Assessment-driven selection and adaptation of exercise difficulty in robot-assisted therapy: a pilot study with a hand rehabilitation robot

Understanding task "challenge" in stroke rehabilitation: an interdisciplinary concept analysis

PURPOSE

Rehabilitation plays a critical role in minimising disability after stroke, with the concept of "challenge" proposed to be essential to rehabilitation efficacy and outcomes. This review unpacks how challenge is conceptualised in stroke rehabilitation literature from the perspectives of physiotherapy, occupational therapy, speech-language therapy and people with stroke. A secondary purpose was to provide a definition of challenge that is applicable to stroke rehabilitation.

METHODS

Principle-based concept analysis was utilised to examine challenge within the stroke rehabilitation literature. Forty-two papers were included. Data analysis involved immersion, analytical questioning, coding and synthesis to elicit the conceptual components of challenge.

RESULTS

Challenge was understood as a multidimensional and dynamic concept with three facets: nominal, functional and perceived challenge. Functional and perceived challenge were integral to optimal challenge. Optimal challenge was central to enhancing the outcomes and experiences of people with stroke, in rehabilitation and everyday life.

CONCLUSIONS

Challenge is a key concept which, when carefully optimised to the person's ability and experience, may positively influence their learning, recovery and engagement after stroke. This review lays a conceptual foundation for better understanding, operationalisation and advancement of challenge, offering important implications for addressing the growing burden of stroke disability, through rehabilitation.

Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience

BACKGROUND

Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the unsupervised use of robotic technologies is not yet a standard, as rehabilitation robots often show low usability or are considered unsafe to be used by patients independently. In this paper we explore the feasibility of unsupervised therapy with an upper limb rehabilitation robot in a clinical setting, evaluate the effect on the overall therapy dose, and assess user experience during unsupervised use of the robot and its usability.

METHODS

Subacute stroke patients underwent a four-week protocol composed of daily 45 min-sessions of robot-assisted therapy. The first week consisted of supervised therapy, where a therapist explained how to interact with the device. The second week was minimally supervised, i.e., the therapist was present but intervened only if needed. After this phase, if participants learnt how to use the device, they proceeded to two weeks of fully unsupervised training. Feasibility, dose of robot-assisted therapy achieved during unsupervised use, user experience, and usability of the device were evaluated. Questionnaires to evaluate usability and user experience were performed after the minimally supervised week and at the end of the study, to evaluate the impact of therapists' absence.

RESULTS

Unsupervised robot-assisted therapy was found to be feasible, as 12 out of the 13 recruited participants could progress to unsupervised training. During the two weeks of unsupervised therapy participants on average performed an additional 360 min of robot-assisted rehabilitation. Participants were satisfied with the device usability (mean System Usability Scale scores > 79), and no adverse events or device deficiencies occurred.

CONCLUSIONS

We demonstrated that unsupervised robot-assisted therapy in a clinical setting with an actuated device for the upper limb was feasible and can lead to a meaningful increase in therapy dose. These results support the application of unsupervised robot-assisted therapy as a complement to usual care in clinical settings and pave the way to its application in home settings.

TRIAL REGISTRATION

Registered on 13.05.2020 on clinicaltrials.gov (NCT04388891).

A usability study on mobile EMG-guided wrist extension training in subacute stroke patients-MyoGuide

BACKGROUND

Effective stroke rehabilitation requires high-dose, repetitive-task training, especially during the early recovery phase. However, the usability of upper-limb rehabilitation technology in acute and subacute stroke survivors remains relatively unexplored. In this study, we introduce subacute stroke survivors to MyoGuide, a mobile training platform that employs surface electromyography (sEMG)-guided neurofeedback training that specifically targets wrist extension. Notably, the study emphasizes evaluating the platform's usability within clinical contexts.

METHODS

Seven subacute post-stroke patients (1 female, mean age 53.7 years, mean time post-stroke 58.9 days, mean duration per training session 48.9 min) and three therapists (one for eligibility screening, two for conducting training) participated in the study. Participants underwent ten days of supervised one-on-one wrist extension training with MyoGuide, which encompassed calibration, stability assessment, and dynamic tasks. All training records including the Level of Difficulty (LoD) and Stability Assessment Scores were recorded within the application. Usability was assessed through the System Usability Scale (SUS) and participants' willingness to continue home-based training was gauged through a self-developed survey post-training. Therapists also documented the daily performance of participants and the extent of support required.

RESULTS

The usability analysis yielded positive results, with a median SUS score of 82.5. Compared to the first session, participants significantly improved their performance at the final session as indicated by both the Stability Assessment Scores (p = 0.010, mean = 229.43, CI = [25.74-433.11]) and the LoD (p < 0.001; mean: 45.43, CI: [25.56-65.29]). The rate of progression differed based on the initial impairment levels of the patient. After training, participants expressed a keen interest in continuing home-based training. However, they also acknowledged challenges related to independently using the Myo armband and software.

CONCLUSIONS

This study introduces the MyoGuide training platform and demonstrates its usability in a clinical setting for stroke rehabilitation, with the assistance of a therapist. The findings support the potential of MyoGuide for wrist extension training in patients across a wide range of impairment levels. However, certain usability challenges, such as donning/doffing the armband and navigating the application, need to be addressed to enable independent MyoGuide training requiring only minimal supervision by a therapist.

Interactive curriculum learning increases and homogenizes motor smoothness

One of the challenges of technology-assisted motor learning is how to adapt practice to facilitate learning. Random practice has been shown to promote long-term learning. However, it does not adapt to the learner's specific learning requirements. Previous attempts to adapt learning considered the skill level of learners from past training sessions. This study investigates the effects of personalizing practice in real time, through a curriculum learning approach, where a curriculum of tasks is built by considering consecutive performance differences for each task. 12 participants were allocated to each of three training conditions in an experiment which required performing a steering task to drive a cursor in an arc channel. The curriculum learning approach was compared to two other conditions: random practice and another adaptive practice, which does not consider the learning evolution. The curriculum learning practice outperformed the random practice in effectively increasing movement smoothness at post-test and outperformed both the random practice and the adaptive practice on transfer tests. The adaptation of practice through the curriculum learning approach also made learners' skills more uniform. Based on these findings, we anticipate that future research will explore the use of curriculum learning in interactive training tools to support motor skill learning, such as rehabilitation.

Progressive Transition From Supervised to Unsupervised Robot-Assisted Therapy After Stroke: Protocol for a Single-Group, Interventional Feasibility Study

BACKGROUND

Increasing the dose of therapy delivered to patients with stroke may improve functional outcomes and quality of life. Unsupervised technology-assisted rehabilitation is a promising way to increase the dose of therapy without dramatically increasing the burden on the health care system. Despite the many existing technologies for unsupervised rehabilitation, active rehabilitation robots have rarely been tested in a fully unsupervised way. Furthermore, the outcomes of unsupervised technology-assisted therapy (eg, feasibility, acceptance, and increase in therapy dose) vary widely. This might be due to the use of different technologies as well as to the broad range of methods applied to teach the patients how to independently train with a technology.

OBJECTIVE

This paper describes the study design of a clinical study investigating the feasibility of unsupervised therapy with an active robot and of a systematic approach for the progressive transition from supervised to unsupervised use of a rehabilitation technology in a clinical setting. The effect of unsupervised therapy on achievable therapy dose, user experience in this therapy setting, and the usability of the rehabilitation technology are also evaluated.

METHODS

Participants of the clinical study are inpatients of a rehabilitation clinic with subacute stroke undergoing a 4-week intervention where they train with a hand rehabilitation robot. The first week of the intervention is supervised by a therapist, who teaches participants how to interact and train with the device. The second week consists of minimally supervised therapy, where the therapist is present but intervenes only if needed as participants exercise with the device. If the participants properly learn how to train with the device, they proceed to the unsupervised phase and train without any supervision during the third and fourth weeks. Throughout the duration of the study, data on feasibility and therapy dose (ie, duration and repetitions) are collected. Usability and user experience are evaluated at the end of the second (ie, minimally supervised) and fourth (ie, unsupervised) weeks, allowing us to investigate the effect of therapist absence.

RESULTS

As of April 2023, 13 patients were recruited and completed the protocol, with no reported adverse events.

CONCLUSIONS

This study will inform on the feasibility of fully unsupervised rehabilitation with an active rehabilitation robot in a clinical setting and its effect on therapy dose. Furthermore, if successful, the proposed systematic approach for a progressive transition from supervised to unsupervised technology-assisted rehabilitation could serve as a benchmark to allow for easier comparisons between different technologies. This approach could also be extended to the application of such technologies in the home environment, as the supervised and minimally supervised sessions could be performed in the clinic, followed by unsupervised therapy at home after discharge.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04388891; https://clinicaltrials.gov/study/NCT04388891.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48485.

Mechanical digit sensory stimulation: a randomized control trial on neurological and motor recovery in acute stroke

Background

Mechanical digit sensory stimulation (MDSS) is a novel therapy designed to accelerate the recovery of upper limb (including hand) function in patients with hemiplegia following a stroke. The primary goal of this study was to investigate the effect of MDSS on patients with acute ischemic stroke (AIS).

Methods

Sixty-one inpatients with AIS were randomly divided into conventional rehabilitation group (RG) and stimulation group (SG), and the latter group received MDSS therapy. A healthy group consisting of 30 healthy adults was also included. The interleukin-17A (IL-17A), vascular endothelial growth factor A (VEGF-A), and tumor necrosis factor-alpha (TNF-α) plasma levels were measured in all subjects. The neurological and motor functions of patients were evaluated using the National Institutes of Health Stroke Scale (NIHSS), Mini-Mental State Examination (MMSE), Fugel-Meyer Assessment (FMA), and Modified Barthel Index (MBI).

Results

After 12 days of intervention, the IL-17A, TNF-α, and NIHSS levels were significantly decreased, while the VEGF-A, MMSE, FMA, and MBI levels were significantly increased in both disease groups. No significant difference was observed between both disease groups after intervention. The levels of IL-17A and TNF-α were positively correlated with NIHSS but negatively correlated with MMSE, FMA, and MBI. The VEGF-A levels were negatively correlated with NIHSS but positively correlated with MMSE, FMA, and MBI.

Conclusion

Both MDSS and conventional rehabilitation significantly reduce the production of IL-17A and TNF-α, increase the VEGF-A levels, and effectively improve cognition and motor function of hemiplegic patients with AIS, and the effects of MDSS and conventional rehabilitation are comparable.

An online method to monitor hand muscle tone during robot-assisted rehabilitation

Introduction: Robot-assisted neurorehabilitation is becoming an established method to complement conventional therapy after stroke and provide intensive therapy regimes in unsupervised settings (e.g., home rehabilitation). Intensive therapies may temporarily contribute to increasing muscle tone and spasticity, especially in stroke patients presenting tone alterations. If sustained without supervision, such an increase in muscle tone could have negative effects (e.g., functional disability, pain). We propose an online perturbation-based method that monitors finger muscle tone during unsupervised robot-assisted hand therapy exercises. Methods: We used the ReHandyBot, a novel 2 degrees of freedom (DOF) haptic device to perform robot-assisted therapy exercises training hand grasping (i.e., flexion-extension of the fingers) and forearm pronosupination. The tone estimation method consisted of fast (150 ms) and slow (250 ms) 20 mm ramp-and-hold perturbations on the grasping DOF, which were applied during the exercises to stretch the finger flexors. The perturbation-induced peak force at the finger pads was used to compute tone. In this work, we evaluated the method performance in a stiffness identification experiment with springs (0.97 and 1.57 N/mm), which simulated the stiffness of a human hand, and in a pilot study with subjects with increased muscle tone after stroke and unimpaired, which performed one active sensorimotor exercise embedding the tone monitoring method. Results: The method accurately estimates forces with root mean square percentage errors of 3.8% and 11.3% for the soft and stiff spring, respectively. In the pilot study, six chronic ischemic stroke patients [141.8 (56.7) months after stroke, 64.3 (9.5) years old, expressed as mean (std)] and ten unimpaired subjects [59.9 (6.1) years old] were tested without adverse events. The average reaction force at the level of the fingertip during slow and fast perturbations in the exercise were respectively 10.7 (5.6) N and 13.7 (5.6) N for the patients and 5.8 (4.2) N and 6.8 (5.1) N for the unimpaired subjects. Discussion: The proposed method estimates reaction forces of physical springs accurately, and captures online increased reaction forces in persons with stroke compared to unimpaired subjects within unsupervised human-robot interactions. In the future, the identified range of muscle tone increase after stroke could be used to customize therapy for each subject and maintain safety during intensive robot-assisted rehabilitation.

Effects of robotic upper limb treatment after stroke on cognitive patterns: A systematic review

BACKGROUND

Robotic therapy (RT) has been internationally recognized for the motor rehabilitation of the upper limb. Although it seems that RT can stimulate and promote neuroplasticity, the effectiveness of robotics in restoring cognitive deficits has been considered only in a few recent studies.

OBJECTIVE

To verify whether, in the current state of the literature, cognitive measures are used as inclusion or exclusion criteria and/or outcomes measures in robotic upper limb rehabilitation in stroke patients.

METHODS

The systematic review was conducted according to PRISMA guidelines. Studies eligible were identified through PubMed/MEDLINE and Web of Science from inception to March 2021.

RESULTS

Eighty-one studies were considered in this systematic review. Seventy-three studies have at least a cognitive inclusion or exclusion criteria, while only seven studies assessed cognitive outcomes.

CONCLUSION

Despite the high presence of cognitive instruments used for inclusion/exclusion criteria their heterogeneity did not allow the identification of a guideline for the evaluation of patients in different stroke stages. Therefore, although the heterogeneity and the low percentage of studies that included cognitive outcomes, seemed that the latter were positively influenced by RT in post-stroke rehabilitation. Future larger RCTs are needed to outline which cognitive scales are most suitable and their cut-off, as well as what cognitive outcome measures to use in the various stages of post-stroke rehabilitation.

Design and Preliminary Evaluation of a Robot-assisted Assessment-driven Finger Proprioception Therapy

Neurological injuries such as stroke often lead to motor and somatosensory impairments of the hand. Deficits in somatosensation, especially proprioception, result in difficulties performing activities of daily living involving fine motor tasks. However, it is challenging to accurately detect those impairments due to the limitations of clinical assessments. Hence therapies rarely focus on proprioception specifically, while such training could promote functional benefits. In this work we propose and preliminarily evaluate a robot-assisted, assessment-driven therapy of finger proprioception. We designed and implemented two therapeutic exercises, one targeting passive and the other active position sense. The difficulty level of the therapy exercises was adapted to each patient's proprioceptive impairment. We evaluated the exercises and their usability with 7 stroke participants and 8 clinicians in a 45-minutes protocol. We found that the exercises were feasible for stroke participants, as 5 individuals progressed in difficulty levels over multiple exercise repetitions, indicating adequacy of the adaptation algorithm. Moreover, usability was rated mostly as satisfactory by the patients (System Usability Scale = 73), and they also found the exercises interesting. Clinicians rated the exercises as difficult but clinically meaningful. Overall, these promising preliminary results pave the way for further development and validation of the proposed therapy approach.

Learning Dynamic Patient-Robot Task Assignment and Scheduling for A Robotic Rehabilitation Gym

A robotic rehabilitation gym is a setup that allows multiple patients to exercise together using multiple robots. The effectiveness of training in such a group setting could be increased by dynamically assigning patients to specific robots. In this simulation study, we develop an automated system that dynamically makes patient-robot assignments based on measured patient performance to achieve optimal group rehabilitation outcome. To solve the dynamic assignment problem, we propose an approach that uses a neural network classifier to predict the assignment priority between two patients for a specific robot given their task success rate on that robot. The priority classifier is trained using assignment demonstrations provided by a domain expert. In the absence of real human data from a robotic gym, we develop a robotic gym simulator and create a synthetic dataset for training the classifier. The simulation results show that our approach makes effective assignments that yield comparable patient training outcomes to those obtained by the domain expert.

Automatic and Personalized Adaptation of Therapy Parameters for Unsupervised Robot-Assisted Rehabilitation: a Pilot Evaluation

Growing evidence shows that increasing the dose of upper limb therapy after stroke might improve functional outcomes and unsupervised robot-assisted therapy may be a solution to achieve such an increase without adding workload on therapists. However, most of existing robotic devices still need frequent supervision by trained personnel and are currently not designed or ready for unsupervised use. One reason for this is that most rehabilitation devices are not capable of delivering and adapting personalized therapy without external intervention. Here we present a set of clinically-inspired algorithms that automatically adapt therapy parameters in a personalized way and guide the course of robot-assisted therapy sessions. We implemented these algorithms on a robotic device for hand rehabilitation and tested them in a pilot study with 5 subacute stroke subjects over 10 robot-assisted therapy sessions, some of which unsupervised. Results show that our algorithms could adapt the therapy difficulty throughout the whole study without requiring external intervention, maintaining performance around a predefined 70% target value (mean performance for all the subjects over all the sessions: 64.5%). Moreover, the algorithms could guide patients through the therapy sessions, minimizing the number of actions that subjects had to learn and perform. These results open the door to the use of robotic devices in an unsupervised setting to increase therapy dose after stroke.

Towards Unsupervised Rehabilitation: Development of a Portable Compliant Device for Sensorimotor Hand Rehabilitation

Sensorimotor impairments of the hand after stroke can drastically reduce the ability to perform activities of daily living. Recently, there has been an increased interest in minimally supervised and unsupervised rehabilitation to increase therapy dosage and to complement conventional therapy. Several devices have been developed that are simple to use and portable. Yet, they do not incorporate diversified somatosensory feedback, which has been suggested to promote sensorimotor recovery. Here we present the prototype of a portable one-degree-of-freedom hand trainer based on a novel compliant shell mechanism. Our solution is safe, intuitive, and can be used for various hand sizes. Importantly, it also provides rich sensory feedback through haptic rendering. We complement our device with a rehabilitation game, where we leverage interactive tangible game elements with diverse haptic characteristics to provide somatosensory training and foster recovery.

Impairments in Cognitive Control Using a Reverse Visually Guided Reaching Task Following Stroke

BACKGROUND

Cognitive and motor function must work together quickly and seamlessly to allow us to interact with a complex world, but their integration is difficult to assess directly. Interactive technology provides opportunities to assess motor actions requiring cognitive control.

OBJECTIVE

To adapt a reverse reaching task to an interactive robotic platform to quantify impairments in cognitive-motor integration following stroke.

METHODS

Participants with subacute stroke (N=59) performed two tasks using the Kinarm: Reverse Visually Guided Reaching (RVGR) and Visually Guided Reaching (VGR). Tasks required subjects move a cursor "quickly and accurately" to virtual targets. In RVGR, cursor motion was reversed compared to finger motion (i.e., hand moves left, cursor moves right). Task parameters and Task Scores were calculated based on models developed from healthy controls, and accounted for the influence of age, sex, and handedness.

RESULTS

Many stroke participants (86%) were impaired in RVGR with their affected arm (Task Score > 95% of controls). The most common impairment was increased movement time. Seventy-three percent were also impaired with their less affected arm. The most common impairment was larger initial direction angles of reach. Impairments in RVGR improved over time, but 71% of participants tested longitudinally were still impaired with the affected arm ∼6 months post-stroke. Importantly, although 57% were impaired with the less affected arm at 6 months, these individuals were not impaired in VGR.

CONCLUSIONS

Individuals with stroke were impaired in a reverse reaching task but many did not show similar impairments in a standard reaching task, highlighting selective impairment in cognitive-motor integration.

Professionals' Views and Experiences of Using Rehabilitation Robotics With Stroke Survivors: A Mixed Methods Survey

Objective: To understand the reason for low implementation of clinical and home-based rehabilitation robots and their potential. Design: Online questionnaire (November 2020 and February 2021). Subjects: A total of 100 professionals in stroke rehabilitation area were involved (Physiotherapists n = 62, Occupation therapists n = 35). Interventions: Not applicable. Main Measures: Descriptive statistics and thematic content analysis were used to analyze the responses: 1. Participants' details, 2. Professionals' views and experience of using clinical rehabilitation robots, 3. Professionals' expectation and concerns of using home-based rehabilitation robots. Results: Of 100 responses, 37 had experience of rehabilitation robots. Professionals reported that patients enjoyed using them and they increased accessibility, autonomy, and convenience especially when used at home. The main emergent themes were: "aims and objectives for rehabilitation robotics," "requirements" (functional, software, and safety), "cost," "patient factors" (contraindications, cautions, and concerns), and "staff issues" (concerns and benefits). The main benefits of rehabilitation robots were that they provided greater choice for therapy, increased the amount/intensity of treatment, and greater motivation to practice. Professionals perceived logistical issues (ease of use, transport, and storage), cost and limited adaptability to patients' needs to be significant barriers to tier use, whilst acknowledging they can reduce staff workload to a certain extent. Conclusion: The main reported benefit of rehabilitation robots were they increased the amount of therapy and practice after stroke. Ease of use and adaptability are the key requirements. High cost and staffing resources were the main barriers.

Neurorehabilitation From a Distance: Can Intelligent Technology Support Decentralized Access to Quality Therapy?

Current neurorehabilitation models primarily rely on extended hospital stays and regular therapy sessions requiring close physical interactions between rehabilitation professionals and patients. The current COVID-19 pandemic has challenged this model, as strict physical distancing rules and a shift in the allocation of hospital resources resulted in many neurological patients not receiving essential therapy. Accordingly, a recent survey revealed that the majority of European healthcare professionals involved in stroke care are concerned that this lack of care will have a noticeable negative impact on functional outcomes. COVID-19 highlights an urgent need to rethink conventional neurorehabilitation and develop alternative approaches to provide high-quality therapy while minimizing hospital stays and visits. Technology-based solutions, such as, robotics bear high potential to enable such a paradigm shift. While robot-assisted therapy is already established in clinics, the future challenge is to enable physically assisted therapy and assessments in a minimally supervized and decentralized manner, ideally at the patient’s home. Key enablers are new rehabilitation devices that are portable, scalable and equipped with clinical intelligence, remote monitoring and coaching capabilities. In this perspective article, we discuss clinical and technological requirements for the development and deployment of minimally supervized, robot-assisted neurorehabilitation technologies in patient’s homes. We elaborate on key principles to ensure feasibility and acceptance, and on how artificial intelligence can be leveraged for embedding clinical knowledge for safe use and personalized therapy adaptation. Such new models are likely to impact neurorehabilitation beyond COVID-19, by providing broad access to sustained, high-quality and high-dose therapy maximizing long-term functional outcomes.

Validity, reliability, and sensitivity to motor impairment severity of a multi-touch app designed to assess hand mobility, coordination, and function after stroke

BACKGROUND

The assessment of upper-limb motor impairments after stroke is usually performed using clinical scales and tests, which may lack accuracy and specificity and be biased. Although some instruments exist that are capable of evaluating hand functions and grasping during functional tasks, hand mobility and dexterity are generally either not specifically considered during clinical assessments or these examinations lack accuracy. This study aimed to determine the convergent validity, reliability, and sensitivity to impairment severity after a stroke of a dedicated, multi-touch app, named the Hand Assessment Test.

METHODS

The hand mobility, coordination, and function of 88 individuals with stroke were assessed using the app, and their upper-limb functions were assessed using the Fugl-Meyer Assessment for Upper Extremity, the Jebsen-Taylor Hand Function Test, the Box and Block Test, and the Nine Hole Peg Test. Twenty-three participants were further considered to investigate inter- and intra-rater reliability, standard error of measurement, and the minimal detectable change threshold of the app. Finally, participants were categorized according to motor impairment severity and the sensitivity of the app relative to these classifications was investigated.

RESULTS

Significant correlations, of variable strengths, were found between the measurements performed by the app and the clinical scales and tests. Variable reliability, ranging from moderate to excellent, was found for all app measurements. Exercises that involved tapping and maximum finger-pincer grasp were sensitive to motor impairment severity.

CONCLUSIONS

The convergent validity, reliability, and sensitivity to motor impairment severity of the app, especially of those exercises that involved tapping and the maximum extension of the fingers, together with the widespread availability of the app, could support the use of this and similar apps to complement conventional clinical assessments of hand function after stroke.

Towards a Platform for Robot-Assisted Minimally-Supervised Therapy of Hand Function: Design and Pilot Usability Evaluation

BACKGROUND

Robot-assisted therapy can increase therapy dose after stroke, which is often considered insufficient in clinical practice and after discharge, especially with respect to hand function. Thus far, there has been a focus on rather complex systems that require therapist supervision. To better exploit the potential of robot-assisted therapy, we propose a platform designed for minimal therapist supervision, and present the preliminary evaluation of its immediate usability, one of the main and frequently neglected challenges for real-world application. Such an approach could help increase therapy dose by allowing the training of multiple patients in parallel by a single therapist, as well as independent training in the clinic or at home.

METHODS

We implemented design changes on a hand rehabilitation robot, considering aspects relevant to enabling minimally-supervised therapy, such as new physical/graphical user interfaces and two functional therapy exercises to train hand motor coordination, somatosensation and memory. Ten participants with chronic stroke assessed the usability of the platform and reported the perceived workload during a single therapy session with minimal supervision. The ability to independently use the platform was evaluated with a checklist.

RESULTS

Participants were able to independently perform the therapy session after a short familiarization period, requiring assistance in only 13.46 (7.69-19.23)% of the tasks. They assigned good-to-excellent scores on the System Usability Scale to the user-interface and the exercises [85.00 (75.63-86.88) and 73.75 (63.13-83.75) out of 100, respectively]. Nine participants stated that they would use the platform frequently. Perceived workloads lay within desired workload bands. Object grasping with simultaneous control of forearm pronosupination and stiffness discrimination were identified as the most difficult tasks.

DISCUSSION

Our findings demonstrate that a robot-assisted therapy device can be rendered safely and intuitively usable upon first exposure with minimal supervision through compliance with usability and perceived workload requirements. The preliminary usability evaluation identified usability challenges that should be solved to allow real-world minimally-supervised use. Such a platform could complement conventional therapy, allowing to provide increased dose with the available resources, and establish a continuum of care that progressively increases therapy lead of the patient from the clinic to the home.

Improving motor function after chronic stroke by interactive gaming with a redesigned MR-compatible hand training device

New rehabilitation strategies enabled by technological developments are challenging the prevailing concept of there being a limited window for functional recovery after stroke. In this study, we examined the utility of a robot-assisted therapy used in combination with a serious game as a rehabilitation and motor assessment tool in patients with chronic stroke. We evaluated 928 game rounds from 386 training sessions of 8 patients who had suffered an ischemic stroke affecting middle cerebral artery territory that incurred at least 6 months prior. Motor function was assessed with clinical motor scales, including the Fugl-Meyer upper extremity (FM UE) scale, Action Research Arm Test, Modified Ashworth scale and the Box and Blocks test. Robotic device output measures (mean force, force-position correlation) and serious game score elements (collisions, rewards and total score) were calculated. A total of 2 patients exhibited a marginal improvement after a 10-week training protocol according to the FM UE scale and an additional patient exhibited a significant improvement according to Box and Blocks test. Motor scales showed strong associations of robotic device parameters and game metrics with clinical motor scale scores, with the strongest correlations observed for the mean force (0.677<Ρ<0.869), followed by the number of collisions (-0.670<Ρ<-0.585). Linear regression analysis showed that these indices were independent predictors of motor scale scores. In conclusion, a robotic device linked to a serious game can be used by patients with chronic stroke and induce at least some clinical improvements in motor performance. Robotic device output parameters and game score elements associate strongly with clinical motor scales and have the potential to be used as predictors in models of rehabilitation progress.

Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation

Enhancing patients' engagement is of great benefit for neural rehabilitation. However, physiological and neurological differences among individuals can cause divergent responses to the same task, and the responses can further change considerably during training; both of these factors make engagement enhancement a challenge. This challenge can be overcome by training task optimization based on subjects' responses. To this end, an engagement enhancement method based on human-in-the-loop optimization is proposed in this paper. Firstly, an interactive speed-tracking riding game is designed as the training task in which four reference speed curves (RSCs) are designed to construct the reference trajectory in each generation. Each RSC is modeled using a piecewise function, which is determined by the starting velocity, transient time, and end velocity. Based on the parameterized model, the difficulty of the training task, which is a key factor affecting the engagement, can be optimized. Then, the objective function is designed with consideration to the tracking accuracy and the surface electromyogram (sEMG)-based muscle activation, and the physical and physiological responses of the subjects can consequently be evaluated simultaneously. Moreover, a covariance matrix adaption evolution strategy, which is relatively tolerant of both measurement noises and human adaptation, is used to generate the optimal parameters of the RSCs periodically. By optimization of the RSCs persistently, the objective function can be maximized, and the subjects' engagement can be enhanced. Finally, the performance of the proposed method is demonstrated by the validation and comparison experiments. The results show that both subjects' sEMG-based motor engagement and electroencephalography based neural engagement can be improved significantly and maintained at a high level.

Robotic Rehabilitation: An Opportunity to Improve Cognitive Functions in Subjects With Stroke. An Explorative Study

Background: After a stroke, up to three-quarters of acute and subacute stroke survivors exhibit cognitive impairment, with a significant impact on functional recovery, quality of life, and social engagement. Robotic therapy has shown its effectiveness on motor recovery, but its effectiveness on cognitive recovery has not fully investigated. Objective: This study aims to assess the impact of a technological rehabilitation intervention on cognitive functions in patients with stroke, using a set of three robots and one sensor-based device for upper limb rehabilitation. Methods: This is a pilot study in which 51 patients were enrolled. An upper limb rehabilitation program was performed using three robots and one sensor-based device. The intervention comprised motor/cognitive exercises, especially selected among the available ones to train also cognitive functions. Patients underwent 30 rehabilitation sessions, each session lasting 45 minutes, 5 days a week. Patients were assessed before and after the treatment with several cognitive tests (Oxford Cognitive Scale, Symbol Digit Modalities Test, Digit Span, Rey-Osterrieth Complex Figure, Tower of London, and Stroop test). In addition, motor (Fugl-Meyer Assessment and Motricity Index) and disability (modified Barthel Index) scales were used. Results: According to the Oxford Cognitive Scale domains, a significant percentage of patients exhibited cognitive deficits. Excluding perception (with only one patient impaired), the domain with the lowest percentage of patients showing a pathological score was praxis (about 25%), while the highest percentage of impaired patients was found in calculation (about 70%). After the treatment, patients improved in all the investigated cognitive domains, as measured by the selected cognitive assessment scales. Moreover, motor and disability scales confirmed the efficacy of robotics on upper limb rehabilitation in patients with stroke. Conclusions: This explorative study suggests that robotic technology can be used to combine motor and cognitive exercises in a unique treatment session. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT04164381.

Multiplayer Interaction Platform With Gaze Tracking for Individuals With Autism

Deficits in interpersonal communication along with difficulty in putting oneself into the shoes of others characterizes individuals with Autism Spectrum Disorder (ASD). Additionally, they exhibit atypical looking pattern causing them to miss aspects related to understanding other's preference for a context that is crucial for effective social communication. Prior research studies show the use of multiplayer platforms can improve interaction among these individuals. However, these multiplayer platforms do not demand players to understand each other's preference, important for effective social interaction. In this work, we have developed a multiplayer interaction platform using virtual reality augmented with eye-tracking technology. Thirty-six participants comprising of individuals with ASD (n = 18; Group_ASD) and typically developing (TD) individuals (n = 18; Group_TD) interacted in pairs within each participant group using our platform. Results indicate that both Group_ASD and Group_TD showed improvement in performance across the tasks with the Group_TD performing better than the Group_ASD. Additionally, the eye-gaze data indicated an underlying relationship between one's looking pattern and task performance that was differentiated between the Group_ASD and Group_TD. The current results indicate a potential of our multiplayer interaction platform to serve as a complementary tool in the hands of the interventionist promoting social reciprocity and interaction among individuals with ASD.

Neurocognitive robot-assisted rehabilitation of hand function: a randomized control trial on motor recovery in subacute stroke

Background

Hand function is often impaired after stroke, strongly affecting the ability to perform daily activities. Upper limb robotic devices have been developed to complement rehabilitation therapy offered to persons who suffered a stroke, but they rarely focus on the training of hand sensorimotor function. The primary goal of this study was to evaluate whether robot-assisted therapy of hand function following a neurocognitive approach (i.e., combining motor training with somatosensory and cognitive tasks) produces an equivalent decrease in upper limb motor impairment compared to dose-matched conventional neurocognitive therapy, when embedded in the rehabilitation program of inpatients in the subacute stage after stroke.

Methods

A parallel-group, randomized controlled trial was conducted on subjects with subacute stroke receiving either conventional or robot-assisted neurocognitive hand therapy using a haptic device. Therapy was provided for 15, 45-min sessions over four weeks, nested within the standard therapy program. Primary outcome was the change from baseline in the upper extremity part of the Fugl-Meyer Assessment (FMA-UE) after the intervention, which was compared between groups using equivalence testing. Secondary outcome measures included upper limb motor, sensory and cognitive assessments, delivered therapy dose, as well as questionnaires on user technology acceptance.

Results

Thirty-three participants with stroke were enrolled. 14 subjects in the robot-assisted and 13 subjects in the conventional therapy group completed the study. At the end of intervention, week 8 and week 32, the robot-assisted/conventional therapy group improved by 7.14/6.85, 7.79/7.31, and 8.64/8.08 points on the FMA-UE, respectively, establishing that motor recovery in the robot-assisted group is non-inferior to that in the control group.

Conclusions

Neurocognitive robot-assisted therapy of hand function allows for a non-inferior motor recovery compared to conventional dose-matched neurocognitive therapy when performed during inpatient rehabilitation in the subacute stage. This allows the early familiarization of subjects with stroke to the use of such technologies, as a first step towards minimal therapist supervision in the clinic, or directly at home after hospital discharge, to help increase the dose of hand therapy for persons with stroke.

Trial registration

EUDAMED database (CIV-13-02-009921), clinicaltrials.gov (NCT02096445). Registered 26 March 2014 – Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02096445

Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study

BACKGROUND

In the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches.

METHODS

Here, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients' motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training.

RESULTS

The results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual.

CONCLUSIONS

The results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings. Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).

Method for Muscle Tone Monitoring During Robot-Assisted Therapy of Hand Function: A Proof of Concept

Robot-assisted rehabilitation of hand function is becoming an established approach to complement conventional therapy after stroke, particularly in view of its possible unsupervised use to promote an increase in therapy dose. Given their intensive therapy regime, robots may promote a temporary increase in hand muscle tone and spasticity, which may cause pain and negatively affect recovery. To integrate hand muscle tone monitoring into an assessment-driven robot-assisted therapy concept, an online assessment of muscle tone is proposed and incorporated into an exercise. The exercise was preliminarily tested in a pilot study with five chronic stroke survivors (non-spastic at rest) and five healthy participants to identify the range of potential physiological muscle tone change that can happen also in a non-spastic population during a single exercise session. In both groups, the muscle tone level during hand opening was higher in fast 20 mm ramp-and-hold perturbations (150 ms) compared to slow (250 ms) perturbations, and corresponded to a force change of approximately 4-5 N. Despite not being statistically significantly different, in the stroke group the force change (and the speed dependency) increased with exercise time. This information could serve as a basis to develop strategies to continuously adapt the difficulty and activity level required in robot-assisted rehabilitation and to monitor or even control the muscle tone evolution over time.

Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review

BACKGROUND

With advances in technology, the adoption of wearable devices has become a viable adjunct in poststroke rehabilitation. Upper limb (UL) impairment affects up to 77% of stroke survivors impacting on their ability to carry out everyday activities. However, despite an increase in research exploring these devices for UL rehabilitation, little is known of their effectiveness.

OBJECTIVE

This review aimed to assess the effectiveness of UL wearable technology for improving activity and participation in adult stroke survivors.

METHODS

Randomized controlled trials (RCTs) and randomized comparable trials of UL wearable technology for poststroke rehabilitation were included. Primary outcome measures were validated measures of activity and participation as defined by the International Classification of Functioning, Disability, and Health. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, and the Cochrane Library. The Cochrane Risk of Bias Tool was used to assess the methodological quality of the RCTs and the Downs and Black Instrument for the quality of non RCTs.

RESULTS

In the review, we included 11 studies with collectively 354 participants at baseline and 323 participants at final follow-up including control groups and participants poststroke. Participants' stroke type and severity varied. Only 1 study found significant between-group differences for systems functioning and activity (P≤.02). The 11 included studies in this review had small sample sizes ranging from 5 to 99 participants at an average (mean) age of 57 years.

CONCLUSIONS

This review has highlighted a number of reasons for insignificant findings in this area including low sample sizes and the appropriateness of the methodology for complex interventions. However, technology has the potential to measure outcomes, provide feedback, and engage users outside of clinical sessions. This could provide a platform for motivating stroke survivors to carry out more rehabilitation in the absence of a therapist, which could maximize recovery.

TRIAL REGISTRATION

PROSPERO CRD42017057715; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=57715.

Virtual reality-based balance training system augmented with operant conditioning paradigm

Background

Stroke-related sensory and motor deficits often steal away the independent mobility and balance from stroke survivors. Often, this compels the stroke survivors to rely heavily on their non-paretic leg during weight shifting to execute activities of daily living (ADL), with reduced usage of the paretic leg. Increased reliance on non-paretic leg often leads to learned nonuse of the paretic leg. Therefore, it is necessary to measure the contribution of individual legs toward one’s overall balance. In turn, techniques can be developed to condition the usage of both the legs during one’s balance training, thereby encouraging the hemiplegic patients for increased use of their paretic leg. The aim of this study is to (1) develop a virtual reality (VR)-based balance training platform that can estimate the contribution of each leg during VR-based weight-shifting tasks in an individualized manner and (2) understand the implication of operant conditioning paradigm during balance training on the overall balance of hemiplegic stroke patients.

Result

Twenty-nine hemiplegic patients participated in a single session of VR-based balance training. The participants maneuvered virtual objects in the virtual environment using two Wii Balance Boards that measured displacement in the center of pressure (CoP) due to each leg when one performed weight-shifting tasks. For operant conditioning, the weight distribution across both the legs was conditioned (during normal trial) to reward participants for increased usage of the paretic leg during the weight-shifting task. The participants were offered multiple levels of normal trials with intermediate catch trial (with equal weight distribution between both legs) in an individualized manner. The effect of operant conditioning during the normal trials was measured in the following catch trials. The participants showed significantly improved performance in the final catch trial compared to their initial catch trial task. Also, the enhancement in CoP displacement of the paretic leg was significant in the final catch trial compared to the initial catch trial.

Conclusion

The developed system was able to encourage participants for improved usage of their paretic leg during weight-shifting tasks. Such an approach has the potential to address the issue of learned nonuse of the paretic leg in stroke patients.

Effects of Transcranial Direct Current Stimulation (tDCS) Combined With Wrist Robot-Assisted Rehabilitation on Motor Recovery in Subacute Stroke Patients: A Randomized Controlled Trial

Both transcranial direct current stimulation (tDCS) and wrist robot-assisted training have demonstrated to be promising approaches for stroke rehabilitation. However, the effects of the combination of the two treatments in subacute stroke patients are not clear yet. To investigate the effectiveness of combining tDCS and wrist robot-assisted rehabilitation in subacute stroke patients in comparison with the wrist robotic training only, a single-blind, randomized, sham-controlled trial was performed with 40 subacute stroke patients (25 ± 7 days from stroke onset time). Patients were randomly assigned to experimental group (EG, n = 20 ) where patients receive real tDCS [2 mA, 20 min, and the anodal electrode on the primary motor cortex-M1-area of the affected hemisphere (C3/C4 in the 10-20 EEG system and the cathodal electrode on the contralateral orbit bone)] or control group (CG, n = 20 ) where patients receive sham tDCS (5 s) during wrist robotic rehabilitation training. The effects of the treatment were evaluated by means of the upper extremity, shoulder-elbow, and wrist subsections of the Fugl-Meyer assessment scale, Modified Ashworth Scale, Motricity Index and Box and Block Test together with kinematic parameters. One out of 20 patients in the CG did not complete the treatment. All the clinical outcome measures except the Modified Ashworth Scale showed a significant increase after the treatment in both groups. However, no significant difference in the average changes after treatment between groups was observed. The movement velocity and smoothness showed significant increases after the training, even though no significant difference between groups was observed. The combination of wrist robot-assisted training and tDCS did not show additional effects in comparison with wrist robot-assisted training only in subacute stroke patients. The negative results found in this paper are specific for the specific intervention. The timing of delivering the tDCS and the robot-assisted therapy has to be deeply investigated to enhance the effectiveness of the training.

Design and Characterization of a Robotic Device for the Assessment of Hand Proprioceptive, Motor, and Sensorimotor Impairments

Hand function is often impaired after neurological injuries such as stroke. In order to design patient-specific rehabilitation, it is essential to quantitatively assess those deficits. Current clinical scores cannot provide the required level of detail, and most assessment devices have been developed for the proximal joints of the upper limb. This paper presents a new robotic platform for the assessment of proprioceptive, motor, and sensorimotor hand impairments. A detailed technical evaluation demonstrated the capabilities to render different haptic environments required for a comprehensive assessment battery, and showed that the device is suitable for human interaction due to its ergonomic design. A preliminary study on proprioceptive assessment using a gauge position matching task with one healthy, one stroke, and one multiple sclerosis subject showed that the robotic system is able to rapidly and sensitively quantify proprioceptive deficits, and has the potential to be integrated into the clinical settings.

Kinect-Assisted Performance-Sensitive Upper Limb Exercise Platform for Post-stroke Survivors

One's ability to use upper limbs is critical for performing activities of daily living necessary for enjoying quality community life. However, after stroke, such abilities becomes adversely affected and it often deprives one of their capability to perform tasks that need coordinated movement in the upper limbs. To address issues with upper limb dysfunction, patients typically undergo rehabilitative exercises. Given the high patient to doctor ratio particularly in developing countries like India, conventional rehabilitation with patients undergoing exercises under one-on-one therapist's supervision often becomes a challenge. Thus, investigators are exploring technology such as computer-based platforms coupled with cameras that can alleviate the need for the continuous presence of a therapist and can offer a powerful complementary tool in the hands of the clinicians. Such marker-based imaging systems used for rehabilitation can offer real-time processing and high accuracy of data. However, these systems often require dedicated lab space and high set-up time. Often this is very expensive and suffers from portability issues. Investigators have been exploring marker-less imaging techniques e.g., Kinect integrated computer-based graphical user interfaces in stroke-rehabilitation such as tracking one's limb movement during rehabilitation. In our present study, we have developed a Kinect-assisted computer-based system that offered Human Computer Interaction (HCI) tasks of varying challenge levels. Execution of the tasks required one to use reaching and coordination skills of the upper limbs. Also, the system was Performance-sensitive i.e., adaptive to the individualized residual movement ability of one's upper limb quantified in terms of task performance score. We tested for the usability of our system by exposing 15 healthy participants to our system. Subsequently, seven post-stroke patients interacted with our system over a few sessions spread over 2 weeks. Also, we studied patient's mean tonic activity corresponding to the HCI tasks as a possible indicator of one's post-stroke functional recovery suggesting its potential of our system to serve as a rehabilitation platform. Our results indicate the potential of such systems toward the improvement of task performance capability of post-stroke patients with possibilities of upper limb movement rehabilitation.

Haptic Error Modulation Outperforms Visual Error Amplification When Learning a Modified Gait Pattern

Robotic algorithms that augment movement errors have been proposed as promising training strategies to enhance motor learning and neurorehabilitation. However, most research effort has focused on rehabilitation of upper limbs, probably because large movement errors are especially dangerous during gait training, as they might result in stumbling and falling. Furthermore, systematic large movement errors might limit the participants' motivation during training. In this study, we investigated the effect of training with novel error modulating strategies, which guarantee a safe training environment, on motivation and learning of a modified asymmetric gait pattern. Thirty healthy young participants walked in the exoskeletal robotic system Lokomat while performing a foot target-tracking task, which required an increased hip and knee flexion in the dominant leg. Learning the asymmetric gait pattern with three different strategies was evaluated: (i) No disturbance: no robot disturbance/guidance was applied, (ii) haptic error amplification: unsafe and discouraging large errors were limited with haptic guidance, while haptic error amplification enhanced awareness of small errors relevant for learning, and (iii) visual error amplification: visually observed errors were amplified in a virtual reality environment. We also evaluated whether increasing the movement variability during training by adding randomly varying haptic disturbances on top of the other training strategies further enhances learning. We analyzed participants' motor performance and self-reported intrinsic motivation before, during and after training. We found that training with the novel haptic error amplification strategy did not hamper motor adaptation and enhanced transfer of the practiced asymmetric gait pattern to free walking. Training with visual error amplification, on the other hand, increased errors during training and hampered motor learning. Participants who trained with visual error amplification also reported a reduced perceived competence. Adding haptic disturbance increased the movement variability during training, but did not have a significant effect on motor adaptation, probably because training with haptic disturbance on top of visual and haptic error amplification decreased the participants' feelings of competence. The proposed novel haptic error modulating controller that amplifies small task-relevant errors while limiting large errors outperformed visual error augmentation and might provide a promising framework to improve robotic gait training outcomes in neurological patients.

Hand-Exoskeleton Assisted Progressive Neurorehabilitation using Impedance Adaptation based Challenge Level Adjustment Method

This paper presents an underactuated design of a robotic hand exoskeleton and a challenge based neurorehabilitation strategy. The exoskeleton is designed to reproduce natural human fingertip paths during extension and grasping, keeping minimal kinematic complexity. It facilitates an impedance adaptation based trigged assistance control strategy by a switching between active non-assist and passive assistance modes. In active non-assist mode, the exoskeleton motion follows the applied fingertip forces based on an impedance model. If the applied fingertip forces are inadequate, the passive assistance mode is triggered. The impedance parameters are updated at regular intervals based on the user performance, to implement a challenge based rehabilitation strategy. A six-week long hand therapy, conducted on four chronic stroke patients results in significant (p-value<0.05) increase in force generation capacity and decrease (p-value<0.05) in the required assistance. Also, there was a significant (p-value<0.05) increase in the system impedance parameters which adequately challenged the patients. The change in the Action-Research-Arm-Test (ARAT) scores from baseline are also found to be significant (p-value<0.05) and beyond the minimal clinically important difference (MCID) limit. Thus the results prove that the proposed control strategy with has the potential to be a clinically effective solution for personalized rehabilitation of poststroke hand functionality.

Wrist Robot-assisted Rehabilitation Treatment in Subacute and Chronic Stroke Patients: from Distal to Proximal Motor Recovery

In this study, the recovery of proximal and distal segments in stroke patients who received distal training alone was investigated. Forty (20 subacute and 20 chronic) stroke patients were recruited to perform wrist robot-assisted rehabilitation training. The upper extremity, shoulder-elbow and wrist subsections of the Fugl-Meyer Assessment Scale were used to assess the motor recovery of distal and proximal segments. In addition, the Modified Ashworth Scale, the Motricity Index and the Box & Block test were used as clinical outcome measures together with kinematic parameters to evaluate the effects of the training. Significant increases in the wrist and shoulder-elbow subsections of the Fugl-Meyer Assessment Scale, Motricity Index and Box & Block test were found in both groups. Average changes in shoulder-elbow and upper extremity subsections of the Fugl-Meyer Assessment Scale in the subacute group (6.10 ± 6.60 and 15.65 ± 14.04) were significantly higher (p < 0.05) than those in the chronic group (2.30 ± 2.76 and 6.60 ± 4.64). In addition, significant increases in the movement velocity, movement smoothness and movement quality were observed in the subacute group. Our findings provide evidence that following a robot-assisted rehabilitation treatment there is a distal-to-proximal generalization in subacute stroke patients.

Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective

The past decades have seen rapid and vast developments of robots for the rehabilitation of sensorimotor deficits after damage to the central nervous system (CNS). Many of these innovations were technology-driven, limiting their clinical application and impact. Yet, rehabilitation robots should be designed on the basis of neurophysiological insights underlying normal and impaired sensorimotor functions, which requires interdisciplinary collaboration and background knowledge.

Recovery of sensorimotor function after CNS damage is based on the exploitation of neuroplasticity, with a focus on the rehabilitation of movements needed for self-independence. This requires a physiological limb muscle activation that can be achieved through functional arm/hand and leg movement exercises and the activation of appropriate peripheral receptors. Such considerations have already led to the development of innovative rehabilitation robots with advanced interaction control schemes and the use of integrated sensors to continuously monitor and adapt the support to the actual state of patients, but many challenges remain. For a positive impact on outcome of function, rehabilitation approaches should be based on neurophysiological and clinical insights, keeping in mind that recovery of function is limited. Consequently, the design of rehabilitation robots requires a combination of specialized engineering and neurophysiological knowledge. When appropriately applied, robot-assisted therapy can provide a number of advantages over conventional approaches, including a standardized training environment, adaptable support and the ability to increase therapy intensity and dose, while reducing the physical burden on therapists. Rehabilitation robots are thus an ideal means to complement conventional therapy in the clinic, and bear great potential for continued therapy and assistance at home using simpler devices.

This review summarizes the evolution of the field of rehabilitation robotics, as well as the current state of clinical evidence. It highlights fundamental neurophysiological factors influencing the recovery of sensorimotor function after a stroke or spinal cord injury, and discusses their implications for the development of effective rehabilitation robots. It thus provides insights on essential neurophysiological mechanisms to be considered for a successful development and clinical inclusion of robots in rehabilitation.

Algorithm for improving psychophysical threshold estimates by detecting sustained inattention in experiments using PEST

Psychophysical procedures are applied in various fields to assess sensory thresholds. During experiments, sampled psychometric functions are usually assumed to be stationary. However, perception can be altered, for example by loss of attention to the presentation of stimuli, leading to biased data, which results in poor threshold estimates. The few existing approaches attempting to identify non-stationarities either detect only whether there was a change in perception, or are not suitable for experiments with a relatively small number of trials (e.g., [Formula: see text] 300). We present a method to detect inattention periods on a trial-by-trial basis with the aim of improving threshold estimates in psychophysical experiments using the adaptive sampling procedure Parameter Estimation by Sequential Testing (PEST). The performance of the algorithm was evaluated in computer simulations modeling inattention, and tested in a behavioral experiment on proprioceptive difference threshold assessment in 20 stroke patients, a population where attention deficits are likely to be present. Simulations showed that estimation errors could be reduced by up to 77% for inattentive subjects, even in sequences with less than 100 trials. In the behavioral data, inattention was detected in 14% of assessments, and applying the proposed algorithm resulted in reduced test-retest variability in 73% of these corrected assessments pairs. The novel algorithm complements existing approaches and, besides being applicable post hoc, could also be used online to prevent collection of biased data. This could have important implications in assessment practice by shortening experiments and improving estimates, especially for clinical settings.

Usability evaluation of low-cost virtual reality hand and arm rehabilitation games

The emergence of lower-cost motion tracking devices enables home-based virtual reality rehabilitation activities and increased accessibility to patients. Currently, little documentation on patients' expectations for virtual reality rehabilitation is available. This study surveyed 10 people with stroke for their expectations of virtual reality rehabilitation games. This study also evaluated the usability of three lower-cost virtual reality rehabilitation games using a survey and House of Quality analysis. The games (kitchen, archery, and puzzle) were developed in the laboratory to encourage coordinated finger and arm movements. Lower-cost motion tracking devices, the P5 Glove and Microsoft Kinect, were used to record the movements. People with stroke were found to desire motivating and easy-to-use games with clinical insights and encouragement from therapists. The House of Quality analysis revealed that the games should be improved by obtaining evidence for clinical effectiveness, including clinical feedback regarding improving functional abilities, adapting the games to the user's changing functional ability, and improving usability of the motion-tracking devices. This study reports the expectations of people with stroke for rehabilitation games and usability analysis that can help guide development of future games.

Quantitative assessment of paretic limb dexterity and interlimb coordination during bilateral arm rehabilitation training

In neuro-rehabilitation after stroke, the conventional constrained induced movement therapy (CIMT) has been well-accepted. Existing bilateral trainings are mostly on mirrored symmetrical motion. However, complementary bilateral movements are dominantly involved in activities of daily living (ADLs), and functional bilateral therapies may bring better skill transfer from trainings to daily life. Neurophysiological evidence is also growing. In this work, we firstly introduce our bilateral arm training system realized with a haptic interface and a motion sensor, as well as the tasks that have been designed to train both the manipulation function of the paretic arm and coordination of bilateral upper limbs. Then, we propose quantitative measures for functional assessment of complementary bilateral training performance, including kinematic behavior indices, smoothness, submovement and bimanual coordination. After that, we describe the experiments with healthy subjects and the results with respect to these quantitative measures. Feasibility and sensitivity of the proposed indices were evaluated through comparison of unilateral and bilateral training outcomes. The proposed bilateral training system and tasks, as well as the quantitative measures, have been demonstrated effective for training and assessment of unilateral and bilateral arm functions.

Virtual Reality-Based Center of Mass-Assisted Personalized Balance Training System

Poststroke hemiplegic patients often show altered weight distribution with balance disorders, increasing their risk of fall. Conventional balance training, though powerful, suffers from scarcity of trained therapists, frequent visits to clinics to get therapy, one-on-one therapy sessions, and monotony of repetitive exercise tasks. Thus, technology-assisted balance rehabilitation can be an alternative solution. Here, we chose virtual reality as a technology-based platform to develop motivating balance tasks. This platform was augmented with off-the-shelf available sensors such as Nintendo Wii balance board and Kinect to estimate one’s center of mass (CoM). The virtual reality-based CoM-assisted balance tasks (Virtual CoMBaT) was designed to be adaptive to one’s individualized weight-shifting capability quantified through CoM displacement. Participants were asked to interact with Virtual CoMBaT that offered tasks of varying challenge levels while adhering to ankle strategy for weight shifting. To facilitate the patients to use ankle strategy during weight-shifting, we designed a heel lift detection module. A usability study was carried out with 12 hemiplegic patients. Results indicate the potential of our system to contribute to improving one’s overall performance in balance-related tasks belonging to different difficulty levels.

Evaluation Results of an Ontology-based Design Model of Virtual Environments for Upper Limb Motor Rehabilitation of Stroke Patients

OBJECTIVES

1) To enhance the content of an ontology for designing virtual environments (VEs) for upper limb motor rehabilitation of stroke patients according to the suggestions and comments of rehabilitation specialists and software developers, 2) to characterize the perceived importance level of the ontology, 3) to determine the perceived usefulness of the ontology, and 4) to identify the safety characteristics of the ontology for VEs design according to the rehabilitation specialists.

METHODS

Using two semi-structured Web questionnaires, we asked six rehabilitation specialists and six software developers to provide us with their perception regarding the level of importance and the usability of the ontology. From their responses we have identified themes related to perceived and required safety characteristics of the ontology.

RESULTS

Significant differences in the importance level were obtained for the Stroke Disability, VE Configuration, Outcome Measures, and Safety Calibration classes, which were perceived as highly important by rehabilitation specialists. Regarding usability, the ontology was perceived by both groups with high usefulness, ease of use, learnability and intention of use. Concerning the thematic analysis of recommendations, eight topics for safety characteristics of the ontology were identified: adjustment of therapy strategies; selection and delimitation of movements; selection and proper calibration of the interaction device; proper selection of measuring instruments; gradual modification of the difficulty of the exercise; adaptability and variability of therapy exercises; feedback according to the capabilities of the patient; and real-time support for exercise training.

CONCLUSIONS

The rehabilitation specialists and software developers confirmed the importance of the information contained in the ontology regarding motor rehabilitation of the upper limb. Their recommendations highlight the safety features and the advantages of the ontology as a guide for the effective design of VEs.

Closed-Loop Task Difficulty Adaptation during Virtual Reality Reach-to-Grasp Training Assisted with an Exoskeleton for Stroke Rehabilitation

Stroke patients with severe motor deficits of the upper extremity may practice rehabilitation exercises with the assistance of a multi-joint exoskeleton. Although this technology enables intensive task-oriented training, it may also lead to slacking when the assistance is too supportive. Preserving the engagement of the patients while providing “assistance-as-needed” during the exercises, therefore remains an ongoing challenge. We applied a commercially available seven degree-of-freedom arm exoskeleton to provide passive gravity compensation during task-oriented training in a virtual environment. During this 4-week pilot study, five severely affected chronic stroke patients performed reach-to-grasp exercises resembling activities of daily living. The subjects received virtual reality feedback from their three-dimensional movements. The level of difficulty for the exercise was adjusted by a performance-dependent real-time adaptation algorithm. The goal of this algorithm was the automated improvement of the range of motion. In the course of 20 training and feedback sessions, this unsupervised adaptive training concept led to a progressive increase of the virtual training space (p < 0.001) in accordance with the subjects' abilities. This learning curve was paralleled by a concurrent improvement of real world kinematic parameters, i.e., range of motion (p = 0.008), accuracy of movement (p = 0.01), and movement velocity (p < 0.001). Notably, these kinematic gains were paralleled by motor improvements such as increased elbow movement (p = 0.001), grip force (p < 0.001), and upper extremity Fugl-Meyer-Assessment score from 14.3 ± 5 to 16.9 ± 6.1 (p = 0.026). Combining gravity-compensating assistance with adaptive closed-loop feedback in virtual reality provides customized rehabilitation environments for severely affected stroke patients. This approach may facilitate motor learning by progressively challenging the subject in accordance with the individual capacity for functional restoration. It might be necessary to apply concurrent restorative interventions to translate these improvements into relevant functional gains of severely motor impaired patients in activities of daily living.

Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton

Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation and antigravity assistance augments upper limb function and brain activity during rehabilitation exercises and may thus provide a novel restorative framework for severely affected stroke patients.

Closed-Loop Neuroprosthesis for Reach-to-Grasp Assistance: Combining Adaptive Multi-channel Neuromuscular Stimulation with a Multi-joint Arm Exoskeleton

Stroke patients with severe motor deficits cannot execute task-oriented rehabilitation exercises with their affected upper extremity. Advanced rehabilitation technology may support them in performing such reach-to-grasp movements. The challenge is, however, to provide assistance as needed, while maintaining the participants' commitment during the exercises. In this feasibility study, we introduced a closed-loop neuroprosthesis for reach-to-grasp assistance which combines adaptive multi-channel neuromuscular stimulation with a multi-joint arm exoskeleton. Eighteen severely affected chronic stroke patients were assisted by a gravity-compensating, seven-degree-of-freedom exoskeleton which was attached to the paretic arm for performing reach-to-grasp exercises resembling activities of daily living in a virtual environment. During the exercises, adaptive electrical stimulation was applied to seven different muscles of the upper extremity in a performance-dependent way to enhance the task-oriented movement trajectory. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. Closed-loop neuromuscular stimulation could be well integrated into the exoskeleton-based training, and increased the task-related range of motion (p = 0.0004) and movement velocity (p = 0.015), while preserving accuracy. The highest relative stimulation intensity was required to facilitate the grasping function. The facilitated range of motion correlated with the upper extremity Fugl-Meyer Assessment score of the patients (p = 0.028). Combining adaptive multi-channel neuromuscular stimulation with antigravity assistance amplifies the residual motor capabilities of severely affected stroke patients during rehabilitation exercises and may thus provide a customized training environment for patient-tailored support while preserving the participants' engagement.

Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation

Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

Characterization of Artifacts Produced by Gel Displacement on Non-invasive Brain-Machine Interfaces during Ambulation

So far, Brain-Machine Interfaces (BMIs) have been mainly used to study brain potentials during movement-free conditions. Recently, due to the emerging concern of improving rehabilitation therapies, these systems are also being used during gait experiments. Under this new condition, the evaluation of motion artifacts has become a critical point to assure the validity of the results obtained. Due to the high signal to noise ratio provided, the use of wet electrodes is a widely accepted technic to acquire electroencephalographic (EEG signals). To perform these recordings it is necessary to apply a conductive gel between the scalp and the electrodes. This work is focused on the study of gel displacements produced during ambulation and how they affect the amplitude of EEG signals. Data recorded during three ambulation conditions (gait training) and one movement-free condition (BMI motor imagery task) are compared to perform this study. Two phenomenons, manifested as unusual increases of the signals' amplitude, have been identified and characterized during this work. Results suggest that they are caused by abrupt changes on the conductivity between the electrode and the scalp due to gel displacement produced during ambulation and head movements. These artifacts significantly increase the Power Spectral Density (PSD) of EEG recordings at all frequencies from 5 to 90 Hz, corresponding to the main bandwidth of electrocortical potentials. They should be taken into consideration before performing EEG recordings in order to asses the correct gel allocation and to avoid the use of electrodes on certain scalp areas depending on the experimental conditions.