Robot-assisted Therapy Research Articles

Robot-Assisted Therapy in Guillain–Barrè Syndrome: Systematic Review of Primary Evidence and Study Protocol for a Randomized Clinical Trial

Background: Guillain–Barré syndrome (GBS) is an immune-mediated polyradiculoneuropathy that represents a leading cause of motor impairment. Robot-assisted therapy (RAT) has been widely applied in various neurological conditions. However, the use of RAT in GBS remains underexplored. This systematic review (SR) aims to evaluate the preliminary evidence regarding the efficacy of RAT in terms of motor recovery in people with GBS (pwGBSs). Secondly, the study protocol for a randomized RCT is reported. Methods: A comprehensive SR was conducted on PubMed, Scopus, EMBASE, Cochrane Library, and Epistemikos. Risk of bias was assessed using the National Institute of Health (NIH) study quality assessment. The SR’s protocol was recorded in the PROSPERO database. Results: Out of 116 articles found, four studies published in the past four years met the inclusion criteria. These studies investigated the effects of RAT on lower limbs (three studies) and upper limbs (one study) in four pwGBSs. The results showed improvements in motor function and patient engagement, but it is impossible to generalize the findings. Conclusions: Our SRs supports the rationale for an RCT to assess the efficacy of RAT in pwGBSs. We present the protocol for a double-blind RCT to evaluate the effects of RAT on upper limb motor function in pwGBSs.

Advancements in Physiotherapy: The Role of Medical Devices in Enhancing Rehabilitation Outcomes – A Comprehensive Review

Physiotherapy has evolved significantly with the integration of medical devices, transforming traditional rehabilitation practices and improving patient outcomes. This review explores advancements in medical devices, such as robotic-assisted therapy, wearable technologies, and virtual reality, highlighting their applications in enhancing mobility, pain management, and recovery speed. The study synthesizes evidence from recent clinical trials and literature, discussing the benefits, challenges, and future potential of these technologies in physiotherapy. Emphasis is placed on their role in creating patient-specific rehabilitation plans and addressing barriers to adoption, including cost and accessibility. The findings underscore the need for innovative, cost-effective solutions to broaden the impact of these advancements globally.

Effects of robot-assisted hand function therapy on brain functional mechanisms: a synchronized study using fNIRS and sEMG.

Robot-assisted hand function therapy is pivotal in the rehabilitation of patients with stroke; however, its therapeutic mechanism remains elusive. Currently, research examining the impact of robot-assisted hand function therapy on brain function in patients with stroke is scarce, and there is a lack of studies investigating the correlation between muscle activity and alterations in brain function. This study aimed to investigate the correlation between forearm muscle movement and brain functional activation by employing the synchronized use of functional near-infrared spectroscopy and surface electromyography methods. Moreover, it sought to compare neural activity patterns during different rehabilitation tasks and refine the mechanism of robot-assisted hand function therapy for post-stroke hand function impairments. Stroke patients with hand dysfunction underwent three sessions of robot-assisted hand function therapy within 2 weeks to 3 months of onset. The fNIRS-sEMG synchronous technique was used to observe brain function and forearm muscle activation. Ten participants were randomly assigned to receive mirror, resistance, or passive rehabilitation training. During the intervention, cortical and muscle activation information was obtained using fNIRS and electromyographic signals. The primary outcomes included changes in oxyhemoglobin concentration and root mean square of surface electromyography. Compared to the resting state, the Oxy-Hb concentration in the brain regions involved in three rehabilitation tasks with robot-assisted hand function therapy significantly increased (p < 0.05). Mirror therapy significantly enhanced the prefrontal cortex and the superior frontal cortex activation levels. In contrast, resistance therapy significantly promoted the activation of the supplementary motor area and the premotor cortex. Passive rehabilitation tasks showed some activation in the target brain area premotor cortex region. Robot-assisted hand function therapy has shown that forearm muscle movement is closely related to oxygenated hemoglobin concentration activity in specific brain regions during different rehabilitation tasks. The simultaneous sEMG-fNIRS study found a significant correlation between muscle movement and brain activity after stroke, which provides an important basis for understanding the treatment mechanism of hand function impairment.

Research trends and hotspots of post-stroke upper limb dysfunction: a bibliometric and visualization analysis.

The global prevalence of stroke has been increasing. Motor dysfunction is observed in approximately 55 to 75% of stroke patients, with upper limb impairment affecting around 85% of them. Following upper limb dysfunction, the body's recovery time is not only slower compared to the lower limbs, but the restoration of its fine motor skills is significantly more challenging, greatly impacting the daily lives of patients. Consequently, there is an increasing urgency for study on the upper limb function in stroke. A search was conducted in the Web of Science Core Collection: Science Citation Index Expanded (SCI-Expanded) database for material published from January 1, 2004 to December 31, 2023. We included all relevant literature reports and conducted an analysis of annual publications, countries/regions, institutions, journals, co-cited references, and keywords using the software packages CiteSpace, VOSviewer, and Bibliometrix R. Next, we succinctly outlined the research trends and hotspots in post-stroke upper limb dysfunction. This analysis comprised 1,938 articles from 1,897 institutions, 354 journals, and 53 countries or regions. A yearly rise in the production of publications was noted. The United States is the foremost nation on the issue. Northwestern University has the most amounts of papers compared to all other institutions. The journal Neurorehabilitation and Neural Repair is a highly significant publication in this field, with Catherine E. Lang serving as the principal author. The majority of the most-cited references focus on subjects such as the reliability and validity of assessment instruments, RCT of therapies, systematic reviews, and meta-analyses. The intervention measures primarily comprise three types of high-frequency phrases that are related, as determined by keyword analysis: intelligent rehabilitation, physical factor therapy, and occupational therapy. Current areas of focus in research include randomized clinical trials, neurorehabilitation, and robot-assisted therapy. Current research has shown a growing interest in studying upper limb function assessment, occupational therapy, physical therapy, robot-assisted therapy, virtual reality, brain-computer interface, telerehabilitation, cortical reorganisation, and neural plasticity. These topics have become popular and are expected to be the focus of future research.

Sensory Stimulation and Robot-Assisted Arm Training After Stroke: A Randomized Controlled Trial.

Functional recovery after stroke is often limited, despite various treatment methods such as robot-assisted therapy. Repetitive sensory stimulation (RSS) might be a promising add-on therapy that is thought to directly drive plasticity processes. First positive effects on sensorimotor function have been shown. However, clinical studies are scarce, and the effect of RSS combined with robot-assisted training has not been evaluated yet. Therefore, our objective was to investigate the feasibility and sensorimotor effects of RSS (compared to a control group receiving sham stimulation) followed by robot-assisted arm therapy. Forty participants in the subacute phase (4.4-23.9weeks) after stroke with a moderate to severe arm paresis were randomized to RSS or control group. Participants received 12 sessions of (sham-) stimulation within 3weeks. Stimulation of the fingertips and the robot-assisted therapy were each applied in 45-min sessions. Motor and sensory outcome assessments (e.g. Fugl-Meyer-Assessment, grip strength) were measured at baseline, post intervention and at a 3-week follow-up. Participants in both groups improved their sensorimotor function from baseline to post and follow-up measurements, as illustrated by most motor and sensory outcome assessments. However, no significant group effects were found for any measures at any time ( P >0.058). Stimulations were well accepted, no safety issues arose. Feasibility of robot-assisted therapy with preceding RSS in persons with moderate to severe paresis was demonstrated. However, RSS preceding robot-assisted training failed to show a preliminary effect compared to the control intervention. Participants might have been too severely affected to identify changes driven by the RSS, or these might have been diluted or more difficult to identify because of the additional robotic training and neurorehabilitation. for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A478 ).

Non-pharmacological interventions to treat mood disturbances post-stroke: a systematic review

ABSTRACT Background Stroke survivors face high rates of depression, anxiety, and pseudobulbar affect. Clinicians report lack of clarity on effective non-pharmacological interventions due to uncertainty about treatment options as barriers to evidence-based treatment. No systematic review has investigated the effectiveness of non-pharmacological interventions on the conditions of depression, anxiety, and pseudo-bulbar affect. Objectives The aim of this study was to evaluate the effectiveness of non-pharmacological interventions on the outcomes of depression, anxiety, and pseudobulbar affect in post-stroke individuals. Methods Following the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched databases Medline, Scopus, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and PsycINFO for randomized controlled trials in English, within 2012–2023, evaluating the effect of a non-pharmacological intervention on depression, anxiety, and/or pseudobulbar affect. Two researchers screened titles, abstracts, and full texts. One researcher extracted data and assessed risk of bias. Data were synthesized narratively. Results Forty-two studies were included. Intervention types included education (n = 9), psychological therapy (n = 8), and physical exercise (n = 8). Intervention types reporting positive outcomes for depression were psychological therapy (n = 6), physical exercise (n = 3) and robot-assisted therapy (n = 3). Intervention types effective in improving anxiety were physical exercise (n = 2), psychological therapy (n = 3) and multi-modal therapy approaches (n = 2). No studies explored the impact on pseudobulbar affect. Conclusion Non-pharmacological interventions may be effective in improving mood in stroke survivors. Robot-assisted therapy and physical exercise were seen to improve multiple outcome measures. Patient education should be delivered alongside rehabilitation and directed to both stroke-survivor and caregiver.

Effects of Single-Joint Type Hybrid Assistive Limb in Knee Rehabilitation on Reduction of Pre-motor Time and Increased Rate of Fast Muscle Activation for Anterior Cruciate Regiment (ACL) Reconstruction.

Changes in muscle characteristics after post-anterior cruciate regiment (ACL) reconstruction are common. Knee robotic-assisted therapy using hybrid assistive limb (HAL) single-joint training for recovery from ACL injury has the potential to optimize muscle activity; however, its neurophysiological effects remain unclear. Thus, this study aimed to explore the electrophysiological parameters. This prospective, nonrandomized, controlled trial was conducted between December 2021 and January 2024. The patients were divided into two groups: the HAL group and the control group, each including five patients who underwent arthroscopic ACL reconstruction. Knee HAL single-joint training was conducted once weekly for three sessions. Three electrophysiological measures were examined related to knee neuromuscular responses pre-motor time, peak amplitude time, and neuromuscular rate of electromyography rise (RER) using surface electromyography (EMG). The pre-motor time and peak amplitude time were assessed in both groups at each session pre- and post-intervention.Bothgroups were evaluated for RERat postoperative weeks 17 and 21. Regarding the interaction of pre-motor time within each group, the interaction of pre-motor time within each group, the effect size of vastus medialis (VM) was larger in the HAL group. The peak amplitude time of EMG, the overall estimated marginal means, and the HAL group exhibited a significant difference in the VM (p=0.019), while vastus lateralis (VL) showed no significant difference but a larger effect size (d=0.61). The RERrevealed a significant difference in semitendinosus-RER30ms in the HAL group (p=0.044). Theknee HAL training for post-ACL reconstruction patients may influence neurophysiological outcomes.

Advancing Rehabilitation Accuracy: A Robotic-Human-Like Controller for Continuous Passive Motion with Natural Behavioural Responses

Conventionally, researchers have primarily focused on developing gravity-compensation robots without considering the voluntary resistant force in continuous passive motion (CPM) therapy. This leads to critical limitations in robot-assisted therapy compared to conventional therapy administered by therapists, particularly in terms of generating natural behavioural responses in patients. To address this limitation, our proposed technique aims to investigate model-based dynamic force estimation specifically related to intrinsic muscular force in order to develop a robotic-human-like controller for CPM therapy. We conducted an estimation of the muscular force based on surface electromyography (sEMG) signals using Ridge Polynomial, Artificial Neural Network (ANN), and Support Vector Machine (SVM) approaches. Strategic preprocessing and model optimization procedures were implemented. The optimized results demonstrate that ANN exhibits slightly superior performance enhancing the accuracy and precision with its quicker testing time. Moreover, the substantive results demonstrate a notable comparison between the use of conventional gravity compensation and our novel technique which integrates both intrinsic muscular force and gravity compensation. It reveals that our approach yields calculated voluntary forces that more closely approximate to the actual values in comparison to the conventional method. In conclusion, this research makes a significant contribution to the development of a smart robotic controller offering high-accuracy measurement of voluntary forces for CPM therapy, thereby facilitating natural behavioural responses.

A genetic algorithm-based method to modulate the difficulty of serious games along consecutive robot-assisted therapy sessions

Background and Objective:One of the biggest challenges during neurorehabilitation therapies is finding an appropriate level of therapy intensity for each patient to ensure the recovery of movement of the affected limbs while maintaining motivation. Different studies have proposed adapting the difficulty of exercises based on psychophysiological state, based on success rate, or by modeling the user’s skills. However, all studies propose solutions for a single session, requiring a calibration process before using it in each session. We propose a dynamic adaptation method that can be used during different rehabilitation sessions, without the need for recalibration between sessions. Methods:The adaptation architecture is based on a genetic algorithm that aims to maintain a certain score level and to motivate the user to move. The method has been evaluated with two serious games for five sessions using a rehabilitation robot. A common initial evaluation was made for all the users involved in the study, and the game parameters that best suited each user from the previous session were introduced as the starting point of the next session. In addition, the desired score rate was lowered between sessions to increase the difficulty level. The psychophysiological state of the users was measured based on the Self-Assessment Manikin test, as well as different cardiorespiratory and galvanic skin response signals were analyzed. Results:The adaptation architecture proposed can find those game parameters that maximize the user movement for both games. In one of the games, the score rate set for each session is followed with high fidelity. The degree of personalization in the games increases between sessions as the dispersion of the game parameters grows. The Self-Assessment Manikin test and the physiological signals results would indicate that the psychophysiological state remains equal between sessions despite an increase in game difficulty. Conclusions:The genetic algorithm-based game adaptation has proven efficacy in maximizing the therapy performance through the sessions without needing recalibration. It also can be concluded that the design of the game influences the adaptation performance. Additionally, adaptive game design facilitated by our method does not significantly impact players’ emotional or physiological states.

The Feasibility of Robot-assisted Laser Interstitial Thermal Therapy (LITT) for Brain Tumors in Octogenarians

The use of robot-assisted laser interstitial thermal therapy (LITT) is emerging as a viable treatment option for brain tumors in patients aged 80-90 years (octogenarians). Correspondingly, the aim of this study was to describe the clinical feasibility of octogenarians undergoing LITT procedure for brain tumors at our institution. A retrospective review was conducted of all robot-assisted LITT procedures performed at our institution between 2013 and 2023 for octogenarians. Comparison of continuous variables was by Student t tests, and Kaplan-Meier estimates were used to estimate survival outcomes. A total of 20 of 311 (6%) LITT patients in the search cohort were octogenarians. Mean age was 82.6 years (range, 80.1-88.0 years) with 13 (65%) female patients. Brain tumor lesions most commonly were located on the left side (65%), and, for ablation, all were single trajectories with mean number of 2.3 ablations. No operative complications were seen during hospitalization, with mean length of stay of 1.6 days and most common disposition destination being home (95%). There were no 30- or 90-day readmissions or emergency department presentations. Mean follow-up was 12.4 months without any complications in that time. The most common pathology in our cohort was glioblastoma (55%). Robot-assisted LITT is a safe and effective treatment option for brain tumors in octogenarians with a very low morbidity risk. Therefore, further investigation is required to understand how LITT can translate to therapeutic benefit in patients aged over 80 years old with brain tumors.

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

Upper limb impairments are among the most common consequences following a stroke. Recently, robot-assisted therapy (RT) and virtual reality (VR) have been used to improve upper limb function in stroke survivors. This review aims to investigate the effects of combined RT and VR on upper limb function in stroke survivors and to provide recommendations for researchers and clinicians in the medical field. We searched PubMed, SCOPUS, REHABDATA, PEDro, EMBASE, and Web of Science from inception to March 28, 2024. Randomized controlled trials (RCTs) involving stroke survivors that compared combined RT and VR interventions with either passive (i.e., sham, rest) or active (i.e., traditional therapy, VR, RT) interventions and assessed outcomes related to upper limb function (e.g., strength, muscle tone, or overall function) were included. The Cochrane Collaboration tool was used to evaluate the methodological quality of the included studies. Six studies were included in this review. In total, 201 patients with stroke (mean age 57.84years) were involved in this review. Four studies were considered 'high quality', while two were considered as 'moderate quality' on the Cochrane Collaboration tool. The findings showed inconsistent results for the effects of combined RT and VR interventions on upper limb function poststroke. In conclusion, there are potential effects of combined RT and VR interventions on improving upper limb function, but further research is needed to confirm these findings, understand the underlying mechanisms, and assess the consistency and generalizability of the results.

Embodied experience in robot-assisted rehabilitation train-ing therapy: A bibliometric analysis (2014-2023)

Industry 4.0 technology has transformed human-robot interaction in robot-assisted rehabilitation therapy. However, most current studies focus on the patients perceived motor participation. Few studies have systematically reviewed the patients experience, including their psychological involvement, perception, experience, and judgment of the rehabilitation environment, therapist, and robot, as well as examining the coupling of mental participation and motor participation. This paper presents a systematic study and literature review from the perspective of the embodied experience of patients, utilizing a combination of the scoping review, performance analysis, science mapping, and bibliometrics analysis to examine relevant literature. The result emphasizes the significance and necessity of the patients embodied experience in robot-assisted rehabilitation training therapy. Most research in this field is founded on embodied theory and embodied technology. This study provides an essential theoretical reference for the study of embodied experience in robot-assisted rehabilitation therapy, helping to improve theoretical and practical approaches to improve the users embodied experience and aid user experience research and design in related research institutions and businesses.

Responsiveness and construct validity of two outcome measures of bilateral upper limb function in patients with chronic stroke

BackgroundStroke is a leading cause of long-term disability among stroke survivors. Despite the availability of numerous stroke rehabilitative therapies, such as mirror therapy, bilateral arm training, and robot-assisted therapy, the recovery of motor function after stroke remains incomplete. Bilateral arm function is a key component in stroke patients to perform activities of daily living and to reflect their functional autonomy.ObjectiveThis clinimetric study investigated and compared the construct validity and responsiveness of 2 bimanual activity outcome measures, the Chedoke Arm and Hand Activity Inventory (CAHAI) and the ABILHAND Questionnaire, in individuals receiving stroke rehabilitation.MethodsThe present study is a secondary analysis following the framework of the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). Individuals with chronic stroke (N = 113) were recruited from outpatient rehabilitation settings. Participants received 18 to 20 sessions of robot-assisted therapy, mirror therapy, combined therapy, or conventional rehabilitation for 4 to 6 weeks. The CAHAI, ABILHAND Questionnaire, and a comparison instrument, the Motor Activity Log (MAL), were administered twice at a 4- to 6-week interval to all participants. ABILHAND scores, in logits, were converted from raw ordinal scores into a linear measure.ResultsThere was medium to large correlation of the CAHAI and the MAL (ρ = 0.60–0.62, p &amp;lt; 0.01) as well as the ABILHAND Questionnaire and the MAL (ρ = 0.44–0.51, p &amp;lt; 0.01). Change scores from the initial measurement to the post-intervention measurement demonstrated small to medium correlation of the CAHAI and the MAL (ρ = 0.27–0.31, p &amp;lt; 0.01) and medium to large correlation of the ABILHAND Questionnaire and the MAL (ρ = 0.37–0.41, p &amp;lt; 0.01). Overall, 7 of 8 hypotheses were supported. The hypothesis testing regarding the construct validity and responsiveness of the CAHAI and ABILHAND Questionnaire was confirmed.ConclusionThe CAHAI and ABILHAND Questionnaire are both responsive and suitable to detect changes in bilateral arm functional daily activities in individuals with chronic stroke. Patient-reported outcome measures are recommended to use along with therapist-rated outcome measures for upper limb capacity evaluation in stroke rehabilitation. Further study with a prospective study design to capture specific clinical features of participants and the use of body-worn sensors, such as the arm accelerometer, is suggested.

Effect of bimanual sensor glove and unimanual robot-assisted therapy for upper limb function after stroke

Effect of bimanual sensor glove and unimanual robot-assisted therapy for upper limb function after stroke

A systematic investigation of detectors for low signal-to-noise ratio EMG signals

Background Active participation of stroke survivors during robot-assisted movement therapy is essential for sensorimotor recovery. Robot-assisted therapy contingent on movement intention is an effective way to encourage patients’ active engagement. For severely impaired stroke patients with no residual movements, a surface electromyogram (EMG) has been shown to be a viable option for detecting movement intention. Although numerous algorithms for EMG detection exist, the detector with the highest accuracy and lowest latency for low signal-to-noise ratio (SNR) remains unknown. Methods This study, therefore, investigates the performance of 13 existing EMG detection algorithms on simulated low SNR (0dB and -3dB) EMG signals generated using three different EMG signal models: Gaussian, Laplacian, and biophysical model. The detector performance was quantified using the false positive rate (FPR), false negative rate (FNR), and detection latency. Any detector that consistently showed FPR and FNR of no more than 20%, and latency of no more than 50ms, was considered an appropriate detector for use in robot-assisted therapy. Results The results indicate that the Modified Hodges detector – a simplified version of the threshold-based Hodges detector introduced in the current study – was the most consistent detector across the different signal models and SNRs. It consistently performed for ~90% and ~40% of the tested trials for 0dB and -3dB SNR, respectively. The two statistical detectors (Gaussian and Laplacian Approximate Generalized Likelihood Ratio) and the Fuzzy Entropy detectors have a slightly lower performance than Modified Hodges. Conclusions Overall, the Modified Hodges, Gaussian and Laplacian Approximate Generalized Likelihood Ratio, and the Fuzzy Entropy detectors were identified as the potential candidates that warrant further investigation with real surface EMG data since they had consistent detection performance on low SNR EMG data.

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

BackgroundUnsupervised 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.MethodsSubacute 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.ResultsUnsupervised 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.ConclusionsWe 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 registrationRegistered on 13.05.2020 on clinicaltrials.gov (NCT04388891).

Multimodal brain-controlled system for rehabilitation training: Combining asynchronous online brain–computer interface and exoskeleton

Background:Traditional therapist-based rehabilitation training for patients with movement impairment is laborious and expensive. In order to reduce the cost and improve the treatment effect of rehabilitation, many methods based on human–computer interaction (HCI) technology have been proposed, such as robot-assisted therapy and functional electrical stimulation (FES). However, due to the lack of active participation of brain, these methods have limited effects on the promotion of damaged nerve remodeling. New method:Based on the neurofeedback training provided by the combination of brain–computer interface (BCI) and exoskeleton, this paper proposes a multimodal brain-controlled active rehabilitation system to help improve limb function. The joint control mode of steady-state visual evoked potential (SSVEP) and motor imagery (MI) is adopted to achieve self-paced control and thus maximize the degree of brain involvement, and a requirement selection function based on SSVEP design is added to facilitate communication with aphasia patients. Comparison with existing methods:In addition, the Transformer is introduced as the MI decoder in the asynchronous online BCI to improve the global perception of electroencephalogram (EEG) signals and maintain the sensitivity and efficiency of the system. Results:In two multi-task online experiments for left hand, right hand, foot and idle states, subject achieves 91.25% and 92.50% best accuracy, respectively. Conclusion:Compared with previous studies, this paper aims to establish a high-performance and low-latency brain-controlled rehabilitation system, and provide an independent and autonomous control mode of the brain, so as to improve the effect of neural remodeling. The performance of the proposed method is evaluated through offline and online experiments.

Learning-based personalisation of robot behaviour for robot-assisted therapy.

During robot-assisted therapy, a robot typically needs to be partially or fully controlled by therapists, for instance using a Wizard-of-Oz protocol; this makes therapeutic sessions tedious to conduct, as therapists cannot fully focus on the interaction with the person under therapy. In this work, we develop a learning-based behaviour model that can be used to increase the autonomy of a robot's decision-making process. We investigate reinforcement learning as a model training technique and compare different reward functions that consider a user's engagement and activity performance. We also analyse various strategies that aim to make the learning process more tractable, namely i) behaviour model training with a learned user model, ii) policy transfer between user groups, and iii) policy learning from expert feedback. We demonstrate that policy transfer can significantly speed up the policy learning process, although the reward function has an important effect on the actions that a robot can choose. Although the main focus of this paper is the personalisation pipeline itself, we further evaluate the learned behaviour models in a small-scale real-world feasibility study in which six users participated in a sequence learning game with an assistive robot. The results of this study seem to suggest that learning from guidance may result in the most adequate policies in terms of increasing the engagement and game performance of users, but a large-scale user study is needed to verify the validity of that observation.

The impact of reminiscent music therapy and robot-assisted rehabilitation on older stroke patients: a protocol for a randomized controlled trial.

Stroke is the main disease that causes the burden of neurological disease, leading to upper limb dysfunction and affecting their self-care abilities. Robot-assisted rehabilitation therapy has been gradually used in the rehabilitation of upper limb function after stroke. However, it would be beneficial to explore auxiliary interventions such as reminiscent music therapy, a combination of music and reminiscent, to relieve negative emotions and post-stroke fatigue and improve rehabilitation outcomes. This protocol aims to evaluate the effectiveness of reminiscent music therapy combined with robot-assisted rehabilitation in older stroke patients. This trial is a single-blind, three-arm randomized controlled trial. Older stroke patients with upper limb dysfunction will be recruited. Participants will be randomly assigned to receive usual rehabilitation treatment and care, usual rehabilitation treatment and care plus robot-assisted rehabilitation and reminiscent music therapy, or usual rehabilitation treatment and care plus robot-assisted rehabilitation. Robot-assisted rehabilitation will be conducted by rehabilitation doctors five times per week for 3 weeks. In experimental group 1, a reminiscent song list will be played for patients. The primary outcome is activities of daily living. All outcomes will be evaluated at baseline and in the week immediately post-intervention. We are conducting the first randomized controlled trial on the effects of reminiscent music therapy combined with robot-assisted rehabilitation in older stroke patients. It is expected that this study, if proven effective in improving the activities of daily living in older stroke patients with upper limb dysfunction, will provide evidence-based rehabilitation strategies for medical staff.Clinical Trial Registration: ChiCTR2200063738.

Walking as “Grounding”: An Ethnography of Robot-Assisted Rehabilitation and Patients’ Aspirations in South Korea

Based upon the view that walking is a highly social act, i.e. “grounding” oneself in the realities, not just the medium of “moving,” this paper explores robot-assisted rehabilitation and patients’ aspirations concerning it. Fieldwork conducted in rehabilitation hospitals and disability centers in South Korea, reveals that rehabilitative medicine settles uneasily on the notion of neuroplasticity as a theoretical tool to legitimize robot-assisted therapy sessions, in the absence both of upstream treatment options such as stem cell therapy and their discernible benefits over human-based intervention. The patient’s clear preference to walk rather than to move, and hence to regain the whole package of sociality associated with the bodily technique underlies their high expectations toward robots. Under these insights, the paper argues that, for the field to enhance its clinical impact, the current regime focused on mechanical, or neurophysiological, aspects of walking should incorporate elements vitalizing the sociality constitutive of it.