Search

Although brain-computer interface (BCI) shows promising prospects to help post-stroke patients recover their motor function, its decoding accuracy is still highly dependent on feature extraction methods. Most current feature extractors in BCI are classification-based methods, yet very few works from literature use metric learning based methods to learn representations for BCI. To circumvent this shortage, we propose a deep metric learning based method, Weighted Convolutional Siamese Network (WCSN) to learn representations from electroencephalogram (EEG) signal. This approach can enhance the decoding accuracy by learning a low dimensional embedding to extract distance-based representations from pair-wise EEG data. To enhance training efficiency and algorithm performance, a temporal-spectral distance weighted sampling method is proposed to select more informative input samples. In addition, an adaptive training strategy is adopted to address the session-to-session non-stationarity by progressively updating the subject-specific model. The proposed method is applied on both upper limb and lower limb neurorehabilitation datasets acquired from 33 stroke patients, with a total of 358 sessions. Results indicate that using k-Nearest Neighbor as the classification algorithm, the proposed method yielded 72.8% and 66.0% accuracies for the two datasets respectively, significantly better than the other state-of-the-arts ( ). Without losing generality, we also evaluated the proposed method on two publicly available datasets acquired from healthy subjects, wherein the proposed algorithm demonstrated superior performance at most cases as well. Our results support, for the first time, the use of a metric learning based feature extractor to learn representations from non-stationary EEG signals for BCI-assisted post-stroke rehabilitation.

Introduction: The aim of this research was to evaluate the impact of a novel tele-rehabilitation system on self-reported functional outcomes compared to usual care during the first three months after stroke., Methods: A parallel, two-arm, evaluator-blinded, randomised controlled trial was conducted. Adults aged ≥40 years who had suffered a stroke within four weeks of the start of the study were recruited from the general community. The intervention group received access to a novel tele-rehabilitation system and programme for three months. The primary outcome measures utilised were the frequency and limitation total scores of the Late-Life Function and Disability Instrument (LLFDI) at three months., Results: A total of 124 individuals were recruited. The mean differences in the LLDFI frequency and limitation total scores at three months comparing the intervention and control groups were -3.30 (95% confidence interval (CI) -7.81 to 1.21) and -6.90 (95% CI -15.02 to 1.22), respectively. Adjusting for the respective baseline covariates and baseline Barthel Index also showed no significant difference between interventions in the LLFDI outcomes., Discussion: The intervention and control groups self-reported similar improvements in functional outcomes. Tele-rehabilitation may be a viable option to provide post-stroke rehabilitation services in Singapore while reducing barriers to continue rehabilitation conventionally after discharge from hospital and encouraging more participation.

Objective: To study the association of caregiver factors and stroke survivor factors with supervised community rehabilitation (SCR) participation over the first 3 months and subsequent 3 to 12 months post-stroke in an Asian setting., Design: Prospective cohort study., Setting: Community setting., Participants: We recruited stroke survivors and their caregivers into our yearlong cohort. Caregiver and stroke survivor variables were collected over 3-monthly intervals. We performed logistic regression with the outcome variable being SCR participation post-stroke., Outcome Measures: SCR participation over the first 3 months and subsequent 3 to 12 months post-stroke RESULTS: 251 stroke survivor-caregiver dyads were available for the current analysis. The mean age of caregivers was 50.1 years, with the majority being female, married and co-residing with the stroke survivor. There were 61%, 28%, 4% and 7% of spousal, adult-child, sibling and other caregivers. The odds of SCR participation decreased by about 15% for every unit increase in caregiver-reported stroke survivor's disruptive behaviour score (OR: 0.845; 95% CI: 0.769 to 0.929). For every 1-unit increase in the caregiver's positive management strategy score, the odds of using SCR service increased by about 4% (OR: 1.039; 95% CI: 1.011 to 1.068)., Conclusion: We established that SCR participation is jointly determined by both caregiver and stroke survivor factors, with factors varying over the early and late post-stroke period. Our results support the adoption of a dyadic or more inclusive approach for studying the utilisation of community rehabilitation services, giving due consideration to both the stroke survivors and their caregivers. Adopting a stroke survivor-caregiver dyadic approach in practice settings should include promotion of positive care management strategies, comprehensive caregiving training including both physical and behavioural dimensions, active engagement of caregivers in rehabilitation journey and conducting regular caregiver needs assessments in the community., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: This single-arm multisite trial investigates the efficacy of the neurostyle brain exercise therapy towards enhanced recovery (nBETTER) system, an electroencephalogram (EEG)-based motor imagery brain-computer interface (MI-BCI) employing visual feedback for upper-limb stroke rehabilitation, and the presence of EEG correlates of mental fatigue during BCI usage., Methods: A total of 13 recruited stroke patients underwent thrice-weekly nBETTER therapy coupled with standard arm therapy over six weeks. Upper-extremity Fugl-Meyer motor assessment (FMA) scores were measured at baseline (week 0), post-intervention (week 6), and follow-ups (weeks 12 and 24). In total, 11/13 patients (mean age 55.2 years old, mean post-stroke duration 333.7 days, mean baseline FMA 35.5) completed the study., Results: Significant FMA gains relative to baseline were observed at weeks 6 and 24. Retrospectively comparing to the standard arm therapy (SAT) control group and BCI with haptic knob (BCI-HK) intervention group from a previous similar study, the SAT group had no significant gains, whereas the BCI-HK group had significant gains at weeks 6, 12, and 24. EEG analysis revealed significant positive correlations between relative beta power and BCI performance in the frontal and central brain regions, suggesting that mental fatigue may contribute to poorer BCI performance., Conclusion: nBETTER, an EEG-based MI-BCI employing only visual feedback, helps stroke survivors sustain short-term FMA improvement. Analysis of EEG relative beta power indicates that mental fatigue may be present., Significance: This study adds nBETTER to the growing literature of safe and effective stroke rehabilitation MI-BCI, and suggests an additional fatigue-monitoring role in future such BCI.

With the availability of multiple rehabilitative interventions, identifying the one that elicits the best motor outcome based on the unique neuro-clinical profile of the stroke survivor is a challenging task. Predicting the potential of recovery using biomarkers specific to an intervention hence becomes important. To address this, we investigate intervention-specific prognostic and monitory biomarkers of motor function improvements using quantitative electroencephalography (QEEG) features in 19 chronic stroke patients following two different upper extremity rehabilitative interventions viz. Brain-computer interface (BCI) and transcranial direct current stimulation coupled BCI (tDCS-BCI). Brain symmetry index was found to be the best prognostic QEEG for clinical gains following BCI intervention ( r = -0.80 , p = 0.02 ), whereas power ratio index (PRI) was observed to be the best predictor for tDCS-BCI ( r = -0.96 , p = 0.004 ) intervention. Importantly, statistically significant between-intervention differences observed in the predictive capabilities of these features suggest that intervention-specific biomarkers can be identified. This approach can be further pursued to distinctly predict the expected response of a patient to available interventions. The intervention with the highest predicted gains may then be recommended to the patient, thereby enabling a personalized rehabilitation regime.

Objectives: This study aimed to quantify health-related quality of life (HRQoL) loss associated with first episode of stroke by comparing patient-reported HRQoL before and after stroke onset. The impact of stroke in local population was also evaluated by comparing the pre- and post-stroke HRQoL with that of the general population., Methods: The HRQoL of stroke survivors was assessed with the EQ-5D-3L index score at recruitment, for recalled pre-stroke HRQoL, and at 3 and 12 month post-stroke. Change in HRQoL from pre-stroke to 3 and 12 month was self-reported by 285 and 238 patients, respectively. Mean EQ index score at each time point (baseline: 464 patients; 3 month post-stroke: 306 patients; 12 month post-stroke: 258 patients) was compared with published population norms for EQ-5D-3L., Results: There was a significant decrease in HRQoL at 3 (0.25) and 12 month (0.09) post-stroke when compared to the retrospectively recalled patients' mean pre-stroke HRQoL level (0.87). The reduction at 3 month was associated with the reduction in all EQ-5D-3L health dimensions; reductions remaining at 12 month were limited to dimensions of mobility, self-care, usual activities, and anxiety/depression. Stroke patients had a lower mean EQ index than the general population by 0.07 points pre-stroke (0.87 vs. 0.94), 0.33 points at 3 month (0.61 vs. 0.94) and 0.18 points at 12 month (0.76 vs. 0.94) post-stroke., Conclusions: Stroke has a substantial impact on HRQoL in Singapore, especially in the first three months post-stroke. Compared to the general population, stroke survivors have lower HRQoL even before stroke onset. This pre-stroke deficit in HRQoL should be taken into account when quantifying health burden of stroke or setting goals for stroke rehabilitation., Competing Interests: The authors have declared that no competing interests exist.

Stroke is a leading cause of disability in the world and the use of robots in rehabilitation has become increasingly common. The Fourth Industrial Revolutions has created a novel and wide range of options for the involvement of computer-guided and artificially intelligent machines to be used in rehabilitation. In this chapter we critically review some of the literature on the use of robots in rehabilitation, and emphasize the diversity of approaches in this burgeoning field. We argue that there is a need to consolidate interdisciplinary evidence on robotics and rehabilitation in a systematic way, as the alternative is to have a literature that continues to grow, following the interests of various specialists, but without offering a synoptic assessment of what is available to medical specialists and patients. A literature review using Scopus and Web of Science, coupled with the Briggs Institute's Critical Appraisal Tool: Checklist for Case Reports was conducted. The two databases were systematically searched using inter-disciplinary keywords in Feb 2019. An initial search of the databases produced 9894 articles. After rigorous reviews, 35 articles were screened and selected for further interpretation. We examined the current studies on the efficiency and effectiveness of the robot interventions and produced a taxonomy of the review. An original finding of the current robotics in rehabilitation landscaping are critical presented with recommendations and concluding remarks concerning interdisciplinary impact.

This study investigates the neurological changes in the brain activity of chronic stroke patients undergoing different types of motor rehabilitative interventions and their relationship with the clinical recovery using the Quantitative Electroencephalography (QEEG) features. Over a period of two weeks, 19 hemiplegic chronic stroke patients underwent 10 sessions of upper extremity motor rehabilitation using a brain-computer interface paradigm (BCI group, n=9) and transcranial direct current stimulation coupled BCI paradigm (tDCS group, n=10). The pre- and post-treatment brain activations, as well as the intervention-induced changes in the neuronal activity, were quantified using 11 QEEG features and their relationship with clinical motor improvement was investigated. Significant treatment-induced change in the relative theta power was observed in the BCI group and the change was significantly correlated with the clinical improvements. Also, in the BCI group, the relative theta power and interactions between the theta, alpha, and beta power were identified as monitory biomarkers of motor recovery. On the contrary, the tDCS group was characterized by the significant change in brain asymmetry. Furthermore, we observed significant intergroup differences in the predictive capabilities of post-intervention QEEG features between the BCI and tDCS group. Based on the intergroup differences observed in this study and convergent results from the other neuroimaging analysis performed on the same cohort, we suggest that distinctly different mechanisms of neuronal recovery were facilitated by tDCS and BCI interventions and these treatment specific mechanisms can be encapsulated using QEEG.

Mapping the brain alterations post stroke and post intervention is important for rehabilitation therapy development. Previous work has shown changes in functional connectivity based on resting-state fMRI, structural connectivity derived from diffusion MRI and perfusion as a result of brain-computer interface-assisted motor imagery (MI-BCI) and transcranial direct current stimulation (tDCS) in upper-limb stroke rehabilitation. Besides functional connectivity, regional amplitude of local low-frequency fluctuations (ALFF) may provide complementary information on the underlying neural mechanism in disease. Yet, findings on spontaneous brain activity during resting-state in stroke patients after intervention are limited and inconsistent. Here, we sought to investigate the different brain alteration patterns induced by tDCS compared to MI-BCI for upper-limb rehabilitation in chronic stroke patients using resting-state fMRI-based ALFF method. Our results suggested that stroke patients have lower ALFF in the ipsilesional somatomotor network compared to controls at baseline. Increased ALFF at contralesional somatomotor network and alterations in higher-level cognitive networks such as the default mode network (DMN) and salience networks accompany motor recovery after intervention; though the MI-BCI alone group and MI-BCI combined with tDCS group exhibit differential patterns.

Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been used in stroke rehabilitation, though their combinatory effect is unknown. We investigated brain plasticity following a combined MI-BCI and tDCS intervention in chronic subcortical stroke patients with unilateral upper limb disability. Nineteen patients were randomized into tDCS and sham-tDCS groups. Diffusion and perfusion MRI, and transcranial magnetic stimulation were used to study structural connectivity, cerebral blood flow (CBF), and corticospinal excitability, respectively, before and 4 weeks after the 2-week intervention. After quality control, thirteen subjects were included in the CBF analysis. Eleven healthy controls underwent 2 sessions of MRI for reproducibility study. Whereas motor performance showed comparable improvement, long-lasting neuroplasticity can only be detected in the tDCS group, where white matter integrity in the ipsilesional corticospinal tract and bilateral corpus callosum was increased but sensorimotor CBF was decreased, particularly in the ipsilesional side. CBF change in the bilateral parietal cortices also correlated with motor function improvement, consistent with the increased white matter integrity in the corpus callosum connecting these regions, suggesting an involvement of interhemispheric interaction. The preliminary results indicate that tDCS may facilitate neuroplasticity and suggest the potential for refining rehabilitation strategies for stroke patients.

Introduction: The poststroke acute and rehabilitation length of stay (LOS) are key markers of stroke care efficiency. This study aimed to describe the characteristics and identify the predictors of poststroke acute, rehabilitation and total LOS. This study also defined a subgroup of patients as "short" LOS and compared its complication rates and functional outcomes in rehabilitation with a "long" acute LOS group., Materials and Methods: A prospective cohort study (n = 1277) was conducted in a dedicated rehabilitation unit within a tertiary academic acute hospital over a 5-year period between 2004 and 2009. The functional independence measure (FIM) was the primary functional outcome measure in the rehabilitation phase. A group with an acute LOS of less than 7 days was defined as "short" acute LOS., Results: Ischaemic strokes comprised 1019 (80%) of the cohort while the rest were haemorrhagic strokes. The mean acute and rehabilitation LOS were 9 ± 7 days and 18 ± 10 days, respectively. Haemorrhagic strokes and anterior circulation infarcts had significantly longer acute, rehabilitation and total LOS compared to posterior circulation and lacunar infarcts. The acute, rehabilitation and total LOS were significantly shorter for stroke admissions after 2007. There was poor correlation (r = 0.12) between the acute and rehabilitation LOS. In multivariate analyses, stroke type was strongly associated with acute LOS, while rehabilitation admission FIM scores were significantly associated with rehabilitation LOS. Patients in the short acute LOS group had fewer medical complications and similar FIM efficacies compared to the longer acute LOS group., Conclusion: Consideration for stroke type and initial functional status will facilitate programme planning that has a better estimation of the LOS duration, allowing for more equitable resource distribution across the inpatient stroke continuum. We advocate earlier transfers of appropriate patients to rehabilitation units as this ensures rehabilitation efficacy is maintained while the development of medical complications is potentially minimised.

Background: Most acute stroke patients with disabilities do not receive recommended rehabilitation following discharge to the community. Functional and social barriers are common reasons for non-adherence to post-discharge rehabilitation. Home rehabilitation is an alternative to centre-based rehabilitation but is costlier. Tele-rehabilitation is a possible solution, allowing for remote supervision of rehabilitation and eliminating access barriers. The objective of the Singapore Tele-technology Aided Rehabilitation in Stroke (STARS) trial is to determine if a novel tele-rehabilitation intervention for the first three months after stroke admission improves functional recovery compared to usual care., Methods/design: This is a single blind (evaluator blinded), parallel, two-arm randomised controlled trial study design involving 100 recent stroke patients. The inclusion criteria are age ≥40 years, having caregiver support and recent stroke defined as stroke diagnosis within 4 weeks. Consenting participants will be randomized with varying block size of 4 or 6 assuming a 1:1 treatment allocation with the participating centre as the stratification factor. The baseline assessment will be done within 4 weeks of stroke onset, followed by follow-up assessments at 3 and 6 months. The tele-rehabilitation intervention lasts for 3 months and includes exercise 5-days-a-week using an iPad-based system that allows recording of daily exercise with video and sensor data and weekly video-conferencing with tele-therapists after data review. Those allocated to the control group will receive usual care. The primary outcome measure is improvement in life task's social activity participation at three months as measured by the disability component of the Jette Late Life Functional and Disability Instrument (LLFDI). Secondary outcome variables consist of gait speed (Timed 5-Meter Walk Test) and endurance (Two-Minute Walk test), performance of basic activities of daily living (Shah-modified Barthel Index), balance confidence (Activities-Specific Balance Confidence Scale), patient self-reported health-related quality-of-life [Euro-QOL (EQ-5D)], health service utilization (Singapore Stroke Study Health Service Utilization Form) and caregiver reported stress (Zarit Caregiver Burden Inventory)., Discussion: The goal of this trial is to provide evidence on the potential benefit and cost-effectiveness of this novel tele-rehabilitation programme which will guide health care decision-making and potentially improve performance of post-stroke community-based rehabilitation., Trial Registration: This trial protocol was registered under ClinicalTrials.gov on 18 July 2013 as study title "The Singapore Tele-technology Aided Rehabilitation in Stroke (STARS) Study" (ID: The STARS Study, ClinicalTrials.gov Identifier: NCT01905917 ).

Objective: To investigate the efficacy and effects of transcranial direct current stimulation (tDCS) on motor imagery brain-computer interface (MI-BCI) with robotic feedback for stroke rehabilitation., Design: A sham-controlled, randomized controlled trial., Setting: Patients recruited through a hospital stroke rehabilitation program., Participants: Subjects (N=19) who incurred a stroke 0.8 to 4.3 years prior, with moderate to severe upper extremity functional impairment, and passed BCI screening., Interventions: Ten sessions of 20 minutes of tDCS or sham before 1 hour of MI-BCI with robotic feedback upper limb stroke rehabilitation for 2 weeks. Each rehabilitation session comprised 8 minutes of evaluation and 1 hour of therapy., Main Outcome Measures: Upper extremity Fugl-Meyer Motor Assessment (FMMA) scores measured end-intervention at week 2 and follow-up at week 4, online BCI accuracies from the evaluation part, and laterality coefficients of the electroencephalogram (EEG) from the therapy part of the 10 rehabilitation sessions., Results: FMMA score improved in both groups at week 4, but no intergroup differences were found at any time points. Online accuracies of the evaluation part from the tDCS group were significantly higher than those from the sham group. The EEG laterality coefficients from the therapy part of the tDCS group were significantly higher than those of the sham group., Conclusions: The results suggest a role for tDCS in facilitating motor imagery in stroke., (Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.)

In the past 3 decades, interest has increased in brain-computer interface (BCI) technology as a tool for assisting, augmenting, and rehabilitating sensorimotor functions in clinical populations. Initially designed as an assistive device for partial or total body impairments, BCI systems have since been explored as a possible adjuvant therapy in the rehabilitation of patients who have had a stroke. In particular, BCI systems incorporating a robotic manipulanda to passively manipulate affected limbs have been studied. These systems can use a range of invasive (ie, intracranial implanted electrodes) or noninvasive neurophysiologic recording techniques (ie, electroencephalography [EEG], near-infrared spectroscopy, and magnetoencephalography) to establish communication links between the brain and the BCI system. Trials are most commonly performed on EEG-based BCI in comparison with the other techniques because of its high temporal resolution, relatively low setup costs, portability, and noninvasive nature. EEG-based BCI detects event-related desynchronization/synchronization in sensorimotor oscillatory rhythms associated with motor imagery (MI), which in turn drives the BCI. Previous evidence suggests that the process of MI preferentially activates sensorimotor regions similar to actual task performance and that repeated practice of MI can induce plasticity changes in the brain. It is therefore postulated that the combination of MI and BCI may augment rehabilitation gains in patients who have had a stroke by activating corticomotor networks via MI and providing sensory feedback from the affected limb using end-effector robots. In this review we examine the current literature surrounding the feasibility of EEG-based MI-BCI systems in stroke rehabilitation. We also discuss the limitations of using EEG-based MI-BCI in patients who have had a stroke and suggest possible solutions to overcome these limitations., (Copyright © 2014 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.)

Brain-computer interface (BCI) technology has the potential as a post-stroke rehabilitation tool, and the efficacy of the technology is most often demonstrated through output peripherals such as robots, orthosis and computers. In this study, the EEG signals recorded during the course of upper limb stroke rehabilitaion using motor imagery BCI were analyzed to better understand the effect of BCI therapy for post-stroke rehabilitation. The stroke patients recruited underwent 10 sessions of 1-hour BCI with robotic feedback for 2 weeks, 5 times a week. The analysis was performed by computing the coherences of the EEG in the lesion and contralesion side of the hemisphere from each session, and the coherence index of the lesion hemisphere (0 ≤ CI ≤ 1) was computed. The coherence index represents the rate of activation of the lesion hemisphere, and the correlation with the Fugl-Meyer assessment (FMA) before and after the BCI therapy was investigated. Significant improvement in the FMA scores was reported for five of the six patients (p = 0.01). The analysis showed that the number of sessions with CI ≥ 0.5 correlated with the change in the FMA scores. This suggests that post-stroke motor recovery best results from the activation in the lesion hemisphere, which is in agreement with previous studies performed using multimodal imaging technologies.

Clinical studies had shown that EEG-based motor imagery Brain-Computer Interface (MI-BCI) combined with robotic feedback is effective in upper limb stroke rehabilitation, and transcranial Direct Current Stimulation (tDCS) combined with other rehabilitation techniques further enhanced the facilitating effect of tDCS. This motivated the current clinical study to investigate the effects of combining tDCS with MI-BCI and robotic feedback compared to sham-tDCS for upper limb stroke rehabilitation. The stroke patients recruited were randomized to receive 20 minutes of tDCS or sham-tDCS prior to 10 sessions of 1-hour MI-BCI with robotic feedback for 2 weeks. The online accuracies of detecting motor imagery from idle condition were assessed and offline accuracies of classifying motor imagery from background rest condition were assessed from the EEG of the evaluation and therapy parts of the 10 rehabilitation sessions respectively. The results showed no evident differences between the online accuracies on the evaluation part from both groups, but the offline analysis on the therapy part yielded higher averaged accuracies for subjects who received tDCS (n=3) compared to sham-tDCS (n=2). The results suggest towards tDCS effect in modulating motor imagery in stroke, but a more conclusive result can be drawn when more data are collected in the ongoing study.

Introduction/Background Stroke is a leading cause of disability worldwide. Functional, financial and social barriers commonly prevent individuals with acute stroke and disabilities from receiving rehabilitation following their hospital discharge. Home-based rehabilitation is an alternative to center-based rehabilitation but it is often costlier. Tele-rehabilitation is a promising solution for optimizing rehabilitation utilization, as it can enable clinicians to supervise patients and conversely, patients to receive the recommended care remotely. Our team therefore developed a novel tele-rehabilitation, with the primary aim to estimate the extent to which the proposed tele-rehabilitation resulted in an improvement in function during the first three-months after stroke in comparison to usual rehabilitation. Material and method This was a randomized controlled trial. We used the Late-Life Function and Disability Instrument (FDI) to assess our primary outcome (with adjustment made for baseline covariate). Results We recruited 124 participants and randomized them to receive either 12-week home-based tele-rehabilitation or usual rehabilitation. Rehabilitation Over the 12-week rehabilitation period, the intervention group spent 2246-minutes on their rehabilitation whereas the control group spent 2565-minutes. The median difference between the two groups was not statistically significant ( P = 0.649). Primary Outcome (FDI) The mean FDI frequency score post-rehabilitation for the intervention and control groups were 39.7 (SD 11.7) and 43.0 (SD 10.6) respectively. The mean FDI limitation score post-rehabilitation for the intervention group was 78.5 (SD 20.6) and that for the control group was 85.4 (SD 19.6). The unadjusted and adjusted differences in both FDI scores between the two groups were not statistically significant (Models 1 and 2). Conclusion Both groups reported comparable amount of time spent on rehabilitation and similarly positive impact on the primary outcome. Home-based tele-rehabilitation can be an effective strategy for minimizing or eliminating rehabilitation utilization barriers while achieving the same functional outcome as center-based rehabilitation. [ABSTRACT FROM AUTHOR]