions during the acute phase, rehabilitation treatment plays a crucial role in stroke care. Robotic technology takes distinct advantages over traditional physical therapy, occupational therapy, and speech therapy, and is increasingly gaining popularity in post-stroke rehabilitation. The use of rehabilitation robots not only alleviates the workload of healthcare professionals but also enhances the prognosis for specific stroke patients. This review presents a concise overview of the application of therapeutic robots in post-stroke rehabilitation, with particular emphasis on the recovery of motor and cognitive function.

SpasticSim: a synthetic data generation method for upper limb spasticity modelling in neurorehabilitation

In neurorehabilitation, assessment of functional problems is essential to define optimal rehabilitation treatments. Usually, this assessment process requires distinguishing between impaired and non-impaired behavior of limbs. One of the common muscle motor disorders affecting limbs is spasticity, which is complicated to quantify objectively due to the complex nature of motor control. Thus, the lack of heterogeneous samples of patients constituting an acceptable amount of data is an obstacle which is relevant to understanding the behavior of spasticity and, consequently, quantifying it. In this article, we use the 3D creation suite Blender combined with the MBLab add-on to generate synthetic samples of human body models, aiming to be as sufficiently representative as possible to real human samples. Exporting these samples to OpenSim and performing four specific upper limb movements, we analyze the muscle behavior by simulating the six degrees of spasticity contemplated by the Modified Ashworth Scale (MAS). The complete dataset of patients and movements is open-source and available for future research. This approach advocates the potential to generate synthetic data for testing and validating musculoskeletal models.

Personalized robots for long-term telerehabilitation after stroke: a perspective on technological readiness and clinical translation

Stroke rehabilitation, which demands consistent, intensive, and adaptable intervention in the long term, faced significant challenges due to the COVID-19 pandemic. During this time, telerehabilitation emerged as a noteworthy complement to traditional rehabilitation services, offering the convenience of at-home care delivery and overcoming geographical and resource limitations. Self-help rehabilitation robots deliver repetitive and intensive physical assistance, thereby alleviating the labor burden. However, robots have rarely demonstrated long-term readiness for poststroke telerehabilitation services. The transition from research trials to general clinical services presents several challenges that may undermine the rehabilitative gains observed in these studies. This perspective discusses the technological readiness of personal use robots in the context of telerehabilitation and identifies the potential challenges for their clinical translation. The goal is to leverage technology to seamlessly integrate it into standard clinical workflows, ultimately enhancing the outcomes of stroke rehabilitation.

Generating a novel synthetic dataset for rehabilitation exercises using pose-guided conditioned diffusion models: A quantitative and qualitative evaluation

Machine learning has emerged as a promising approach to enhance rehabilitation therapy monitoring and evaluation, providing personalized insights. However, the scarcity of data remains a significant challenge in developing robust machine learning models for rehabilitation. This paper introduces a novel synthetic dataset for rehabilitation exercises, leveraging pose-guided person image generation using conditioned diffusion models. By processing a pre-labeled dataset of class movements for 6 rehabilitation exercises, the described method generates realistic human movement images of elderly subjects engaging in home-based exercises. A total of 22,352 images were generated to accurately capture the spatial consistency of human joint relationships for predefined exercise movements. This novel dataset significantly amplified variability in the physical and demographic attributes of the main subject and the background environment. Quantitative metrics used for image assessment revealed highly favorable results. The generated images successfully maintained intra-class and inter-class consistency in motion data, producing outstanding outcomes with distance correlation values exceeding the 0.90. This innovative approach empowers researchers to enhance the value of existing limited datasets by generating high-fidelity synthetic images that precisely augment the anthropometric and biomechanical attributes of individuals engaged in rehabilitation exercises.

A deep learning system to monitor and assess rehabilitation exercises in home-based remote and unsupervised conditions

In the domain of physical rehabilitation, the progress in machine learning and the availability of cost-effective motion capture technologies have paved the way for innovative systems capable of capturing human movements, automatically analyzing recorded data, and evaluating movement quality. This study introduces a novel, economically viable system designed for monitoring and assessing rehabilitation exercises. The system enables real-time evaluation of exercises, providing precise insights into deviations from correct execution. The evaluation comprises two significant components: range of motion (ROM) classification and compensatory pattern recognition. To develop and validate the effectiveness of the system, a unique dataset of 6 resistance training exercises was acquired. The proposed system demonstrated impressive capabilities in motion monitoring and evaluation. Notably, we achieved promising results, with mean accuracies of 89% for evaluating ROM-class and 98% for classifying compensatory patterns. By complementing conventional rehabilitation assessments conducted by skilled clinicians, this cutting-edge system has the potential to significantly improve rehabilitation practices. Additionally, its integration in home-based rehabilitation programs can greatly enhance patient outcomes and increase access to high-quality care.

UCO Physical Rehabilitation: New Dataset and Study of Human Pose Estimation Methods on Physical Rehabilitation Exercises

Physical rehabilitation plays a crucial role in restoring motor function following injuries or surgeries. However, the challenge of overcrowded waiting lists often hampers doctors' ability to monitor patients' recovery progress in person. Deep Learning methods offer a solution by enabling doctors to optimize their time with each patient and distinguish between those requiring specific attention and those making positive progress. Doctors use the flexion angle of limbs as a cue to assess a patient's mobility level during rehabilitation. From a Computer Vision perspective, this task can be framed as automatically estimating the pose of the target body limbs in an image. The objectives of this study can be summarized as follows: (i) evaluating and comparing multiple pose estimation methods; (ii) analyzing how the subject's position and camera viewpoint impact the estimation; and (iii) determining whether 3D estimation methods are necessary or if 2D estimation suffices for this purpose. To conduct this technical study, and due to the limited availability of public datasets related to physical rehabilitation exercises, we introduced a new dataset featuring 27 individuals performing eight diverse physical rehabilitation exercises focusing on various limbs and body positions. Each exercise was recorded using five RGB cameras capturing different viewpoints of the person. An infrared tracking system named OptiTrack was utilized to establish the ground truth positions of the joints in the limbs under study. The results, supported by statistical tests, show that not all state-of-the-art pose estimators perform equally in the presented situations (e.g., patient lying on the stretcher vs. standing). Statistical differences exist between camera viewpoints, with the frontal view being the most convenient. Additionally, the study concludes that 2D pose estimators are adequate for estimating joint angles given the selected camera viewpoints.

The role of collaborative robotics in assistive and rehabilitation applications

Collaborative robotics principles and advancements may transform the field of assistive and rehabilitation robotics.

EMG-Based Control Strategies of a Supernumerary Robotic Hand for the Rehabilitation of Sub-Acute Stroke Patients: Proof of Concept

One of the most frequent and severe aftermaths of a stroke is the loss of upper limb functionality. Therapy started in the sub-acute phase proved more effective, mainly when the patient participates actively. Recently, a novel set of rehabilitation and support robotic devices, known as supernumerary robotic limbs, have been introduced. This work investigates how a surface electromyography (sEMG) based control strategy would improve their usability in rehabilitation, limited so far by input interfaces requiring to subjects some level of residual mobility. After briefly introducing the phenomena hindering post-stroke sEMG and its use to control robotic hands, we describe a framework to acquire and interpret muscle signals of the forearm extensors. We applied it to drive a supernumerary robotic limb, the SoftHand-X, to provide Task-Specific Training (TST) in patients with sub-acute stroke. We propose and describe two algorithms to control the opening and closing of the robotic hand, with different levels of user agency and therapist control. We experimentally tested the feasibility of the proposed approach on four patients, followed by a therapist, to check their ability to operate the hand. The promising preliminary results indicate sEMG-based control as a viable solution to extend TST to sub-acute post-stroke patients.

Customized Series Elastic Actuator for a Safe and Compliant Human-Robot Interaction: Design and Characterization

When it comes to robotic-mediated rehabilitation it is mandatory to design a system that guarantees a safe and compliant human-machine interaction. Dealing with rehabilitative upper limb exoskeletons, Series Elastic Actuators offer a potential solution for this purpose. This work proposes four different solutions for SEAs' spring design. After an analysis on the mechanical requirements, four different solutions are explored and presented. The performances of the proposed highly integrated SEAs are compared. An initial static characterization provided insights on the linearity and repeatability of each spring torque-angle performances. The dynamics of the springs and their frequency responses are then analysed to show how it is possible to exploit our system for human-robot interaction applications.

Applying an Artificial Neuromolecular System to the Application of Robotic Arm Motion Control in Assisting the Rehabilitation of Stroke Patients-An Artificial World Approach

Stroke patients cannot use their hands as freely as usual. However, recovery after a stroke is a long road for many patients. If artificial intelligence can assist human arm movement, it is believed that the possibility of stroke patients returning to normal hand movement can be significantly increased. In this study, the artificial neuromolecular system (ANM system) developed by our laboratory is used as the core motion control system to learn to control the mechanical arm, produce similar human rehabilitation actions, and assist patients in transiting between different activities. The strength of the ANM system lies in its ability to capture and process spatiotemporal information by exploiting the dynamic information processing inside neurons. Five experiments are conducted in this research: continuous learning, dimensionality reduction, moving problem domains, transfer learning, and fault tolerance. The results show that the ANM system can find out the arm movement trajectory when people perform different rehabilitation actions through the ability of continuous learning and reduce the activation of multiple muscle groups in stroke patients through the learning method of reducing dimensions. Finally, using the ANM system can reduce the learning time and performance required to switch between different actions through transfer learning.

The Translation of Mobile-Exoneuromusculoskeleton-Assisted Wrist-Hand Poststroke Telerehabilitation from Laboratory to Clinical Service

Rehabilitation robots are helpful in poststroke telerehabilitation; however, their feasibility and rehabilitation effectiveness in clinical settings have not been sufficiently investigated. A non-randomized controlled trial was conducted to investigate the feasibility of translating a telerehabilitation program assisted by a mobile wrist/hand exoneuromusculoskeleton (WH-ENMS) into routine clinical services and to compare the rehabilitative effects achieved in the hospital-service-based group (n = 12, clinic group) with the laboratory-research-based group (n = 12, lab group). Both groups showed significant improvements (p ≤ 0.05) in clinical assessments of behavioral motor functions and in muscular coordination and kinematic evaluations after the training and at the 3-month follow-up, with the lab group demonstrating better motor gains than the clinic group (p ≤ 0.05). The results indicated that the WH-ENMS-assisted tele-program was feasible and effective for upper limb rehabilitation when integrated into routine practice, and the quality of patient-operator interactions physically and remotely affected the rehabilitative outcomes.

Robotic arm training in neurorehabilitation enhanced by augmented reality - a usability and feasibility study

BACKGROUND

Robotic therapy and serious gaming support motor learning in neurorehabilitation. Traditional monitor-based gaming outputs cannot adequately represent the third dimension, whereas virtual reality headsets lack the connection to the real world. The use of Augmented Reality (AR) techniques could potentially overcome these issues. The objective of this study was thus to evaluate the usability, feasibility and functionality of a novel arm rehabilitation device for neurorehabilitation (RobExReha system) based on a robotic arm (LBR iiwa, KUKA AG) and serious gaming using the AR headset HoloLens (Microsoft Inc.).

METHODS

The RobExReha system was tested with eleven adult inpatients (mean age: 64.4 ± 11.2 years; diagnoses: 8 stroke, 2 spinal cord injury, 1 Guillain-Barré-Syndrome) who had paretic impairments in their upper limb. Five therapists administered and evaluated the system. Data was compared with a Reference Group (eleven inpatients; mean age: 64.3 ± 9.1 years; diagnoses: 10 stroke, 1 spinal cord injury) who trained with commercially available robotic therapy devices (ArmeoPower or ArmeoSpring, Hocoma AG). Patients used standardized questionnaires for evaluating usability and comfort (Quebec User Evaluation of Satisfaction with assistive technology [QUEST]), workload (Raw Task Load Index [RTLX]) and a questionnaire for rating visual perception of the gaming scenario. Therapists used the QUEST, the System Usability Scale and the short version of the User Experience Questionnaire.

RESULTS

Therapy with the RobExReha system was safe and feasible for patients and therapists, with no serious adverse events being reported. Patients and therapists were generally satisfied with usability. The patients' usability ratings were significantly higher in the Reference Group for two items of the QUEST: reliability and ease of use. Workload (RTLX) ratings did not differ significantly between the groups. Nearly all patients using the RobExReha system perceived the gaming scenario in AR as functioning adequately despite eight patients having impairments in stereoscopic vision. The therapists valued the system's approach as interesting and inventive.

CONCLUSIONS

We demonstrated the clinical feasibility of combining a novel robotic upper limb robot with an AR-serious game in a neurorehabilitation setting. To ensure high usability in future applications, a reliable and easy-to-use system that can be used for task-oriented training should be implemented.

TRIAL REGISTRATION

Ethical approval was obtained and the trial was registered at the German Clinical Trials Register (DRKS00022136).

The effectiveness of robotic-assisted upper limb rehabilitation to improve upper limb function in patients with cervical spinal cord injuries: a systematic literature review

Background

Spinal Cord Injury (SCI) damages corticospinal tracts and descending motor pathways responsible for transmitting signals from the brain to the spinal cord, leading to temporary or permanent changes in sensation, motor function, strength, and body function below the site of injury. Cervical SCI (cSCI), which leads to tetraplegia, causes severe functional upper limb (UL) impairments that increase falls risk, limits independence, and leads to difficulties with activities of daily living (ADLs). Robotic therapy (RT) has been developed in recent decades as a new treatment approach for people with cervical spinal cord injuries (cSCI). The present review aimed to explore current available evidence and studies regarding the effectiveness of RT for individuals with cSCI in improving UL function, identify current research gaps and future research directions.

Method

This review was conducted by searching PubMed, CINAHL, Medline, Embase, and APA PsycInfo for relevant studies published from January 2010 to January 2022. Selected studies were analyzed with a focus on the patients' self-perception of limited UL function and level of independence in activities of daily living. In addition, the JBI Critical Appraisal checklist was used to assess study quality.

Results

A total of 7 articles involving 87 patients (74 males and 13 females) were included in the analysis, with four studies utilizing exoskeleton and three studies utilizing end-effector robotic devices, respectively. The quality of these studies varied between JBI Critical Appraisal scores of 4 to 8. Several studies lacked blinding and a control group which affected internal validity. Nevertheless, four out of seven studies demonstrated statistically significant improvements in outcome measurements on UL function and strength after RT.

Conclusion

This review provided mixed evidence regarding the effectiveness of RT as a promising intervention approach to improve upper limb function in participants with cSCI. Although RT was shown to be safe, feasible, and reduces active therapist time, further research on the long-term effects of UL RT is still needed. Nevertheless, this review serves as a useful reference for researchers to further develop exoskeletons with practical and plausible applications toward geriatric orthopaedics.

Comparing the Lower-Limb Muscle Activation Patterns of Simulated Walking Using an End-Effector-Type Robot with Real Level and Stair Walking in Children with Spastic Bilateral Cerebral Palsy

Cerebral palsy is a neurologic disorder caused by lesions on an immature brain, often resulting in spasticity and gait abnormality. This study aimed to compare the muscle activation patterns of real level and stair walking with those of simulated walking using an end-effector-type robot in children with spastic cerebral palsy. The electromyographic activities of the vastus lateralis, biceps femoris, tibialis anterior and medial gastrocnemius of nine children with spastic bilateral cerebral palsy were measured during gait using a wireless surface EMG device. Morning walk was used for the simulated gait. Differences in the muscle activation patterns between the real and simulated gait conditions were analyzed. In the loading response, all four muscles showed reduced activity during two simulated conditions. In mid-stance, mGCM showed reduced activity during simulated conditions, whereas BFem showed greater activity during simulated level walking. In the swing phase, BFem and TAnt activity was reduced during the simulated conditions. The onset-offset of the VLat, BFem and TAnt activity was significantly delayed during simulated versus real level walking. No differences in activity onset-offset were observed between the simulated level and stair conditions. In conclusion, the robot-simulated gait showed differences in its muscle activation patterns compared with the real gait conditions, which must be considered for gait training using an end-effector-type robot.

Home-based upper limb stroke rehabilitation mechatronics: challenges and opportunities

Interest in home-based stroke rehabilitation mechatronics, which includes both robots and sensor mechanisms, has increased over the past 12 years. The COVID-19 pandemic has exacerbated the existing lack of access to rehabilitation for stroke survivors post-discharge. Home-based stroke rehabilitation devices could improve access to rehabilitation for stroke survivors, but the home environment presents unique challenges compared to clinics. The present study undertakes a scoping review of designs for at-home upper limb stroke rehabilitation mechatronic devices to identify important design principles and areas for improvement. Online databases were used to identify papers published 2010-2021 describing novel rehabilitation device designs, from which 59 publications were selected describing 38 unique designs. The devices were categorized and listed according to their target anatomy, possible therapy tasks, structure, and features. Twenty-two devices targeted proximal (shoulder and elbow) anatomy, 13 targeted distal (wrist and hand) anatomy, and three targeted the whole arm and hand. Devices with a greater number of actuators in the design were more expensive, with a small number of devices using a mix of actuated and unactuated degrees of freedom to target more complex anatomy while reducing the cost. Twenty-six of the device designs did not specify their target users' function or impairment, nor did they specify a target therapy activity, task, or exercise. Twenty-three of the devices were capable of reaching tasks, 6 of which included grasping capabilities. Compliant structures were the most common approach of including safety features in the design. Only three devices were designed to detect compensation, or undesirable posture, during therapy activities. Six of the 38 device designs mention consulting stakeholders during the design process, only two of which consulted patients specifically. Without stakeholder involvement, these designs risk being disconnected from user needs and rehabilitation best practices. Devices that combine actuated and unactuated degrees of freedom allow a greater variety and complexity of tasks while not significantly increasing their cost. Future home-based upper limb stroke rehabilitation mechatronic designs should provide information on patient posture during task execution, design with specific patient capabilities and needs in mind, and clearly link the features of the design to users' needs.

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.

Motor Control Changes after Utilizing Upper Extremity Myoelectric Powered Wearable Orthotics in Persons with Acute SCI

Following spinal cord injury (SCI), upper extremity (UE) weakness may impede one's ability to carry out activities of daily living (ADLs). Such a limitation drastically lowers a person's level of independence. Additionally, therapy and the field of assistive technology continue to place a strong premium on the restoration of UE motor function in patients with SCI. The main objective of this study was to assess the benefits of an UE myoelectric-powered wearable orthosis (MPWO) produced by MyoMo, Inc. (Boston, MA) on improving UE motor function in order to enhance ADLs and quality of life in individuals with subacute SCI. A 43-year-old man with subacute incomplete SCI (iSCI), American Spinal Injury Association (ASIA) Impairment Scale (AIS) C grade received 18 sessions (over a period of six weeks) of UE mobility therapy utilizing the MPWO. The MPWO was used to enhance active range of motion (AROM) of the hand and elbow, and associated muscle activations. After training with the MPWO, hand and elbow AROM and muscle activations were enhanced. These preliminary findings imply that UE-MPWO device-assisted rehabilitation may increase participants' UE activities, leading to improved function.Clinical Relevance- These preliminary findings from a person with iSCI in the subacute phase indicate that training with UE-MPWO assistive devices may enhance UE use during ADLs for people with muscle weakness but still having some residual voluntary muscle activation ability.

Current insights into the management of spinal cord injury

Background

Traumatic spinal cord injury (SCI) is a serious disorder that results in severe impairment of neurological function as well as disability, ultimately reducing a patient's quality of life. The pathophysiology of SCI involves a primary and secondary phase, which causes neurological injury.

Methods

Narrative review on current clinical management of spinal cord injury and emerging therapies.

Results

This review explores the management of SCI through early decompressive surgery, optimizing mean arterial pressure, steroid therapy and focused rehabilitation. These management strategies reduce secondary injury mechanisms to prevent the propagation of further neurological damage. The literature regarding emerging research is also explored in cell-based, gene, pharmacological and neuromodulation therapies, which aim to repair the spinal cord following the primary injury mechanism.

Conclusions

Outcomes for patients with SCI can be enhanced and improved if primary and secondary phases of SCI can be addressed.

Development of a Control Strategy in an Isokinetic Device for Physical Rehabilitation

Robotic-assisted rehabilitation is currently being applied to improve the effectiveness of human gait rehabilitation and recover the mobility and strength after a stroke or spinal cord injury; a robotic assistant can allow the active participation of the patient and the supervision of the collected data and decrease the labor required from therapists during the patient's training exercises. The goal of gait rehabilitation with robotic-based assistance is to restore motor function by using diverse control strategies, taking account of the physical interaction with the lower limbs of the patient. Over the last few years, researchers have extracted useful information from the patient's biological signals that can effectively reflect movement intention and muscle activation. One way to evaluate progress in rehabilitation is through isokinetic prototype tests that describe the dynamic characteristics of an isokinetic leg extension device for rehabilitation and control action. These tests use an isokinetic system to assess muscle strength and performance in a patient during isometric or isokinetic contraction. An experimental prototype shown in the following work allows the device's performance to be evaluated in a controlled environment before the patient's use. New features provide a control system that can be teleoperated for distributed structures, enabling the remote operation and management of the device. In order to achieve physical recovery from musculoskeletal injuries in the lower limbs and the reintegration of the affected subject into society as an independent and autonomous individual in their daily activities, a control model that introduces a medical isokinetic rehabilitation protocol is presented, in which the element that carries out such protocol consists of a magnetic particle brake whose control action is strongly influenced by the dynamics of the system when in contact with the end user-specifically, the patient's legs in the stretch from the knee to the ankle. The results of these tests are valuable for health professionals seeking to measure their patient's progress during the rehabilitation process and determine when it is safe and appropriate to advance in their treatment.

Design and Development of a Spherical 5-Bar Thumb Exoskeleton Mechanism for Poststroke Rehabilitation

This paper presents the kinematic design and development of a two degree-of-freedom (2DOF) spherical 5-bar thumb exoskeleton to augment the finger individuating grasp exercise robot (FINGER) rehabilitation robot, which assists the index and middle fingers individually in naturalistic grasping. The thumb module expands the capabilities of FINGER, allowing for broader proprioceptive training and assessment of hand function. The design process started by digitizing thumb-grasping motions to the index and the middle fingers separately, recorded from multiple healthy subjects utilizing a motion capture system. Fitting spheres to trajectory data of each subject allowed normalization of all subjects' data to a common center and radius. A two-revolute joint serial-chain mechanism was synthesized (intermediate optimization step) to reach the normalized trajectories. Next, the two resulting grasping trajectories were spatially sampled as targets for the 2DOF spherical 5-bar synthesis. Optimization of the spherical 5-bar included symmetry constraints and cost-function penalties for poor manipulability. The resulting exoskeleton assists both flexion/extension and abduction/adduction of the thumb enabling a wide range of motions. Consistent with FINGER, the parallel structure of the spherical 5-bar places the actuators at the base of the module, allowing for desirable characteristics, including high backdrivability, high controllable bandwidth, and low mechanical impedance. The mechanical design was developed from the kinematic solution, including an adjustable thumb cuff to accommodate different hand sizes. Fit and function of the device were tested on multiple subjects, including survivors of stroke. A proportional-derivative force controller with gravity and friction compensation was implemented to reduce resistance to motion during subject testing.

Exoskeleton-Assisted Anthropomorphic Movement Training for the Upper Limb After Stroke: The EAMT Randomized Trial

BACKGROUND

Robot-assisted arm training is generally delivered in the robot-like manner of planar or mechanical 3-dimensional movements. It remains unclear whether integrating upper extremity (UE) natural coordinated patterns into a robotic exoskeleton can improve outcomes. The study aimed to compare conventional therapist-mediated training to the practice of human-like gross movements derived from 5 typical UE functional activities managed with exoskeletal assistance as needed for patients after stroke.

METHODS

In this randomized, single-blind, noninferiority trial, patients with moderate-to-severe UE motor impairment due to subacute stroke were randomly assigned (1:1) to receive 20 sessions of 45-minute exoskeleton-assisted anthropomorphic movement training or conventional therapy. Treatment allocation was masked from independent assessors, but not from patients or investigators. The primary outcome was the change in the Fugl-Meyer Assessment for Upper Extremity from baseline to 4 weeks against a prespecified noninferiority margin of 4 points. Superiority would be tested if noninferiority was demonstrated. Post hoc subgroup analyses of baseline characteristics were performed for the primary outcome.

RESULTS

Between June 2020 and August 2021, totally 80 inpatients (67 [83.8%] males; age, 51.9±9.9 years; days since stroke onset, 54.6±38.0) were enrolled, randomly assigned to the intervention, and included in the intention-to-treat analysis. The mean Fugl-Meyer Assessment for Upper Extremity change in exoskeleton-assisted anthropomorphic movement training (14.73 points; [95% CI, 11.43-18.02]) was higher than that of conventional therapy (9.90 points; [95% CI, 8.15-11.65]) at 4 weeks (adjusted difference, 4.51 points [95% CI, 1.13-7.90]). Moreover, post hoc analysis favored the patient subgroup (Fugl-Meyer Assessment for Upper Extremity score, 23-38 points) with moderately severe motor impairment.

CONCLUSIONS

Exoskeleton-assisted anthropomorphic movement training appears to be effective for patients with subacute stroke through repetitive practice of human-like movements. Although the results indicate a positive sign for exoskeleton-assisted anthropomorphic movement training, further investigations into the long-term effects and paradigm optimization are warranted.

REGISTRATION

URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100044078.

Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review

BACKGROUND

Neuromotor rehabilitation and improvement of upper limb functions are necessary to improve the life quality of patients who have experienced injuries or have pathological outcomes. Modern approaches, such as robotic-assisted rehabilitation can help to improve rehabilitation processes and thus improve upper limb functions. Therefore, the aim of this study was to investigate the role of robots in upper limb disability improvement and rehabilitation.

METHODS

This scoping review was conducted by search in PubMed, Web of Science, Scopus, and IEEE (January 2012- February 2022). Articles related to upper limb rehabilitation robots were selected. The methodological quality of all the included studies will be appraised using the Mixed Methods Appraisal Tool (MMAT). We used an 18-field data extraction form to extract data from articles and extracted the information such as study year, country, type of study, purpose, illness or accident leading to disability, level of disability, assistive technologies, number of participants in the study, sex, age, rehabilitated part of the upper limb using a robot, duration and frequency of treatment, methods of performing rehabilitation exercises, type of evaluation, number of participants in the evaluation process, duration of intervention, study outcomes, and study conclusions. The selection of articles and data extraction was made by three authors based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth author. Inclusion criteria were articles involving upper limb rehabilitation robots, articles about upper limb disability caused by any illness or injury, and articles published in English. Also, articles involving other than upper limb rehabilitation robots, robots related to rehabilitation of diseases other than upper limb, systematic reviews, reviews, and meta-analyses, books, book chapters, letters to the editor, and conference papers were also excluded. Descriptive statistics methods (frequency and percentage) were used to analyses the data.

RESULTS

We finally included 55 relevant articles. Most of the studies were done in Italy (33.82%). Most robots were used to rehabilitate stroke patients (80%). About 60.52% of the studies used games and virtual reality rehabilitate the upper limb disabilities using robots. Among the 14 types of applied evaluation methods, "evaluation and measurement of upper limb function and dexterity" was the most applied evaluation method. "Improvement in musculoskeletal functions", "no adverse effect on patients", and "Safe and reliable treatment" were the most cited outcomes, respectively.

CONCLUSIONS

Our findings show that robots can improve musculoskeletal functions (musculoskeletal strength, sensation, perception, vibration, muscle coordination, less spasticity, flexibility, and range of motion) and empower people by providing a variety of rehabilitation capabilities.

Sensor-Based Rehabilitation in Neurological Diseases: A Bibliometric Analysis of Research Trends

BACKGROUND

As the field of sensor-based rehabilitation continues to expand, it is important to gain a comprehensive understanding of its current research landscape. This study aimed to conduct a bibliometric analysis to identify the most influential authors, institutions, journals, and research areas in this field.

METHODS

A search of the Web of Science Core Collection was performed using keywords related to sensor-based rehabilitation in neurological diseases. The search results were analyzed with CiteSpace software using bibliometric techniques, including co-authorship analysis, citation analysis, and keyword co-occurrence analysis.

RESULTS

Between 2002 and 2022, 1103 papers were published on the topic, with slow growth from 2002 to 2017, followed by a rapid increase from 2018 to 2022. The United States was the most active country, while the Swiss Federal Institute of Technology had the highest number of publications among institutions. Sensors published the most papers. The top keywords included rehabilitation, stroke, and recovery. The clusters of keywords comprised machine learning, specific neurological conditions, and sensor-based rehabilitation technologies.

CONCLUSIONS

This study provides a comprehensive overview of the current state of sensor-based rehabilitation research in neurological diseases, highlighting the most influential authors, journals, and research themes. The findings can help researchers and practitioners to identify emerging trends and opportunities for collaboration and can inform the development of future research directions in this field.

Experimental Evaluation of EMKEY: An Assistive Technology for People with Upper Limb Disabilities

Assistive technology can help people with disabilities to use computers more effectively and can enable them to access the same information and resources as people without disabilities. To obtain more insight into the factors that can bring about the design of an Emulator of Mouse and Keyboard (EMKEY) to higher levels of user satisfaction, an experimental study was conducted in order to analyse its effectiveness and efficiency. The experimental study involved 27 participants (M_age = 20.81, SD = 1.14) who performed three experimental games under different conditions (using the mouse and using EMKEY with head movements and voice commands). According to the results, the use of EMKEY allowed for the successful performance of tasks such as matching stimuli (F_(2,78) = 2.39, p = 0.10, η² = 0.06). However, the execution times of a task were found to be higher when using the emulator to drag an object on the screen (t_(52,1) = -18.45, p ≤ 0.001, d = 9.60). These results indicate the effectiveness of technological development for people with upper limb disabilities; however, there is room for improvement in terms of efficiency. The findings are discussed in relation to previous research and are based on future studies aimed at improving the operation of the EMKEY emulator.

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

BACKGROUND

This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke.

METHODS

The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires.

RESULTS

Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported.

CONCLUSIONS

Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.

Upper limb home-based robotic rehabilitation in chronic stroke patients: A pilot study

Introduction

Robotic therapy allow to propose sessions of controlled and identical exercises, customizing settings, and characteristics on the individual patient. The effectiveness of robotic assisted therapy is still under study and the use of robots in clinical practice is still limited. Moreover, the possibility of treatment at home allows to reduce the economic costs and time to be borne by the patient and the caregiver and is a valid tool during periods of pandemic such as covid. The aim of this study is to assess whether a robotic home-based treatment rehabilitation using the iCONE robotic device has effects on a stroke population, despite the chronic condition of patients involved and the absence of a therapist next to the patient while performing the exercises.

Materials and methods

All patients underwent an initial (T0) and final (T1) assessment with the iCONE robotic device and clinical scales. After T0 evaluation, the robot was delivered to the patient's home for 10 days of at-home treatment (5 days a week for 2 weeks).

Results

Comparison between T0 and T1 evaluations revealed some significant improvements in robot-evaluated indices such as Independence and Size for the Circle Drawing exercise and Movement Duration for Point-to-Point exercise, but also in the MAS of the elbow. From the analysis of the acceptability questionnaire, a general appreciation of the robot emerged: patients spontaneously asked for the addition of further sessions and to continue therapy.

Discussion

Telerehabilitation of patients suffering from a chronic stroke is an area that is still little explored. From our experience, this is one of the first studies to carry out a telerehabilitation with these characteristics. The use of robots can become a method to reduce the rehabilitation health costs, to ensure continuity of care, and to arrive in more distant places or where the availability of resources is limited.

Conclusion

From the data obtained, this rehabilitation seems to be promising for this population. Moreover, promoting the recovery of the upper limb, iCONE can improve patient's quality of life. It would be interesting to conduct RCT studies to compare a conventional treatment in structure with a robotic telematics treatment.

An augmented reality interface to control a collaborative robot in rehab: A preliminary usability evaluation

Human emotions can be seen as a valuable variable to explore in Human-Computer Interaction for effective, efficient, and satisfying interface development. The inclusion of appropriate emotional triggers in the design of interactive systems can play a decisive role in users' acceptance or rejection. It is well known that the major problem in motor rehabilitation is the high dropout rate resulting from the frustrated expectations given the typical slow recovery process and consequent lack of motivation to endure. This work proposes grouping a collaborative robot with one specific augmented reality equipment to create a rehabilitation system where some gamification levels might be added to provide a better and more motivating experience to patients. Such a system, as a whole, is customizable to adapt to each patient's needs on the rehabilitation exercises. By transforming a tedious exercise into a game, we expect to create an additional layer of enjoyment that can help in triggering positive emotions and stimulate users to continue the rehabilitation process. A pre-prototype was developed to validate this system's usability, and a cross-sectional study using a non-probabilistic sample of 31 individuals is presented and discussed. This study included the application of three standard questionnaires on usability and user experience. The analyses of these questionnaires show that the majority of the users found the system easy and enjoyable. The system was also analysed by a rehabilitation expert who gave a positive output regarding its usefulness, and positive impact on its use in the upper-limb rehabilitation processes. These results clearly encourage further development of the proposed system.

Bridging the Finger-Action Gap between Hand Patients and Healthy People in Daily Life with a Biomimetic System

The hand is involved very deeply in our lives in daily activities. When a person loses some hand function, their life can be greatly affected. The use of robotic rehabilitation to assist patients in performing daily actions might help alleviate this problem. However, how to meet individual needs is a major problem in the application of robotic rehabilitation. A biomimetic system (artificial neuromolecular system, ANM) implemented on a digital machine is proposed to deal with the above problems. Two important biological features (structure-function relationship and evolutionary friendliness) are incorporated into this system. With these two important features, the ANM system can be shaped to meet the specific needs of each individual. In this study, the ANM system is used to help patients with different needs perform 8 actions similar to those that people use in everyday life. The data source of this study is our previous research results (data of 30 healthy people and 4 hand patients performing 8 activities of daily life). The results show that while each patient's hand problem is different, the ANM can successfully translate each patient's hand posture into normal human motion. In addition, the system can respond to this difference smoothly rather than dramatically when the patient's hand motions vary both temporally (finger motion sequence) and spatially (finger curvature).

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.

Cognitive and motor cortex activation during robot-assisted multi-sensory interactive motor rehabilitation training: An fNIRS based pilot study

Objective

This study aimed to evaluate the effects of multiple virtual reality (VR) interaction modalities based on force-haptic feedback combined with visual or auditory feedback in different ways on cerebral cortical activation by functional near-infrared spectroscopy (fNIRS). Methods: A modular multi-sensory VR interaction system based on a planar upper-limb rehabilitation robot was developed. Twenty healthy participants completed active elbow flexion and extension training in four VR interaction patterns, including haptic (H), haptic + auditory (HA), haptic + visual (HV), and haptic + visual + auditory (HVA). Cortical activation changes in the sensorimotor cortex (SMC), premotor cortex (PMC), and prefrontal cortex (PFC) were measured.

Results

Four interaction patterns all had significant activation effects on the motor and cognitive regions of the cerebral cortex (p < 0.05). Among them, in the HVA interaction mode, the cortical activation of each ROI was the strongest, followed by HV, HA, and H. The connectivity between channels of SMC and bilateral PFC, as well as the connectivity between channels in PMC, was the strongest under HVA and HV conditions. Besides, the two-way ANOVA of visual and auditory feedback showed that it was difficult for auditory feedback to have a strong impact on activation without visual feedback. In addition, under the condition of visual feedback, the effect of fusion auditory feedback on the activation degree was significantly higher than that of no auditory feedback.

Conclusions

The interaction mode of visual, auditory, and haptic multi-sensory integration is conducive to stronger cortical activation and cognitive control. Besides, there is an interaction effect between visual and auditory feedback, thus improving the cortical activation level. This research enriches the research on activation and connectivity of cognitive and motor cortex in the process of modular multi-sensory interaction training of rehabilitation robots. These conclusions provide a theoretical basis for the optimal design of the interaction mode of the rehabilitation robot and the possible scheme of clinical VR rehabilitation.

Restoring arm function with a soft robotic wearable for individuals with amyotrophic lateral sclerosis

Despite promising results in the rehabilitation field, it remains unclear whether upper limb robotic wearables, e.g., for people with physical impairments resulting from neurodegenerative disease, can be made portable and suitable for everyday use. We present a lightweight, fully portable, textile-based, soft inflatable wearable robot for shoulder elevation assistance that provides dynamic active support to the upper limbs. The technology is mechanically transparent when unpowered, can quantitatively assess free movement of the user, and adds only 150 grams of weight to each upper limb. In 10 individuals with amyotrophic lateral sclerosis (ALS) with different degrees of neuromuscular impairment, we demonstrated immediate improvement in the active range of motion and compensation for continuing physical deterioration in two individuals with ALS over 6 months. Along with improvements in movement, we show that this robotic wearable can improve functional activity without any training, restoring performance of basic activities of daily living. In addition, a reduction in shoulder muscle activity and perceived muscular exertion, coupled with increased endurance for holding objects, highlight the potential of this device to mitigate the impact of muscular fatigue for patients with ALS. These results represent a further step toward everyday use of assistive, soft, robotic wearables for the upper limbs.

Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System

In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The "virtual stiffness" method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations.

Development and Validation of a System for the Assessment and Recovery of Grip Force Control

The ability to finely control hand grip forces can be compromised by neuromuscular or musculoskeletal disorders. Therefore, it is recommended to include the training and assessment of grip force control in rehabilitation therapy. The benefits of robot-mediated therapy have been widely reported in the literature, and its combination with virtual reality and biofeedback can improve rehabilitation outcomes. However, the existing systems for hand rehabilitation do not allow both monitoring/training forces exerted by single fingers and providing biofeedback. This paper describes the development of a system for the assessment and recovery of grip force control. An exoskeleton for hand rehabilitation was instrumented to sense grip forces at the fingertips, and two operation modalities are proposed: (i) an active-assisted training to assist the user in reaching target force values and (ii) virtual reality games, in the form of tracking tasks, to train and assess the user's grip force control. For the active-assisted modality, the control of the exoskeleton motors allowed generating additional grip force at the fingertips, confirming the feasibility of this modality. The developed virtual reality games were positively accepted by the volunteers and allowed evaluating the performance of healthy and pathological users.

SE-TCN network for continuous estimation of upper limb joint angles

The maturity of human-computer interaction technology has made it possible to use surface electromyographic signals (sEMG) to control exoskeleton robots and intelligent prostheses. However, the available upper limb rehabilitation robots controlled by sEMG have the shortcoming of inflexible joints. This paper proposes a method based on a temporal convolutional network (TCN) to predict upper limb joint angles by sEMG. The raw TCN depth was expanded to extract the temporal features and save the original information. The timing sequence characteristics of the muscle blocks that dominate the upper limb movement are not apparent, leading to low accuracy of the joint angle estimation. Therefore, this study squeeze-and-excitation networks (SE-Net) to improve the network model of the TCN. Finally, seven movements of the human upper limb were selected for ten human subjects, recording elbow angle (EA), shoulder vertical angle (SVA), and shoulder horizontal angle (SHA) values during their movements. The designed experiment compared the proposed SE-TCN model with the backpropagation (BP) and long short-term memory (LSTM) networks. The proposed SE-TCN systematically outperformed the BP network and LSTM model by the mean RMSE values: by 25.0 and 36.8% for EA, by 38.6 and 43.6% for SHA, and by 45.6 and 49.5% for SVA, respectively. Consequently, its R² values exceeded those of BP and LSTM by 13.6 and 39.20% for EA, 19.01 and 31.72% for SHA, and 29.22 and 31.89% for SVA, respectively. This indicates that the proposed SE-TCN model has good accuracy and can be used to estimate the angles of upper limb rehabilitation robots in the future.

Kinematic analysis and development of cable-driven rehabilitation robot for cerebral palsy patients

This study aimed to analyze the kinematic development of a rehabilitation cable robot for patients with cerebral palsy problems. For this purpose, the walking pattern of a healthy person was analyzed in the robot by extracting his kinematic model. Therefore, a seven-link model was considered, and changes in the mass center of the links and then movements during the gait cycle were obtained with the angles related to joint changes. Next, the person’s integration with the rehabilitation cable robot was investigated with the resolution of the direct kinematic problem. In addition, the change-related outputs of the cables were obtained by the person’s movement and the attached belt. The robot was further proposed because the specific change diagram of the cables facilitates understanding how much motor torque is needed to change the length of the cable. It is noteworthy that the static person balance is provided in the existing rehabilitation robots. However, in this structure, the balance is done by the six degrees of freedom robot so that the robot can return the person to the original path when he loses his balance. Cable systems for the lower limbs (thighs and shanks) are also simulated to rehabilitate the patient. The obtained results from the simulation and the obtained output from kinematic equations for lower limb movements were also compared, and the highest deference was 2.2, 1.8, 1.8, and 1.5% for shank-back, shank-front, thigh-back, and thigh-front of the leg in the corresponding points in the outputs of both software, respectively.

Effectiveness of robot-assisted arm therapy in stroke rehabilitation: An overview of systematic reviews

BACKGROUND

Robot-assisted arm therapy (RAT) has been used mainly in stroke rehabilitation in the last 20 years with rising expectations and growing evidence summarized in systematic reviews (SRs).

OBJECTIVE

The aim of this study is to provide an overview of SRs about the effectiveness, within the ICF domains, and safety of RAT in the rehabilitation of adult with stroke compared to other treatments.

METHODS

The search strategy was conducted using search strings adapted explicitly for each database. A screening base on title and abstract was realized to find all the potentially relevant studies. The methodological quality of the included SRs was assessed using AMSTAR-2. A pre-determined standardized form was used to realize the data extraction.

RESULTS

18 SRs were included in this overview. Generally, positive effects from the RAT were found for motor function and muscle strength, whereas there is no agreement for muscle tone effects. No effect was found for pain, and only a SR reported the positive impact of RAT in daily living activity.

CONCLUSION

RAT can be considered a valuable option to increase motor function and muscle strength after stroke. However, the poor quality of most of the included SRs could limit the certainty around the results.

Planar Model for Vibration Analysis of Cable Rehabilitation Robots

Cable robots are widely used in the field of rehabilitation. These robots differ from other cable robots because the cables are rather short and are usually equipped with magnetic hooks to improve the ease of use. The vibrations of rehabilitation robots are dominated by the effects of the hooks and payloads, whereas the cables behave as massless springs. In this paper, a 2D model of the cables of a robot that simulates both longitudinal and transverse vibrations is developed and experimentally validated. Then the model is extended to simulate the vibrations of an actual 3D robot in the symmetry planes. Finally, the calculated modal properties (natural frequencies and modes of vibration) are compared with the typical spectrum of excitation due to the cable’s motion. Only the first transverse mode can be excited during the rehabilitation exercise.