Robotic neurorehabilitation: a computational motor learning perspective

iP3T: an interpretable multimodal time-series model for enhanced gait phase prediction in wearable exoskeletons

Introduction

Wearable exoskeletons assist individuals with mobility impairments, enhancing their gait and quality of life. This study presents the iP3T model, designed to optimize gait phase prediction through the fusion of multimodal time-series data.

Methods

The iP3T model integrates data from stretch sensors, inertial measurement units (IMUs), and surface electromyography (sEMG) to capture comprehensive biomechanical and neuromuscular signals. The model's architecture leverages transformer-based attention mechanisms to prioritize crucial data points. A series of experiments were conducted on a treadmill with five participants to validate the model's performance.

Results

The iP3T model consistently outperformed traditional single-modality approaches. In the post-stance phase, the model achieved an RMSE of 1.073 and an R2 of 0.985. The integration of multimodal data enhanced prediction accuracy and reduced metabolic cost during assisted treadmill walking.

Discussion

The study highlights the critical role of each sensor type in providing a holistic understanding of the gait cycle. The attention mechanisms within the iP3T model contribute to its interpretability, allowing for effective optimization of sensor configurations and ultimately improving mobility and quality of life for individuals with gait impairments.

Considerations for developing complex post-stroke upper limb behavioural interventions: An international qualitative study

OBJECTIVE

To simultaneously explore the perspectives and opinions of different invested participant groups on the important considerations for development of upper limb behavioural interventions that drive optimal post-stroke upper limb motor recovery.

DESIGN

A qualitative descriptive study in a constructivist epistemology.

PARTICIPANTS

Purposively selected participant groups (preclinical research n = 9, clinical research n = 9, clinical experience n = 9 and lived experience n = 10).

SETTING

Research participants were selected from top internationally published authors. Experiential participants were recruited internationally, through networks.

RESULTS

Four themes were identified with embedded subthemes. Theme 1: 'Clinical relevance should be the core of a "good" research question' with two subthemes: 'Breaking down silos: forging interdisciplinary research teams', and 'Beyond the pipeline: bench to bedside and back'; theme 2: 'Balance restitution and compensation to maximise outcomes' with three subthemes: 'Good outcome: going beyond an outcome measure', 'Recovery is a puzzle: measure all the pieces', and 'Optimising capacity: knowing when and how'; theme 3: 'Stroke demands personalised solutions' with two subthemes: 'Condition-specific considerations', and 'Person-specific considerations'; theme 4: 'Upper limb recovery requires complex interventions' with four subthemes: 'Fuelling engagement', 'Content is crucial', 'Multidimensional dose', and 'Therapist sway'.

CONCLUSIONS

This study suggests that post-stroke upper limb motor interventions are the interactions of multiple intervention elements (e.g. dose and content) shaped by different contextual considerations (e.g. stroke and personal factors). Development of such interventions may need to consider both content and context of the intervention to drive optimal recovery.

Combining robotics and functional electrical stimulation for assist-as-needed support of leg movements in stroke patients: A feasibility study

PURPOSE

Rehabilitation technology can be used to provide intensive training in the early phases after stroke. The current study aims to assess the feasibility of combining robotics and functional electrical stimulation (FES), with an assist-as-needed approach to support actively-initiated leg movements in (sub-)acute stroke patients.

METHOD

Nine subacute stroke patients performed repetitions of ankle dorsiflexion and/or knee extension movements, with and without assistance. The assist-as-needed algorithm determined the amount and type of support needed per repetition. The number of repetitions and range of motion with and without assistance were compared with descriptive statistics. Fatigue scores were obtained using the visual analogue scale (score 0-10).

RESULTS

Support was required in 44 % of the repetitions for ankle dorsiflexion and in 5 % of the repetitions of knee extension, The median fatigue score was 2.0 (IQR: 0.2) and 4.0 (IQR: 1.5) for knee and ankle, respectively, indicating mild to moderate perceived fatigue.

CONCLUSION

This study demonstrated the feasibility of assist-as-needed assistance through combined robotic and FES support of leg movements in stroke patients. It proved particularly useful for ankle dorsiflexion. Future research should focus on implementing this approach in a clinical setting, to assess clinical applicability and potential effects on leg function.

Effects of virtual reality-based robot therapy combined with task-oriented therapy on upper limb function and cerebral cortex activation in patients with stroke

BACKGROUND

This study aimed to investigate the effects of virtual reality (VR)-based robot therapy combined with task-oriented therapy on cerebral cortex activation and upper limb function in patients with stroke.

METHODS

This study included 46 patients with hemiplegia within 1 year of stroke onset. Patients were divided into an experimental group (n = 23) and a control group (n = 23) using a computer randomization program. The experimental group received VR-based robot and task-oriented therapies, whereas the control group received only task-oriented therapy. All participants received interventions for 40 minutes per session, 5 times a week, for 8 weeks. For the pre- and post-evaluation of all participants, the Fugl-Meyer Assessment for the upper extremity, manual function test, motor activity log, and Jebsen-Taylor Hand Function Test were used to evaluate changes in upper limb function and motor-evoked potential amplitudes were measured to compare cerebral cortex activation.

RESULTS

In comparison to the control group, experimental group demonstrated an improvement in the function of the upper limb (P < .01) and activation of the cerebral cortex (P < .01).

CONCLUSION

The combined intervention of VR-based robot and task-oriented therapies is valuable for improving upper limb function and cerebral cortex activation in patients with stroke.

Digital Technology Enablers of Tele-Neurorehabilitation in Pre- and Post-COVID-19 Pandemic Era - A Scoping Review

Neurorehabilitation (NR), a major component of neurosciences, is the process of restoring a patient's damaged/disorganized neurological function, through training, therapy, and education, while focusing on patient's independence and well-being. Since the advent of the COVID-19 pandemic, various applications of telecare and telehealth services surged drastically and became an integral part of current clinical practices. Tele-Neurorehabilitation (TNR) is one of such applications. When rehabilitation services were disrupted globally due to lockdown and travel restrictions, the importance of TNR was recognized, especially in developed, low, and middle-income countries. With exponential deployment of telehealth interventions in neurosciences, TNR has become a distinct stand-alone sub-specialty of neurosciences and telehealth. Digital technologies, such as wearables, robotics, and Virtual Reality (VR) have enabled TNR to improve the quality of patients' lives. Providing NR remotely using digital technologies and customized digital devices is now a reality, and likely to be the new norm soon. This article provides an overview of the needs, utilization, and deployment of TNR, and focuses on digital technology enablers of TNR in pre- and post-COVID-19 pandemic era.

Clinical indications and protocol considerations for selecting initial body weight support levels in gait rehabilitation: a systematic review

BACKGROUND

Body weight support (BWS) training devices are frequently used to improve gait in individuals with neurological impairments, but guidance in selecting an appropriate level of BWS is limited. Here, we aim to describe the initial BWS levels used during gait training, the rationale for this selection and the clinical goals aligned with BWS training for different diagnoses.

METHOD

A systematic literature search was conducted in PubMed, Embase and Web of Science, including terms related to the population (individuals with neurological disorders), intervention (BWS training) and outcome (gait). Information on patient characteristics, type of BWS device, BWS level and training goals was extracted from the included articles.

RESULTS

Thirty-three articles were included, which described outcomes using frame-based (stationary or mobile) and unidirectional ceiling-mounted devices on four diagnoses (multiple sclerosis (MS), spinal cord injury (SCI), stroke, traumatic brain injury (TBI)). The BWS levels were highest for individuals with MS (median: 75%, IQR: 6%), followed by SCI (median: 40%, IQR: 35%), stroke (median: 30%, IQR: 4.75%) and TBI (median: 15%, IQR: 0%). The included studies reported eleven different training goals. Reported BWS levels ranged between 30 and 75% for most of the training goals, without a clear relationship between BWS level, diagnosis, training goal and rationale for BWS selection. Training goals were achieved in all included studies.

CONCLUSION

Initial BWS levels differ considerably between studies included in this review. The underlying rationale for these differences was not clearly motivated in the included studies. Variation in study designs and populations does not allow to draw a conclusion on the effectiveness of BWS levels. Hence, it remains difficult to formulate guidelines on optimal BWS settings for different diagnoses, BWS devices and training goals. Further efforts are required to establish clinical guidelines and to experimentally investigate which initial BWS levels are optimal for specific diagnoses and training goals.

Robot-assisted support combined with electrical stimulation for the lower extremity in stroke patients: a systematic review

Objective. The incidence of stroke rising, leading to an increased demand for rehabilitation services. Literature has consistently shown that early and intensive rehabilitation is beneficial for stroke patients. Robot-assisted devices have been extensively studied in this context, as they have the potential to increase the frequency of therapy sessions and thereby the intensity. Robot-assisted systems can be combined with electrical stimulation (ES) to further enhance muscle activation and patient compliance. The objective of this study was to review the effectiveness of ES combined with all types of robot-assisted technology for lower extremity rehabilitation in stroke patients.Approach. A thorough search of peer-reviewed articles was conducted. The quality of the included studies was assessed using a modified version of the Downs and Black checklist. Relevant information regarding the interventions, devices, study populations, and more was extracted from the selected articles.Main results. A total of 26 articles were included in the review, with 23 of them scoring at least fair on the methodological quality. The analyzed devices could be categorized into two main groups: cycling combined with ES and robots combined with ES. Overall, all the studies demonstrated improvements in body function and structure, as well as activity level, as per the International Classification of Functioning, Disability, and Health model. Half of the studies in this review showed superiority of training with the combination of robot and ES over robot training alone or over conventional treatment.Significance. The combination of robot-assisted technology with ES is gaining increasing interest in stroke rehabilitation. However, the studies identified in this review present challenges in terms of comparability due to variations in outcome measures and intervention protocols. Future research should focus on actively involving and engaging patients in executing movements and strive for standardization in outcome values and intervention protocols.

NSF DARE-Transforming modeling in neurorehabilitation: Four threads for catalyzing progress

We present an overview of the Conference on Transformative Opportunities for Modeling in Neurorehabilitation held in March 2023. It was supported by the Disability and Rehabilitation Engineering (DARE) program from the National Science Foundation's Engineering Biology and Health Cluster. The conference brought together experts and trainees from around the world to discuss critical questions, challenges, and opportunities at the intersection of computational modeling and neurorehabilitation to understand, optimize, and improve clinical translation of neurorehabilitation. We organized the conference around four key, relevant, and promising Focus Areas for modeling: Adaptation & Plasticity, Personalization, Human-Device Interactions, and Modeling 'In-the-Wild'. We identified four common threads across the Focus Areas that, if addressed, can catalyze progress in the short, medium, and long terms. These were: (i) the need to capture and curate appropriate and useful data necessary to develop, validate, and deploy useful computational models (ii) the need to create multi-scale models that span the personalization spectrum from individuals to populations, and from cellular to behavioral levels (iii) the need for algorithms that extract as much information from available data, while requiring as little data as possible from each client (iv) the insistence on leveraging readily available sensors and data systems to push model-driven treatments from the lab, and into the clinic, home, workplace, and community. The conference archive can be found at (dare2023.usc.edu). These topics are also extended by three perspective papers prepared by trainees and junior faculty, clinician researchers, and federal funding agency representatives who attended the conference.

Analysis of Motor Learning Principles Applied in Tasks or Motor Skills Trained by Stroke Patients

Objective:

To analyze the principles applied to promote and evaluate motor learning in tasks or motor skills trained by stroke patients.

Methods:

Articles were included if they used motor learning principles in tasks or motor skills trained by stroke patients.

Results:

Twelve studies were included in this review. Quality was good for the included studies. Articles used motor learning principle based on practice (N = 12), repetitive training (N = 9), and feedback (N = 5).

Conclusions:

There are different motor learning principles to promote and evaluate motor learning in stroke patients. These findings could guide clinicians during training of tasks or motor skills.

Responsiveness to exoskeleton loading during bimanual reaching is associated with corticospinal tract integrity in stroke

Background

Device-based rehabilitation of upper extremity impairment following stroke often employs one-sized-fits-all approaches that do not account for individual differences in patient characteristics.

Objective

Determine if corticospinal tract lesion load could explain individual differences in the responsiveness to exoskeleton loading of the arms in chronic stroke participants.

Methods

Fourteen stroke participants performed a bimanual shared cursor reaching task in virtual reality while exoskeletons decreased the effective weight of the more-impaired arm and increased the effective weight of the less-impaired arm. We calculated the change in relative displacement between the arms (RC) and the change in relative muscle activity (MC) between the arms from the biceps and deltoids. We calculated corticospinal tract lesion load (wCSTLL) in a subset of 10 participants.

Results

Exoskeleton loading did not change RC (p = 0.07) or MC (p = 0.47) at the group level, but significant individual differences emerged. Participants with little overlap between the lesion and corticospinal tract responded to loading by decreasing muscle activity in the more-impaired arm relative to the less-impaired arm. The change in deltoid MC was associated with smaller wCSTLL (R2 = 0.43, p = 0.039); there was no such relationship for biceps MC (R2 < 0.001, p = 0.98).

Conclusion

Here we provide evidence that corticospinal tract integrity is a critical feature that determines one's ability to respond to upper extremity exoskeleton loading. Our work contributes to the development of personalized device-based interventions that would allow clinicians and researchers to titrate constraint levels during bimanual activities.

Effects of an assist-as-needed equipped Tenodesis-Induced-Grip Exoskeleton Robot (TIGER) on upper limb function in patients with chronic stroke

BACKGROUND

The original version of the Tenodesis-Induced-Grip Exoskeleton Robot (TIGER) significantly improved the motor and functional performance of the affected upper extremity of chronic stroke patients. The assist-as-needed (AAN) technique in robot-involved therapy is widely favored for promoting patient active involvement, thereby fostering motor recovery. However, the TIGER lacked an AAN control strategy, which limited its use in different clinical applications. The present study aimed to develop and analyze the training effects of an AAN control mode to be integrated into the TIGER, to analyze the impact of baseline patient characteristics and training paradigms on outcomes for individuals with chronic stroke and to compare training effects on the upper limb function between using the AAN-equipped TIGER and using the original prototype.

METHODS

This was a single-arm prospective interventional study which was conducted at a university hospital. In addition to 20 min of regular task-specific motor training, each participant completed a 20-min robotic training program consisting of 10 min in the AAN control mode and 10 min in the functional mode. The training sessions took place twice a week for 9 weeks. The primary outcome was the change score of the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE), and the secondary outcomes were the change score of the Box and Blocks Test (BBT), the amount of use (AOU) and quality of movement (QOM) scales of the Motor Activity Log (MAL), the Semmes-Weinstein Monofilament (SWM) test, and the Modified Ashworth Scale (MAS) for fingers and wrist joints. The Generalized Estimating Equations (GEE) and stepwise regression model were used as the statistical analysis methods.

RESULTS

Sixteen chronic stroke patients completed all steps of the study. The time from stroke onset to entry into the trial was 21.7 ± 18.9 months. After completing the training with the AAN-equipped TIGER, they exhibited significant improvements in movement reflected in their total score (pre/post values were 34.6 ± 11.5/38.5 ± 13.4) and all their sub-scores (pre/post values were 21.5 ± 6.0/23.3 ± 6.5, 9.5 ± 6.2/11.3 ± 7.2, and 3.6 ± 1.0/3.9 ± 1.0 for the shoulder, elbow, and forearm sub-category, the wrist and hand sub-category, and the coordination sub-category, respectively) on the FMA-UE (GEE, p < 0.05), as well as their scores on the BBT (pre/post values were 5.9 ± 6.5/9.5 ± 10.1; GEE, p = 0.004) and the AOU (pre/post values were 0.35 ± 0.50/0.48 ± 0.65; GEE, p = 0.02). However, the original TIGER exhibited greater improvements in their performance on the FMA-UE than the participants training with the AAN-equipped TIGER (GEE, p = 0.008). The baseline score for the wrist and hand sub-category of the FMA-UE was clearly the best predictor of TIGER-mediated improvements in hand function during the post-treatment assessment (adjusted R2 = 0.282, p = 0.001).

CONCLUSIONS

This study developed an AAN-equipped TIGER system and demonstrated its potential effects on improving both the function and activity level of the affected upper extremity of patients with stroke. Nevertheless, its training effects were not found to be advantageous to the original prototype. The baseline score for the FMA-UE sub-category of wrist and hand was the best predictor of improvements in hand function after TIGER rehabilitation. Clinical trial registration ClinicalTrials.gov, identifier NCT03713476; date of registration: October19, 2018. https://clinicaltrials.gov/ct2/show/NCT03713476.

Effect of 3-Dimensional Robotic Therapy Combined with Electromyography-Triggered Neuromuscular Electrical Stimulation on Upper Limb Function and Cerebral Cortex Activation in Stroke Patients: A Randomized Controlled Trial

(1) Background: This study investigated the effect of 3-dimensional robotic therapy (RT) combined with electromyography-triggered neuromuscular electrical stimulation (RT-ENMES) on stroke patients' upper-limb function and cerebral cortex activation. (2) Methods: Sixty-one stroke patients were assigned randomly to one of three groups. The stroke patients were in the subacute stage between 2 and 6 months after onset. The three groups received 20 min of RT and 20 min of electromyography-triggered neuromuscular electrical stimulation (ENMES) in the RT-ENMES group (n = 21), 40 min of RT in the RT group (n = 20), and 40 min of ENMES in the ENMES group (n = 20). The treatments were for 40 min, 5 days per week, and for 8 weeks. Upper-extremity function was evaluated using the Fugl-Meyer assessment for upper extremity (FMA-UE), Wolf motor function test, and action research arm test (ARAT); cerebral cortex activation and motor-evoked potential (MEP) amplitude were evaluated before and after the study. (3) Results: The analysis showed significant changes in all evaluation items for all three groups in the before-and-after comparisons. Significant changes were observed in the FMA-UE, ARAT, and MEP; in the posttest, the RT-ENMES group showed more significant changes in the FMA-UE, ARAT, and MEP than the other two groups. (4) Conclusions: The study analysis suggests that RT-ENMES effectively improves upper-limb function and cerebral cortex activation in patients with stroke.

Scoping Review on Brain-Computer Interface-Controlled Electrical Stimulation Interventions for Upper Limb Rehabilitation in Adults: A Look at Participants, Interventions, and Technology

Purpose

While current rehabilitation practice for improving arm and hand function relies on physical/occupational therapy, a growing body of research evaluates the effects of technology-enhanced rehabilitation. We review interventions that combine a brain-computer interface (BCI) with electrical stimulation (ES) for upper limb movement rehabilitation to summarize the evidence on (1) populations of study participants, (2) BCI-ES interventions, and (3) the BCI-ES systems.

Method

After searching seven databases, two reviewers identified 23 eligible studies. We consolidated information on the study participants, interventions, and approaches used to develop integrated BCI-ES systems. The included studies investigated the use of BCI-ES interventions with stroke and spinal cord injury (SCI) populations. All studies used electroencephalography to collect brain signals for the BCI, and functional electrical stimulation was the most common type of ES. The BCI-ES interventions were typically conducted without a therapist, with sessions varying in both frequency and duration.

Results

Of the 23 eligible studies, only 3 studies involved the SCI population, compared to 20 involving individuals with stroke.

Conclusions

Future BCI-ES interventional studies could address this gap. Additionally, standardization of device and rehabilitation modalities, and study-appropriate involvement with therapists, can be considered to advance this intervention towards clinical implementation.

Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke

BACKGROUND

Individualized, targeted, and intense training is the hallmark of successful gait rehabilitation in people post-stroke. Specifically, increasing use of the impaired ankle to increase propulsion during the stance phase of gait has been linked to higher walking speeds and symmetry. Conventional progressive resistance training is one method used for individualized and intense rehabilitation, but often fails to target paretic ankle plantarflexion during walking. Wearable assistive robots have successfully assisted ankle-specific mechanisms to increase paretic propulsion in people post-stroke, suggesting their potential to provide targeted resistance to increase propulsion, but this application remains underexamined in this population. This work investigates the effects of targeted stance-phase plantarflexion resistance training with a soft ankle exosuit on propulsion mechanics in people post-stroke.

METHODS

We conducted this study in nine individuals with chronic stroke and tested the effects of three resistive force magnitudes on peak paretic propulsion, ankle torque, and ankle power while participants walked on a treadmill at their comfortable walking speeds. For each force magnitude, participants walked for 1 min while the exosuit was inactive, 2 min with active resistance, and 1 min with the exosuit inactive, in sequence. We evaluated changes in gait biomechanics during the active resistance and post-resistance sections relative to the initial inactive section.

RESULTS

Walking with active resistance increased paretic propulsion by more than the minimal detectable change of 0.8 %body weight at all tested force magnitudes, with an average increase of 1.29 ± 0.37 %body weight at the highest force magnitude. This improvement corresponded to changes of 0.13 ± 0.03 N m kg- 1 in peak biological ankle torque and 0.26 ± 0.04 W kg- 1 in peak biological ankle power. Upon removal of resistance, propulsion changes persisted for 30 seconds with an improvement of 1.49 ± 0.58 %body weight after the highest resistance level and without compensatory involvement of the unresisted joints or limb.

CONCLUSIONS

Targeted exosuit-applied functional resistance of paretic ankle plantarflexors can elicit the latent propulsion reserve in people post-stroke. After-effects observed in propulsion highlight the potential for learning and restoration of propulsion mechanics. Thus, this exosuit-based resistive approach may offer new opportunities for individualized and progressive gait rehabilitation.

Quantitative Assessment of Upper Limb Movement in Post-Stroke Adults for Identification of Sensitive Measures in Reaching and Lifting Activities

BACKGROUND

The assumption of this work is the achievement of objective results of the movement structure, which forms the basis for in-depth analysis and, consequently, for determining the upper limb movements that are most affected by stroke compared to healthy people.

METHODS

An analysis of relevant and systematically identified features of upper limb movement in post-stroke adults is presented based on scalable hypothesis tests. The basic features were calculated using movements defined by the x, y, and z coordinates (i.e., 3D trajectory time series) and compared to the results of post-stroke patients with healthy controls of similar age.

RESULTS

After automatic feature selection, out of the 1004 common features of upper limb movement, the most differentiated were the upper arm movements in reaching kinematics. In terms of movement type, movements in the frontal plane (shoulder abduction and adduction) were the most sensitive to changes. The largest number of discriminating features was determined on the basis of acceleration time series.

CONCLUSIONS

In the 3D assessment of functional activities of the upper limb, the upper arm turned out to be the most differentiated body segment, especially during abduction and adduction movements. The results indicate a special need to pay attention to abduction and adduction movements to improve the activities of daily living of the upper limbs after a stroke.

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).

Real-time auditory feedback may reduce abnormal movements in patients with chronic stroke

PURPOSE

The current pilot study assesses the use of real-time auditory feedback to help reduce abnormal movements during an active reaching task in patients with chronic stroke.

MATERIALS AND METHODS

20 patients with chronic stroke completed the study with full datasets (age: M = 53 SD = 14; sex: male = 75%; time since stroke in months: M = 34, SD = 33). Patients undertook 100 repetitions of an active reaching task while listening to self-selected music which automatically muted when abnormal movement was detected, determined by thresholds set by clinical therapists. A within-subject design with two conditions (with auditory feedback vs. without auditory feedback) presented in a randomised counterbalanced order was used. The dependent variable was the duration of abnormal movement as a proportion of trial duration.

RESULTS

A significant reduction in the duration of abnormal movement was observed when patients received auditory feedback, F(1,18) = 9.424, p = 0.007, with a large effect size (partial η2 = 0.344).

CONCLUSIONS

Patients with chronic stroke can make use of real-time auditory feedback to increase the proportion of time they spend in optimal movement patterns. The approach provides a motivating framework that encourages high dose with a key focus on quality of movement. Trial Registration: ISRCTN12969079 https://www.isrctn.com/ISRCTN12969079 ISRTCN trial registration REF: ISRCTN12969079IMPLICATIONS FOR REHABILITATIONMovement quality during upper limb rehabilitation should be targeted as part of a well-balanced rehabilitation programme.Auditory feedback is a useful tool to help patients with chronic stroke reduce compensatory movements.

[Hand robotic devices in neurorehabilitation: A systematic review on the feasibility and effectiveness of stroke rehabilitation]

Robot-assisted therapy is a relatively new intervention, increasingly used in the rehabilitation treatment of stroke patients. It allows to increase the number of repetitions in the performance of specific tasks movements. For this review, a search was carried out between August and October 2021 in the PubMed, Web of Science, Scopus, Cochrane, PEDro and OTseeker databases, selecting a total of six randomized controlled trials where robot-assisted hand therapy was used in stroke rehabilitation. Studies agree that robot-assisted hand therapy has benefits in all phases of stroke rehabilitation that translate into motor and functional improvements of the upper limb and improvements in hemispatial neglect.

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.

Naturalistic visualization of reaching movements using head-mounted displays improves movement quality compared to conventional computer screens and proves high usability

BACKGROUND

The relearning of movements after brain injury can be optimized by providing intensive, meaningful, and motivating training using virtual reality (VR). However, most current solutions use two-dimensional (2D) screens, where patients interact via symbolic representations of their limbs (e.g., a cursor). These 2D screens lack depth cues, potentially deteriorating movement quality and increasing cognitive load. Head-mounted displays (HMDs) have great potential to provide naturalistic movement visualization by incorporating improved depth cues, reduce visuospatial transformations by rendering movements in the space where they are performed, and preserve eye-hand coordination by showing an avatar-with immersive VR (IVR)-or the user's real body-with augmented reality (AR). However, elderly populations might not find these novel technologies usable, hampering potential motor and cognitive benefits.

METHODS

We compared movement quality, cognitive load, motivation, and system usability in twenty elderly participants (>59 years old) while performing a dual motor-cognitive task with different visualization technologies: IVR HMD, AR HMD, and a 2D screen. We evaluated participants' self-reported cognitive load, motivation, and usability using questionnaires. We also conducted a pilot study with five brain-injured patients comparing the visualization technologies while using an assistive device.

RESULTS

Elderly participants performed straighter, shorter duration, and smoother movements when the task was visualized with the HMDs than screen. The IVR HMD led to shorter duration movements than AR. Movement onsets were shorter with IVR than AR, and shorter for both HMDs than the screen, potentially indicating facilitated reaction times due to reduced cognitive load. No differences were found in the questionnaires regarding cognitive load, motivation, or usability between technologies in elderly participants. Both HMDs proved high usability in our small sample of patients.

CONCLUSIONS

HMDs are a promising technology to be incorporated into neurorehabilitation, as their more naturalistic movement visualization improves movement quality compared to conventional screens. HMDs demonstrate high usability, without decreasing participants' motivation, and might potentially lower cognitive load. Our preliminary clinical results suggest that brain-injured patients may especially benefit from more immersive technologies. However, larger patient samples are needed to draw stronger conclusions.*.

Performing a shortened version of the Action Research Arm Test in immersive virtual reality to assess post-stroke upper limb activity

BACKGROUND

To plan treatment and measure post-stroke recovery, frequent and time-bounded functional assessments are recommended. With increasing needs for neurorehabilitation advances, new technology based methods, such as virtual reality (VR) have emerged. Here, we developed an immersive VR version of the Action Research Arm Test (ARAT-VR) to complement neurorehabilitation.

OBJECTIVE

This study aimed to assess the validity, usability and test-retest reliability of the ARAT-VR among individuals with stroke, healthcare professionals and healthy control subjects (HCS).

METHODS

Among the 19 items of the ARAT, 13 items were selected and developed in immersive VR. 11 healthcare professionals, 30 individuals with stroke, and 25 HCS were recruited. Content validity was assessed by asking healthcare professionals to rate the difficulty of performing each item of the ARAT-VR in comparison to the classical Action Research Arm Test (ARAT-19). Concurrent validity was first measured using correlation (Spearman tests) between the ARAT-VR and ARAT-19 scores for the individuals with stroke, and second through correlation and comparison between the scores of the ARAT-VR and the reduced version of the ARAT (ARAT-13) for both individuals with stroke and HCS (Wilcoxon signed rank tests and Bland-Altman plots). Usability was measured using the System Usability Scale. A part of individuals with stroke and HCS were re-tested following a convenient delay to measure test-retest reliability (Intra-class correlation and Wilcoxon tests).

RESULTS

Regarding the content validity, median difficulty of the 13 ARAT-VR items (0[0 to - 1] to 0[0-1]) evaluated by healthcare professionals was rated as equivalent to the classical ARAT for all tasks except those involving the marbles. For these, the difficulty was rated as superior to the real tasks (1[0-1] when pinching with the thumb-index and thumb-middle fingers, and 1[0-2] when pinching with thumb-ring finger). Regarding the concurrent validity, for paretic hand scores, there were strong correlations between the ARAT-VR and ARAT-13 (r = 0.84), and between the ARAT-VR and ARAT-19 (r = 0.83). Usability (SUS = 82.5[75-90]) and test-retest reliability (ICC = 0.99; p < 0.001) were excellent.

CONCLUSION

The ARAT-VR is a valid, usable and reliable tool that can be used to assess upper limb activity among individuals with stroke, providing potential to increase assessment frequency, remote evaluation, and improve neurorehabilitation. Trial registration https://clinicaltrials.gov/ct2/show/NCT04694833 ; Unique identifier: NCT04694833, Date of registration: 11/24/2020.

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

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

A Motor Adaptation Model Assuming Update of Internal Model in the Motor Cortex

When considering the human motor-adaptation mechanism from the perspective of the motor control theory, updating the internal model constitutes a critical component. The learning curve at each trial of motion can be explained by a state-space model; however, the model cannot reproduce the time-series data for the hand’s position, velocity, and acceleration (motion profiles). There is no internal model-updating rule for optimal feedback control, a plausible model for reproducing motion profiles. In this paper, we propose an adaptation model that incorporates an internal model-updating rule which modeled after Hebb’s rule into optimal feedback control. Also, we examine the neural substrate of the internal model. To validate the proposed adaptation model, we conducted behavioral experiments with humans that reflected changes in the internal model and reproduced the changes in the internal model as well as the motion profiles using the proposed adaptation model. In addition, we analyzed the data for a visuomotor rotation task performed by a monkey and checked for changes in the output characteristics of neurons in the motor cortex before and after adaptation. According to the above-mentioned validation and analysis results, the motor cortex constitutes the neural substrate of the internal model.

Accurate Real-time Phase Estimation for Normal and Asymmetric Gait

An accurate real-time gait phase estimator for normal and asymmetric gait is developed by training and testing a time-delay neural network on gait data collected from six participants during treadmill walking. The trained model can generate smooth and highly accurate predictions of the gait phase with a root mean square error of less than 3.48% and 4.31% in normal and asymmetric gait, respectively. The coefficient of determination between the estimated and target phase is greater than 99% for all subjects with both normal and asymmetric gait. The proposed gait estimator also exhibits precise heel-strike event detection with an RMSE of 2.56% and 3.70% in normal and asymmetric gait, respectively. A spatial impedance controller is then employed and tested based on the estimated gait phase of a new participant. Obtained results confirm that the controller provided assistance in coordination with the user's motion both in normal and asymmetric gait conditions. The estimated gait phase is compared in the case of walking without and with the exoskeleton in passive and active modes, indicating persistent accuracy of the gait phase estimator regardless of the walking conditions.

Current trends in the treatment of patients with post-stroke unilateral spatial neglect: a scoping review

PURPOSE

The purpose of this scoping review was to explore the current treatment approaches for patients with post-stroke unilateral spatial neglect.

METHODS

A three-step search strategy using the Johanna Briggs Institute (JBI) guidelines, was undertaken. PubMed, CINAHL, The Cochrane Central Register of Controlled Trial, SCOPUS, PROSPERO, JBI, Sport Discus, and Google Scholar databases were searched. Searches were limited to publications from January 1, 2008, to May 1, 2020. Critical appraisal was undertaken by two independent reviewers using a standardized critical appraisal instrument developed by JBI. Data were extracted using a study-specific charting table.

RESULTS

A total of 3,648 articles were identified, 311 full-text articles were screened and 86 articles were critically appraised, with 83 articles included in the review. Intervention approaches for post-stroke unilateral spatial neglect symptom amelioration were identified and categorized as prism adaptation and visual scanning, mental practice and mirror therapy, electrical stimulation and robotics, combination therapy, pharmacological therapy, and other interventions. Both positive and negative results across identified interventions were identified without specific reference to the phase of recovery.

CONCLUSION

This review provides insight into current interventions for post-stroke unilateral spatial neglect. A plethora of intervention studies have been explored to ameliorate neglect symptoms post-stroke.IMPLICATION FOR REHABILITATIONPrism adaptation (PA) and combination therapy are most commonly investigated intervention for unilateral spatial neglect (USN) and showed promise in ameliorating USN symptoms.No single treatment approach seems optimally superior in the rehabilitation of USN post-stroke.Evidence for the selection of treatment at a specific phase of recovery is not conclusive as both positive and negative outcome on neglect measure were observed across all treatment approaches without specific reference to the phase of recovery.Evidence for the long-term use of PA in USN rehabilitation appears to be modest.

Towards functional robotic training: motor learning of dynamic tasks is enhanced by haptic rendering but hampered by arm weight support

Background

Current robot-aided training allows for high-intensity training but might hamper the transfer of learned skills to real daily tasks. Many of these tasks, e.g., carrying a cup of coffee, require manipulating objects with complex dynamics. Thus, the absence of somatosensory information regarding the interaction with virtual objects during robot-aided training might be limiting the potential benefits of robotic training on motor (re)learning. We hypothesize that providing somatosensory information through the haptic rendering of virtual environments might enhance motor learning and skill transfer. Furthermore, the inclusion of haptic rendering might increase the task realism, enhancing participants’ agency and motivation. Providing arm weight support during training might also enhance learning by limiting participants’ fatigue.

Methods

We conducted a study with 40 healthy participants to evaluate how haptic rendering and arm weight support affect motor learning and skill transfer of a dynamic task. The task consisted of inverting a virtual pendulum whose dynamics were haptically rendered on an exoskeleton robot designed for upper limb neurorehabilitation. Participants trained with or without haptic rendering and with or without weight support. Participants’ task performance, movement strategy, effort, motivation, and agency were evaluated during baseline, short- and long-term retention. We also evaluated if the skills acquired during training transferred to a similar task with a shorter pendulum.

Results

We found that haptic rendering significantly increases participants’ movement variability during training and the ability to synchronize their movements with the pendulum, which is correlated with better performance. Weight support also enhances participants’ movement variability during training and reduces participants’ physical effort. Importantly, we found that training with haptic rendering enhances motor learning and skill transfer, while training with weight support hampers learning compared to training without weight support. We did not observe any significant differences between training modalities regarding agency and motivation during training and retention tests.

Conclusion

Haptic rendering is a promising tool to boost robot-aided motor learning and skill transfer to tasks with similar dynamics. However, further work is needed to find how to simultaneously provide robotic assistance and haptic rendering without hampering motor learning, especially in brain-injured patients.

Trial registrationhttps://clinicaltrials.gov/show/NCT04759976

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-00993-w.

A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity

The effective decoding of movement from non-invasive electroencephalography (EEG) is essential for informing several therapeutic interventions, from neurorehabilitation robots to neural prosthetics. Deep neural networks are most suitable for decoding real-time data but their use in EEG is hindered by the gross classes of motor tasks in the currently available datasets, which are solvable even with network architectures that do not require specialized design considerations. Moreover, the weak association with the underlying neurophysiology limits the generalizability of modern networks for EEG inference. Here, we present a neurophysiologically interpretable 3-dimensional convolutional neural network (3D-CNN) that captured the spatiotemporal dependencies in brain areas that get co-activated during movement. The 3D-CNN received topography-preserving EEG inputs, and predicted complex components of hand movements performed on a plane using a back-drivable rehabilitation robot, namely (a) the reaction time (RT) for responding to stimulus (slow or fast), (b) the mode of movement (active or passive, depending on whether there was an assistive force provided by the apparatus), and (c) the orthogonal directions of the movement (left, right, up, or down). We validated the 3D-CNN on a new dataset that we acquired from an in-house motor experiment, where it achieved average leave-one-subject-out test accuracies of 79.81%, 81.23%, and 82.00% for RT, active vs. passive, and direction classifications, respectively. Our proposed method outperformed the modern 2D-CNN architecture by a range of 1.1% to 6.74% depending on the classification task. Further, we identified the EEG sensors and time segments crucial to the classification decisions of the network, which aligned well with the current neurophysiological knowledge on brain activity in motor planning and execution tasks. Our results demonstrate the importance of biological relevance in networks for an accurate decoding of EEG, suggesting that the real-time classification of other complex brain activities may now be within our reach.

Development and Electromyographic Validation of a Compliant Human-Robot Interaction Controller for Cooperative and Personalized Neurorehabilitation

BACKGROUND

Appropriate training modalities for post-stroke upper-limb rehabilitation are key features for effective recovery after the acute event. This study presents a cooperative control framework that promotes compliant motion and implements a variety of high-level rehabilitation modalities with a unified low-level explicit impedance control law. The core idea is that we can change the haptic behavior perceived by a human when interacting with the rehabilitation robot by tuning three impedance control parameters.

METHODS

The presented control law is based on an impedance controller with direct torque measurement, provided with positive-feedback compensation terms for disturbances rejection and gravity compensation. We developed an elbow flexion-extension experimental setup as a platform to validate the performance of the proposed controller to promote the desired high-level behavior. The controller was first characterized through experimental trials regarding joint transparency, torque, and impedance tracking accuracy. Then, to validate if the controller could effectively render different physical human-robot interaction according to the selected rehabilitation modalities, we conducted tests on 14 healthy volunteers and measured their muscular voluntary effort through surface electromyography (sEMG). The experiments consisted of one degree-of-freedom elbow flexion/extension movements, executed under six high-level modalities, characterized by different levels of (i) corrective assistance, (ii) weight counterbalance assistance, and (iii) resistance.

RESULTS

The unified controller demonstrated suitability to promote good transparency and render both compliant and stiff behavior at the joint. We demonstrated through electromyographic monitoring that a proper combination of stiffness, damping, and weight assistance could induce different user participation levels, render different physical human-robot interaction, and potentially promote different rehabilitation training modalities.

CONCLUSION

We proved that the proposed control framework could render a wide variety of physical human-robot interaction, helping the user to accomplish the task while exploiting physiological muscular activation patterns. The reported results confirmed that the control scheme could induce different levels of the subject's participation, potentially applicable to the clinical practice to adapt the rehabilitation treatment to the subject's progress. Further investigation is needed to validate the presented approach to neurological patients.

Human Weight Compensation With a Backdrivable Upper-Limb Exoskeleton: Identification and Control

Active exoskeletons are promising devices for improving rehabilitation procedures in patients and preventing musculoskeletal disorders in workers. In particular, exoskeletons implementing human limb’s weight support are interesting to restore some mobility in patients with muscle weakness and help in occupational load carrying tasks. The present study aims at improving weight support of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments, for design and validation purposes, are conducted on a total of 65 participants who performed posture maintenance and elbow flexion/extension movements. The introduction of joint misalignments in the weight support model significantly reduced the model errors, in terms of weight estimation, and enhanced the estimation reliability. The introduced control architecture reduced model tracking errors regardless of the condition. Weight support significantly decreased the activity of antigravity muscles, as expected, but increased the activity of elbow extensors because gravity is usually exploited by humans to accelerate a limb downwards. These findings suggest that an adaptive weight support controller could be envisioned to further minimize human effort in certain applications.

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

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

Motor learning in neurological rehabilitation

While most upper limb training interventions in neurological rehabilitation are based on established principles of motor learning and neural plasticity, recovery potential may be improved if the focus includes remediating an individual's specific motor impairment within the framework of a motor control theory. This paper reviews current theories of motor control and motor learning and describes how they can be incorporated into training programs to enhance sensorimotor recovery in patients with neurological lesions. An emphasis is placed on dynamical systems theory and the use of new technologies such as virtual, augmented and mixed reality applications for rehabilitation to facilitate learning.Implications for RehabilitationKinematic abundance allows the healthy nervous system to produce different combinations of joint rotations to perform a desired task.The structure of practice to improve the movement repertoire in rehabilitation should take into account the kinematic abundance of the system.Learning can be enhanced by varied practice with feedback about key movement elements.Virtual reality environments provide opportunities to manipulate the structure and schedule of practice and feedback.

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

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

Haptic Training: Which Types Facilitate (re)Learning of Which Motor Task and for Whom? Answers by a Review

The use of robots has attracted researchers to design numerous haptic training methods to support motor learning. However, investigations of new methods yielded inconclusive results regarding their effectiveness to enhance learning due to the diversity of tasks, haptic designs, participants' skill level, and study protocols. In this review, we developed a taxonomy to identify generalizable findings out of publications on haptic training. In the taxonomy, we grouped the results of studies on healthy learners based on participants' skill level and tasks' characteristics. Our inspection of included studies revealed that: i) Performance-enhancing haptic methods were beneficial for novices, ii) Training with haptics was as effective as training with other feedback modalities, and iii) Performance-enhancing and performance-degrading haptic methods were useful for the learning of temporal and spatial aspects, respectively. We also observed that these findings are in line with results from robot-aided neurorehabilitation studies on patients. Our review suggests that haptic training can be effective to foster learning, especially when the information cannot be provided with other feedback modalities. We believe the findings from the taxonomy constitute a general guide, which can assist researchers when designing studies to investigate the effectiveness of haptics on learning different tasks.

Clinical Test of a Wearable, High DOF, Spring Powered Hand Exoskeleton (HandSOME II)

In previous work, we developed an exoskeleton, Hand Spring Operated Movement Enhancer (HandSOME II), that allows movement at 15 hand degrees of freedom (DOF). Eleven separate elastic elements can be added to customize the extension assistance for individuals with impaired hand function. In this pilot study of twelve individuals with stroke, we measured the immediate improvements in range of motion (ROM) and upper extremity function when wearing the device. Index finger ROM was significantly improved at the PIP (p=.01) and DIP joints (p=.026), and the max extension was significantly increased at the MCP (p<.001), PIP (p=.013) and DIP joints (p=.016). The thumb CMC abduction max (p=.017) and CMC flexion/extension ROM also increased (p=.04). In a grip and release task involving various objects, six subjects were unable to complete the tasks without assistance. Across these 6 subjects, 13 of 42 tasks were completed without assistance, while 36 of 42 tasks were completed when wearing HandSOME II. Despite the extension assistance provided by the device, flexion grip force was not statistically decreased. HandSOME II can potentially increase the effectiveness of repetitive task practice in patients with moderate-severe hand impairment by allowing completion of grasp and release tasks that are impossible to complete unassisted.

Efficacy and Safety Study of Wearable Cyborg HAL (Hybrid Assistive Limb) in Hemiplegic Patients With Acute Stroke (EARLY GAIT Study): Protocols for a Randomized Controlled Trial

We hypothesized that gait treatment with a wearable cyborg Hybrid Assistive Limb (HAL) would improve the walking ability of patients with hemiparesis after stroke. This study aims to evaluate the efficacy and safety of gait treatment using HAL versus conventional gait training (CGT) in hemiplegic patients with acute stroke and establish a protocol for doctor-initiated clinical trials for acute stroke. We will enroll patients with acute stroke at the University of Tsukuba Hospital. This study is a single-center, randomized, parallel-group, controlled trial (HAL group, n = 20; control group, n = 20) that will include three phases: (1) pre-observation phase (patient enrollment, baseline assessment, and randomization); (2) treatment phase (nine sessions, twice or thrice per week over 3−4 weeks; the HAL and control groups will perform gait treatment using HAL or CGT, respectively, and finally (3) post-treatment evaluation phase. The Functional Ambulation Category score will be the primary outcome measure, and the following secondary outcome measures will be assessed: Mini-Mental State Examination, Brunnstrom recovery stage of lower limbs, Fugl–Meyer assessment of lower limbs, 6-min walking distance, comfortable gait speed, step length, cadence, Barthel Index, Functional Independence Measure, gait posture, motion analysis (muscle activity), amount of activity (evaluated using an activity meter), stroke-specific QOL, and modified Rankin Scale score. The baseline assessment, post-treatment evaluation, and follow-up assessment will evaluate the overall outcome measures; for other evaluations, physical function evaluation centered on walking will be performed exclusively, excluding ADL and QOL scores. This study is a randomized controlled trial that aims to clarify the efficacy and safety of gait treatment using HAL compared with CGT in hemiplegic patients with acute stroke. In addition, we aim to establish a protocol for doctor-initiated clinical trials for acute stroke based on the study results. If our results demonstrate the effectiveness of the proposed treatment regarding outcomes of patients with hemiplegic acute stroke, this study will promote the treatment of these patients using the HAL system as an effective tool in future stroke rehabilitation programs. The study protocol was registered with the Japan Registry of Clinical Trials on October 14, 2020 (jRCTs032200151).

Customizing Robot-Assisted Passive Neurorehabilitation Exercise Based on Teaching Training Mechanism

Passive movement is an important mean of rehabilitation for stroke survivors in the early stage or with greater paralysis. The upper extremity robot is required to assist therapists with passive movement during clinical rehabilitation, while customizing is one of the crucial issues for robot-assisted upper extremity training, which fits the patient-centeredness. Robot-assisted teaching training could address the need well. However, the existing control strategies of teaching training are usually commanded by position merely, having trouble to achieve the efficacy of treatment by therapists. And deficiency of flexibility and compliance comes to the training trajectory. This research presents a novel motion control strategy for customized robot-assisted passive neurorehabilitation. The teaching training mechanism is developed to coordinate the movement of the shoulder and elbow, ensuring the training trajectory correspondence with human kinematics. Furthermore, the motion trajectory is adjusted by arm strength to realize dexterity and flexibility. Meanwhile, the torque sensor employed in the human-robot interactive system identifies movement intention of human. The goal-directed games and feedbacks promote the motor positivity of stroke survivors. In addition, functional experiments and clinical experiments are investigated with a healthy adult and five recruited stroke survivors, respectively. The experimental results present that the suggested control strategy not only serves with safety training but also presents rehabilitation efficacy.

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

INTRODUCTION

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

METHODS AND ANALYSIS

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

PROSPERO REGISTRATION NUMBER

CRD42020205818.

ETHICS AND DISSEMINATION

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

Analysis of Gait Motion Changes by Intervention Using Robot Suit Hybrid Assistive Limb (HAL) in Myelopathy Patients After Decompression Surgery for Ossification of Posterior Longitudinal Ligament

Ossification of the posterior longitudinal ligament (OPLL) is a hyperostonic condition in which the posterior longitudinal ligament becomes thick and loses its flexibility, resulting in ectopic ossification and severe neurologic deficit (Matsunaga and Sakou, 2012). It commonly presents with myelopathy and radiculopathy and with myelopathy progression motor disorders and balance disorders can appear. Even after appropriate surgical decompression, some motor impairments often remain. The Hybrid Assistive Limb (HAL) is a wearable powered suit designed to assist and support the user's voluntary control of hip and knee joint motion by detecting bioelectric signals from the skin surface and force/pressure sensors in the shoes during movement. In the current study, the HAL intervention was applied to 15 patients diagnosed with OPLL who presented with myelopathy after decompression surgery (6 acute and 9 chronic stage). Following the HAL intervention, there were significant improvements in gait speed, cadence, stride length, in both acute and chronic groups. Joint angle analysis of the lower limbs showed that range of motion (ROM) of hip and knee joints in acute group, and also ROM of hip joint and toe-lift during swing in chronic group increased significantly. ROM of knee joint became closer to healthy gait in both groups. Electromyography analysis showed that hamstrings activity in the late swing phase increased significantly for acute patients. Immidiate effect from HAL session was also observed. EMG of vastus medialis were decreased except chronic 7th session and EMG of gastrocnemius were decreased except acute 7th session, which suggests the patients were learning to walk with lesser knee-hypertension during the sessions. After all, double knee action appeared in both acute and chronic groups after the HAL intervention, rather than knee hyper-extension which is a common gait impairment in OPLL. We consider that these improvements lead to a smoother and healthier gait motion.

An Identification-Based Method Improving the Transparency of a Robotic Upper Limb Exoskeleton

Over the past decade, research on human–robot collaboration has grown exponentially, motivated by appealing applications to improve the daily life of patients/operators. A primary requirement in many applications is to implement highly “transparent” control laws to reduce the robot impact on human movement. This impact may be quantified through relevant motor control indices. In this paper, we show that control laws based on careful identification procedures improve transparency compared to classical closed-loop position control laws. A new performance index based on the ratio between electromyographic activity and limb acceleration is also introduced to assess the quality of human exoskeleton interaction.

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.

[Modern opportunities and prognosis of physical rehabilitation of children with cerebral palsy]

OBJECTIVE

To evaluate the results of traditional and high-tech physical rehabilitation in cerebral palsy and in modeling of rehabilitation prognosis.

MATERIAL AND METHODS

One hundred and twenty-six patients with cerebral palsy (spastic diplegia); mean age 7.0±1.3 years, the duration of inpatient treatment 28 days, were studied. Forty patients received conventional treatment, 86 - a high-tech physical rehabilitation (robotic mechanic therapy with «Lokomat», «Armeo» and electric stimulation of the brain with «Brain-port» device).

RESULTS AND CONCLUSION

The advantage of more significant therapeutic effects of high-tech physical rehabilitation over traditional treatment is established. This effect consists in improving coordination and independent movement. On the basis of the regression analysis, mathematical models of the prognosis of the rehabilitation potential are constructed. High-tech physical rehabilitation has a significantly more pronounced therapeutic effect than traditional treatment.

Patient-Specific Robot-Assisted Stroke Rehabilitation Guided by EEG - A Feasibility Study

Multi-session robot-assisted stroke rehabilitation program requires patients to perform repetitive tasks. It is challenging for the patient to maintain concentration during training sessions. A novel intervention strategy using Electroencephalography (EEG) signals is proposed to maintain concentration during training by enhancing the engagement of stroke patients using robot-assisted multi-session rehabilitation. The approach is illustrated by applying it to one stroke patient undergoing 12 training sessions of hand motor training on the AMADEO rehabilitation device. AMADEO offers four modes of training programs of increased intensity comprising passive training, passive training with biofeedback, assistive training as well as active 2D training games. The EEG signals are measured over eight electrode sites: FC4, C4, CP4, FC3, C3, CP3, Cz, and CPz during each training day to extract movement-related cortical potential (MRCP) signals. Moreover, functional hand recovery parameters are determined using the AMADEO assessment tool. The patient's level of engagement is determined by the negative amplitude of the MRCP signal. The rehabilitation program is switched to a more intense training mode when a consistent decrease is observed in the negative amplitude of MRCP signals from the monitored electrodes. Using this approach, the rehabilitation program becomes patient-specific and adaptive. In addition, it is shown that each training mode exhibits a different recovery level of the affected hand and maximum recovery is achieved when MRCP signals indicate that the patient is actively participating in the training.

Treadmill-Based Locomotor Training With Robotic Pelvic Assist and Visual Feedback: A Feasibility Study

BACKGROUND AND PURPOSE

Gait asymmetries are common after stroke, and often persist despite conventional rehabilitation. Robots provide training at a greater practice frequency than conventional approaches. However, prior studies of have found the transfer of learned skills outside of the device to be inadequate. The tethered pelvic assist device (TPAD) promotes weight shifting, yet allows users to independently navigate spatiotemporal aspects of gait. The purpose of this study was to evaluate feasibility and preliminary efficacy of a 5-day intervention combining TPAD training with visual feedback and task-specific overground training to promote improved force and stance symmetry in individuals after stroke.

METHODS

After baseline assessments, 11 participants chronically after stroke received 1 hour of practice for 5 consecutive days. Training sessions included visual feedback during TPAD treadmill training followed by overground gait training. Safety, perceived exertion, and adherence were recorded as measures of feasibility. Load and stance symmetry were reassessed after the intervention (posttraining) and again 1 week later.

RESULTS

No adverse events were reported. Mean (SD) perceived exertion (3.61 (0.23)) was low and did not significantly change throughout the intervention. Overall adherence was 96.4%. Load asymmetry was not significantly reduced on the treadmill from baseline to posttraining (P = 0.075). Overground stance symmetry significantly improved on posttraining (F = 8.498, P = 0.002), but was not sustained at follow-up. (See the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A311, which summarizes the study background, methods, and results.) DISCUSSION AND CONCLUSIONS:: Results demonstrate this combined interventional approach was feasible and improved stance symmetry overground, yet further work should consider increasing training intensity and/or duration to induce gains lasting through follow-up.

A Review on Design of Upper Limb Exoskeletons

Exoskeleton robotics has ushered in a new era of modern neuromuscular rehabilitation engineering and assistive technology research. The technology promises to improve the upper-limb functionalities required for performing activities of daily living. The exoskeleton technology is evolving quickly but still needs interdisciplinary research to solve technical challenges, e.g., kinematic compatibility and development of effective human–robot interaction. In this paper, the recent development in upper-limb exoskeletons is reviewed. The key challenges involved in the development of assistive exoskeletons are highlighted by comparing available solutions. This paper provides a general classification, comparisons, and overview of the mechatronic designs of upper-limb exoskeletons. In addition, a brief overview of the control modalities for upper-limb exoskeletons is also presented in this paper. A discussion on the future directions of research is included.

Development of a Novel Robotic Rehabilitation System With Muscle-to-Muscle Interface

In this study, we developed a novel robotic system with a muscle-to-muscle interface to enhance rehabilitation of post-stroke patients. The developed robotic rehabilitation system was designed to provide patients with stage appropriate physical rehabilitation exercise and muscular stimulation. Unlike the position-based control of conventional bimanual robotic therapies, the developed system stimulates the activities of the target muscles, as well as the joint movements of the paretic limb. The robot-assisted motion and the electrical stimulation on the muscles of the paretic side are controlled by on-line comparison of the motion and the muscle activities between the paretic and unaffected sides. With the developed system, the rehabilitation exercise can be customized and modulated depending on the patient’s stage of motor recovery after stroke. The system can be operated in three different modes allowing both passive and active exercises. The effectiveness of the developed system was verified with healthy human subjects, where the subjects were paired to serve as the unaffected side and the paretic side of a hemiplegic patient.