[Abstract] Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation

Abstract:

Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems mostly rely on static visual representations for patients to perform motor imagination (MI) tasks, resulting in lower BCI performance. Therefore, this study innovatively used MI and high-frequency steady-state visual evoked potential (SSVEP) to construct a friendly and natural hybrid BCI paradigm. Specifically, the stimulation interface sequentially presented decomposed action pictures of the left and right hands gripping a ball, with the pictures flashing at specific stimulation frequencies (left: 34 Hz, right: 35 Hz). Integrating soft robotic glove as feedback, we established a comprehensive “peripheral – central – peripheral” hand rehabilitation system to facilitate the hand rehabilitation of patients. Filter bank common spatial pattern (FBCSP) and filter bank canonical correlation analysis (FBCCA) algorithms were used to identify MI and SSVEP signals, respectively. Additionally, to fuse the features of these two signals, we proposed a novel fusion algorithm for improving the recognition accuracy of the system. The feasibility of the proposed system was validated through online experiments involving 12 healthy subjects and 9 stroke patients, achieving accuracy rates of 95.83 ± 6.83% and 63.33 ± 10.38%, respectively. The accuracy of MI and SSVEP in 12 healthy subjects reached 81.67 ± 15.63% and 95.14 ± 7.47%, both lower than the accuracy after fusion, these results confirmed the effectiveness of the proposed algorithm. The accuracy rate was more than 50% in both healthy subjects and patients, confirming the effectiveness of the proposed system.

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[Abstract] Motor Imagery and Mental Practice in the Subacute and Chronic Phases in Upper Limb Rehabilitation after Stroke: A Systematic Review – Full Text

Abstract

Introduction. Motor imagery and mental practice can be defined as a continuous mechanism in which the subject tries to emulate a movement using cognitive processes, without actually performing the motor action. The objective of this review was to analyse and check the efficacy of motor imagery and/or mental practice as a method of rehabilitating motor function in patients that have suffered a stroke, in both subacute and chronic phases. 

Material and Methods. We performed a bibliographic search from 2009 to 2021 in the following databases, Medline (PubMed), Scopus, WOS, Cochrane, and OTSeeker. The search focused on randomized clinical trials in which the main subject was rehabilitating motor function of the upper limb in individuals that had suffered a stroke in subacute or chronic phases. 

Results. We analysed a total of 11 randomized clinical trials, with moderate and high methodological quality according to the PEDro scale. Most of the studies on subacute and chronic stages obtained statistically significant short-term results, between pre- and postintervention, in recovering function of the upper limb. 

Conclusions. Motor imagery and/or mental practice, combined with conventional therapy and/or with other techniques, can be effective in the short term in recovering upper limb motor function in patients that have suffered a stroke. More studies are needed to analyse the efficacy of this intervention during medium- and long-term follow-up.

1. Introduction

The World Health Organization (WHO) defines stroke as the clinical syndrome characterised by the rapid development of symptoms and/or local or generalised signs of neurological affectation, which lasts more than 24 hours and can even lead to death, without other apparent cause than a vascular origin [1].

A stroke causes neurological deficits in various domains of brain areas: motor, sensory/perceptive, visual, language, cognitive, intelligence, and emotion. In the motor area, the most frequent syndrome is hemiplegia or hemiparesis [2, 3]. Motor deficits occur predominantly unilaterally, contralateral to the injured side. Different areas of the brain can assume their functions through a spontaneous biological recovery and then move on to a phase of compensation. The phases of stroke have a process of change, and biomarkers will help to improve future treatments and will have to identify the effect on these phases [4].

Within this review, we can define the periods of analysis of the studies in 2 phases: the late subacute phase, which includes from 3 months to 6 months, and the chronic phase, which encompasses more than 6 months of evolution of the disease [4].

Between 30% and 66% of the individuals that have a stroke do not reach satisfactory motor recovery of the affected upper limbs following rehabilitation; this is one of the main causes of disability and produces great limitations in the activities of daily living (ADLs) [5, 6].

There are many definitions from authors that define motor imagery (MI) and mental practice (MP) as a continuous mechanism in which the subject tries to emulate a movement using cognitive processes, without actually performing the motor action [7–9]. In other words, MI consists of the mental representation of the movement, without the actual presence of it. It is a complex cognitive operation that is possible thanks to the use of sensory and perceptive processes that allow an individual to reactivate specific motor actions in the working memory [10]. In the case of MI, reactivation happens when the movement is imagined rather than performed, implying a voluntary impulse. We can generate a movement in this way without needing to perform it, intending to acquire and optimise motor skills [10]. This theory proposes that MI, the observation of the movement and the performance of the movement, share a central nervous function that corresponds among them [11].

These techniques are based on the theory of mirror neurons and demonstrate that people can produce plastic changes in the functionality of hand movements. Several studies have identified patterns in brain activation that occur during MI and found that MI largely activates regions including the frontoparietal network, subcortical and cerebellar regions, anterior intraparietal cortex, primary motor cortex (M1), bilateral supplementary area (SMA), and premotor area (PMA) [12]. Another study [13] showed that the use of MI improves a patient’s upper limb motor functions and activation areas mentioned in the previous study.

People can also develop MP using images of limb movements, which can make it easier for people that have suffered a stroke to recover motor function. Commitment and motivation are essential for participating in the MI training program [14].

The theory of sports science was the origin of MP. This theory establishes that rehearsing can improve the acquisition of motor skills [15]. MP is a method of training during which a person cognitively rehearses a physical skill using motor images, without the presence of physical movements, in order to improve the performance of motor skills [16], when an individual can access the perceptive information from the memory, MP [17].

Both MP and MI can provide an effective strategy to facilitate motor recovery in patients with brain lesions. This is especially true during the first stage of rehabilitation, when full participation in occupational and physical therapy programs may not be possible due to excessive motor weakness of the upper limbs [18]. Studies such as [19] show results indicating a preserved interhemispheric balance of patients in the subacute stage by activating cortical motor areas during MI.

Likewise, the scientific literature indicates that both MP and MI can be effective interventions in chronic phases, because there can also be limitations in the functional mobility of the upper limbs. MI might contribute to motor recovery in chronic stroke patients through the following network reorganization, i.e., promoting the efficiency of regional neuronal communication, and the reorganization of intrinsic functional connectivity of the ipsilesional M1, involving a widely distributed motor network in both hemispheres (H. [20]).

The objective of this systematic review was to analyse and check the efficacy of motor imagery and/or mental practice as a method of rehabilitating motor function in patients that have suffered a stroke, in both subacute and chronic phases. […]

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[ARTICLE] Characterization of Functional Connectivity in Chronic Stroke Subjects after Augmented Reality Training – Full Text

Abstract

Augmented reality (AR) tools have been investigated with promising outcomes in rehabilitation. Recently, some studies have addressed the neuroplasticity effects induced by this type of therapy using functional connectivity obtained from resting-state functional magnetic resonance imaging (rs-fMRI). This work aims to perform an initial assessment of possible changes in brain functional connectivity associated with the use of NeuroR, an AR system for upper limb motor rehabilitation of poststroke participants. An experimental study with a case series is presented. Three chronic stroke participants with left hemiparesis were enrolled in the study. They received eight sessions with NeuroR to provide shoulder rehabilitation exercises. Measurements of range of motion (ROM) were obtained at the beginning and end of each session, and rs-fMRI data were acquired at baseline (pretest) and after the last training session (post-test). Functional connectivity analyses of the rs-fMRI data were performed using a seed placed at the noninjured motor cortex. ROM increased in two patients who presented spastic hemiparesis in the left upper limb, with a change in muscle tone, and stayed the same (at zero angles) in one of the patients, who had the highest degree of impairment, showing flaccid hemiplegia. All participants had higher mean connectivity values in the ipsilesional brain regions associated with motor function at post-test than at pretest. Our findings show the potential of the NeuroR system to promote neuroplasticity related to AR-based therapy for motor rehabilitation in stroke participants.

1. Introduction

Stroke is a serious and common public health problem throughout the world, with high mortality rates [1]. In recent years, advances in the medical treatment of acute stroke have resulted in a decrease in the mortality rate [1,2,3]. However, many survivors remain with significant commitments [4], with upper limb impairment occurring in up to 77% of cases [5]. This is the major cause of functional dependence and the impossibility of carrying out daily life activities [6]. Therefore, health centers, stroke survivors and their families carry the burden of long-term disability.

The increasing proportion of survivors of stroke is associated with an increase in the number of individuals who persist with sensory motor deficits [3,4]. Despite intensive rehabilitation, more than half of the survivors remain with a disability affecting functional independence [7,8,9]. Poststroke rehabilitation has been a challenge because it usually requires repetitive and intensive training. Additionally, there is a shortage of health centers and health professionals to deal with this increasing population [10].

Several neurorehabilitation techniques have been used for neuromuscular rehabilitation of these types of patients [11,12,13,14,15]. Technologies such as augmented reality (AR) have been employed as new therapy tools to improve stroke rehabilitation and provide opportunities to promote the repetitive practice of activities as soon as disengagement and boredom threaten the progress in rehabilitation [4]. AR is a technology that combines the real world with virtual objects and can be manipulated by the user and controlled by specialists. AR applications constitute a safe environment for users [16], and they have the potential to be used at home with remote supervision [17].

AR applied to health and wellness fields has been evaluated in recent years and with promising outcomes in some areas, such as rehabilitation [12,16,18]. Moreover, functional magnetic resonance imaging (fMRI) assessment of brain changes resulting from the use of this type of system in rehabilitation has shown that most result in the restoration of activation patterns or relateralization to the ipsilateral hemisphere [19]. fMRI is a noninvasive and safe technique for mapping functional connectivity and brain function. Resting-state fMRI (rs-fMRI) data can be acquired using spontaneous signals obtained while the participant is resting in the scanner [20]. Data from rs-fMRI have been shown to be stable and reproducible across participants [21]. The rs-fMRI experiments are not used to map brain activation/deactivation of the brain regions during a specific task but rather to investigate brain functional connectivity [22].

Usually, functional connectivity is inferred from seed-based analysis or independent component analysis (ICA). Seed-based analysis is performed by correlating the fMRI time signals of chosen regions of interest (ROIs) with the remaining fMRI time series, disregarding other significant neural coactivation patterns [22], while ICA is a data-driven method that does not depend on any chosen ROI [23].

In this work, for AR training, we chose an AR system, NeuroR, that was initially designed to provide a virtual image to stimulate motor imagery [24]. It uses an approach similar to mirror therapy, with a virtual tridimensional arm superimposed on the impaired limb, that is, the user’s actual upper limb is substituted in the image by the virtual arm. This AR system seeks to promote neuroplasticity by performing a simple task, where the participant, sitting in front of a projection screen or TV, visualizes him/herself performing exercises of shoulder abduction and flexion with the affected arm, which is replaced by a virtual arm. The virtual arm performs a much larger movement than the real movement the patient is actually capable of executing. Actually, the success of virtual reality and AR games applied to rehabilitation seems to be based on their ability to provide false positive feedback, which is thought to promote appropriate brain reorganization [25,26]. Previous experiments showed that three of four stroke patients physically executed shoulder movement when asked to perform motor imagery from the visual feedback of the animation of the tridimensional virtual arm [24]. Another study, by Brauchle et al., with a multijoint arm exoskeleton reported changes in brain functional connectivity during motor execution and motor imagery of different feedback modalities (visual and proprioceptive) for both healthy participants and stroke survivors [27]. They evaluated the functional connectivity networks from electroencephalography data by defining a seed electrode in the ipsilesional primary motor cortex. In the same way, we hypothesized that changes in brain functional connectivity can occur, as pointed out by [27], since the participants also have visual and proprioceptive feedback while they see themselves on the computer screen and see their virtual arm moving during shoulder exercises for mental practice or motor execution.

The aim of the present work was to explore the use of rs-fMRI data to evaluate possible changes in functional brain connectivity of poststroke participants associated with the use of NeuroR in the context of motor rehabilitation. We also wanted to evaluate the spasticity of the patients and possible changes after therapy in their range of motion (ROM). A pilot study was conducted with an acute stroke participant using rs-fMRI and NeuroR training integrated into the patient’s rehabilitation program [28]. Herein, we conducted a case series with three chronic poststroke participants. Functional connectivity analyses were performed to investigate whether functional brain reorganization occurred, triggered by the mental practice of stroke participants using NeuroR. Functional brain connectivity was assessed using the seed-based method. The idea was to investigate whether the integration of the virtual arm image into the AR system stimulates neuroplasticity, making the system a new tool to aid the rehabilitation of poststroke patients. […]

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Figure 1. Sequence of frames for shoulder abduction with the NeuroR system. The virtual arm replaces the real, injured arm on the computer screen, which the patient sees as a mirror image. The virtual arm performs a much larger movement than the real movement the patient is actually capable of executing.

[Abstract] The clinical effects of brain–computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review

Abstract

Purpose

Many recent clinical studies have suggested that the combination of brain–computer interfaces (BCIs) can induce neurological recovery and improvement in motor function. In this review, we performed a systematic review and meta-analysis to evaluate the clinical effects of BCI-robot systems.

Methods

The articles published from January 2010 to December 2020 have been searched by using the databases (EMBASE, PubMed, CINAHL, EBSCO, Web of Science and manual search). The single-group studies were qualitatively described, and only the controlled-trial studies were included for the meta-analysis. The mean difference (MD) of Fugl-Meyer Assessment (FMA) scores were pooled and the random-effects model method was used to perform the meta-analysis. The PRISMA criteria were followed in current review.

Results

A total of 897 records were identified, eight single-group studies and 11 controlled-trial studies were included in our review. The systematic analysis indicated that the BCI-robot systems had a significant improvement on motor function recovery. The meta-analysis showed there were no statistic differences between BCI-robot groups and robot groups, neither in the immediate effects nor long-term effects (p > 0.05).

Conclusion

The use of BCI-robot systems has significant improvement on the motor function recovery of hemiparetic upper-limb, and there is a sustaining effect. The meta-analysis showed no statistical difference between the experimental group (BCI-robot) and the control group (robot). However, there are a few shortcomings in the experimental design of existing studies, more clinical trials need to be conducted, and the experimental design needs to be more rigorous.

• Implications for Rehabilitation
• In this review, we evaluated the clinical effects of brain–computer interface with robot on upper-limb function for post-stroke rehabilitation. After we screened the databases, 19 articles were included in this review. These articles all clinical trial research, they all used non-invasive brain–computer interfaces and upper-limb robot.
• We conducted the systematic review with nine articles, the result indicated that the BCI-robot system had a significant improvement on motor function recovery. Eleven articles were included for the meta-analysis, the result showed there were no statistic differences between BCI-robot groups and robot groups, neither in the immediate effects nor long-term effects.
• We thought the result of meta-analysis which showed no statistic difference was probably caused by the heterogenicity of clinical trial designs of these articles.
• We thought the BCI-robot systems are promising strategies for post-stroke rehabilitation. And we gave several suggestions for further research: (1) The experimental design should be more rigorous, and describe the experimental designs in detail, especially the control group intervention, to make the experiment replicability. (2) New evaluation criteria need to be established, more objective assessment such as biomechanical assessment, fMRI should be utilised as the primary outcome. (3) More clinical studies with larger sample size, novel external devices, and BCI systems need to be conducted to investigate the differences between BCI-robot system and other interventions. (4) Further research could shift the focus to the patients who are in subacute stage, to explore if the early BCI training can make a positive impact on cerebral cortical recovery.

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[ARTICLE] Emerging Limb Rehabilitation Therapy After Post-stroke Motor Recovery – Full Text

Abstract

Stroke, including hemorrhagic and ischemic stroke, refers to the blood supply disorder in the local brain tissue for various reasons (aneurysm, occlusion, etc.). It leads to regional brain circulation imbalance, neurological complications, limb motor dysfunction, aphasia, and depression. As the second-leading cause of death worldwide, stroke poses a significant threat to human life characterized by high mortality, disability, and recurrence. Therefore, the clinician has to care about the symptoms of stroke patients in the acute stage and formulate an effective postoperative rehabilitation plan to facilitate the recovery in patients. We summarize a novel application and update of the rehabilitation therapy in limb motor rehabilitation of stroke patients to provide a potential future stroke rehabilitation strategy.

Introduction

Stroke is an acute cerebrovascular disease with high morbidity, mortality, and disability. It is the second leading cause of death worldwide, accounting for 11.6% of deaths. According to the Global Burden of Disease report, an estimated 12.2 million strokes are there worldwide, resulting in 143 million disability-adjusted life years (DALYs) and 6.55 million deaths (GBD 2019 Stroke Collaborators, 2021). China has the highest number of stroke cases globally. The number of patients belonging to the low-income and youth groups is rapidly increasing, with significant gender and regional differences. According to the WHO, in 2019, stroke was the leading cause of death and DALYs in China (World Health Organization [WHO], 2020). Stroke results in lasting sensory, cognitive and visual impairment, impaired limb motor function, and eventually reduce various bodily functions (Katzan et al., 2018a,b). Motor dysfunction is the most common complication of stroke, followed by hemiplegia in about 80% of patients. Half of these symptoms will accompany patients for life and seriously affect their day-to-day activities (Kim et al., 2020). Studies have shown that hemiplegia is the leading cause of long-term disability in stroke patients from the United States, Japan, and France [(Leys et al., 2008; Ovbiagele and Nguyen-Huynh, 2011; Iso, 2021)]. The fatality rate is significantly lower than before with the progress and development of stroke treatment. However, 80% of the survivors have severe sequelae, and the disability rate is about 75% (Langhorne et al., 2018). Effective rehabilitation training can alleviate functional disability, restore the motor function in hemiplegic limbs, and accelerate the rehabilitation process in post-stroke patients (Laver et al., 2020). At present, patient rehabilitation with limb movement disorders after stroke primarily emphasizes early intervention, somehow ignoring the intervention received during the recovery and the sequelae period. There is a decline in the quality-of-life of patients and aggravation of disease conditions. Therefore, improving limb motor function of stroke patients through rehabilitation is essential. Traditional rehabilitation therapy, including massage, acupuncture, physiotherapy, and electrical stimulation, has been widely employed in the clinical practice (McCrimmon et al., 2015; Yang et al., 2016; Cabanas-Valdés et al., 2021). With the progress of science and technology, several potential neurological rehabilitations are being developed using new technologies to restore movement in the stroke patients. In this review, we summarize the novel methods and applications to restore limb motor dysfunction in stroke rehabilitation, which could provide a potential therapeutic strategy against stroke in the future.[…]

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[Abstract] Virtual Reality Assisted Motor Imagery for Early Post-Stroke Recovery: A Review

Abstract

Stroke is a serious neurological disease that may lead to long-term disabilities and even death for stroke patients worldwide. The acute period, (1 month post-stroke), is crucial for rehabilitation but the current standard clinical practice may be ineffective for patients with severe motor impairment, since most rehabilitation programs involve physical movement. Imagined movement the so-called motor imagery (MI) has been shown to activate motor areas of the brain without physical movement. MI therefore offers an opportunity for early rehabilitation of stroke patients. MI, however, is not widely employed in clinical practice due to a lack of evidence-based research. Here, we review MI-based approaches to rehabilitation of stroke patients and immersive virtual reality (VR) technologies to potentially assist MI and thus, promote recovery of motor function.

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[ARTICLE] Sensorimotor Rhythm-Brain Computer Interface With Audio-Cue, Motor Observation and Multisensory Feedback for Upper-Limb Stroke Rehabilitation: A Controlled Study – Full Text

Abstract

Several studies have shown the positive clinical effect of brain computer interface (BCI) training for stroke rehabilitation. This study investigated the efficacy of the sensorimotor rhythm (SMR)-based BCI with audio-cue, motor observation and multisensory feedback for post-stroke rehabilitation. Furthermore, we discussed the interaction between training intensity and training duration in BCI training. Twenty-four stroke patients with severe upper limb (UL) motor deficits were randomly assigned to two groups: 2-week SMR-BCI training combined with conventional treatment (BCI Group, BG, n = 12) and 2-week conventional treatment without SMR-BCI intervention (Control Group, CG, n = 12). Motor function was measured using clinical measurement scales, including Fugl-Meyer Assessment-Upper Extremities (FMA-UE; primary outcome measure), Wolf Motor Functional Test (WMFT), and Modified Barthel Index (MBI), at baseline (Week 0), post-intervention (Week 2), and follow-up week (Week 4). EEG data from patients allocated to the BG was recorded at Week 0 and Week 2 and quantified by mu suppression means event-related desynchronization (ERD) in mu rhythm (8–12 Hz). All functional assessment scores (FMA-UE, WMFT, and MBI) significantly improved at Week 2 for both groups (p < 0.05). The BG had significantly higher FMA-UE and WMFT improvement at Week 4 compared to the CG. The mu suppression of bilateral hemisphere both had a positive trend with the motor function scores at Week 2. This study proposes a new effective SMR-BCI system and demonstrates that the SMR-BCI training with audio-cue, motor observation and multisensory feedback, together with conventional therapy may promote long-lasting UL motor improvement.

Introduction

Stroke is a leading cause of mortality and disability worldwide (Johnson et al., 2019; Zhou et al., 2019). Up to 66% of stroke survivors experience upper limb (UL) motor impairments, which result in functional limitations in activities of daily living and decreased life quality (Kwah et al., 2013; Morris et al., 2013).

Electroencephalography (EEG)-based sensorimotor rhythm (SMR) brain computer interface (BCI) is a novel technology that can enhance activity-dependent neuroplasticity and restore motor function for stroke survivors (Ang et al., 2014a; Lazarou et al., 2018; Jeunet et al., 2019). SMRs can be measured over the sensorimotor cortex and modulated by actual movement, motor intention, or motor imagery (MI; Frenkel-Toledo et al., 2014; Yuan and He, 2014). Task-related modulation in EEG-based SMRs is usually manifested as event-related desynchronization (ERD) or event-related synchronization (ERS) in low-frequency components [mu rhythm (8–12 Hz) and beta rhythm (13–26 Hz)] (Pfurtscheller and Lopes da Silva, 1999), which forms the basis of neural control in EEG-based SMR-BCI (Yuan and He, 2014). Furthermore, patients with stroke or spinal cord lesions can control physical or virtual devices via SMR-BCI (Prasad et al., 2010; Caria et al., 2011; Ang et al., 2014a,b; Dodakian et al., 2014; McCrimmon et al., 2014; Ono et al., 2014; Yuan and He, 2014; Ang and Guan, 2015; Bartur et al., 2015; Pichiorri et al., 2015; Zich et al., 2015; Shu et al., 2017, 2018; Barsotti et al., 2018; Biasiucci et al., 2018; Lazarou et al., 2018; Lee et al., 2018; Norman et al., 2018; Jeunet et al., 2019; Song and Kim, 2019; Chen et al., 2020; Foong et al., 2020), which raises the possibility of SMR-BCI training for stroke rehabilitation.

Several clinical studies have investigated the effect of SMR-BCI systems and demonstrated the significantly positive outcomes on motor function improvement for stroke patients (Ang and Guan, 2015). Ramos-Murguialday et al. (2013) and Ang et al. (2014a,b) stated the BCI training had better efficacy than sham-BCI for stroke rehabilitation. Besides, Cantillo-Negrete et al. (2021) investigated the clinical and physiological effects of SMR-BCI intervention and conventional therapy for upper limb stroke rehabilitation and a revealed similar positive impact of the two therapy methods. Thus, SMR-BCI training, together with conventional therapy, is a suitable therapy option for stroke recovery.

To improve the efficacy of SMR-BCI, various SMR-BCI systems combined with sensory stimulation, motor observation (MO) have been proposed. Shu et al. (2017, 2018) and Ren et al. (2020) improved the SMR-BCI performance via proprioceptive stimulation before the motor imagery (MI) task. Choi et al. (2019), Nagai and Tanaka (2019), and Fujiwara et al. (2021) found users’ ERD/ERS was enhanced when they performed MI task with motor observation. It is recognized that enhanced ERD/ERS of stroke patients, meaning enhanced motor-related cortical activation (Pfurtscheller and Lopes da Silva, 1999; Pfurtscheller et al., 2006b), can improve users’ engagement and decoding accuracy for BCI system, which could help maximize brain plasticity and restore motor and cognitive function for stroke patients (Bundy et al., 2017; Nagai and Tanaka, 2019). Furthermore, Velasco-Álvarez et al. (2013) designed an audio-cued SMR-BCI system and showed its availability.

Besides, various neuro-feedback has been added to make SMR-BCI system a closed loop for better effect on stroke recovery. Ramos-Murguialday et al. (2013) and Ang et al. (2014a,b, 2015) demonstrated that SMR-BCI with robotic feedback was the most popular feedback method and had positive efficacy for stroke rehabilitation. Pichiorri et al. (2015) and Foong et al. (2020) observed that SMR-BCI with visual feedback showed its excellence for stroke recovery. Auditory feedback may also improve SMR-BCI performance (Nijboer et al., 2008; McCreadie et al., 2013, 2014). Several researchers found the users’ ERD/ERS was improved via SMR-BCI with proprioceptive feedback (Vukelić and Gharabaghi, 2015; Barsotti et al., 2018).

For stroke patients, the ability to keep attention is weakened due to of brain damage. To enhance the ERD/ERS and maximize the efficacy of BCI training, we propose a new SMR-BCI system with audio-cue, MO, and multisensory (auditory, visual, and robotic) feedback and investigate the effectiveness of this system.

Another urgent investigation, which should be further explored, is optimal and safe exercise prescription (e.g., training intensity and duration) (Farrell et al., 2020; Luo et al., 2020). We used the definition of training intensity and duration in a review (Antje et al., 2020) as a reference: (1) training intensity (high: five times per week vs. moderate: 2–3 times per week), (2) training duration (short: 2–3 weeks vs. long: 4–8 weeks). Most of the SMR-BCI intervention proposed fell into the pattern of moderate training intensity with long training duration, involving 10 sessions (twice a week) (McCrimmon et al., 2014), 12 sessions (three times a week) (Ang et al., 2014a; Pichiorri et al., 2015; Chen et al., 2020), 18 sessions (three times a week) (Foong et al., 2020), 20 sessions (daily training exclude weekends) (Ramos-Murguialday et al., 2013; Wu et al., 2020) and 24 sessions (twice a week) (Sebastián-Romagosa et al., 2020), which have shown positive effects on stroke rehabilitation. Few studies have addressed the pattern of high training intensity with short training duration. One clinical trial involved 10 training sessions, but each session of BCI training lasted up to 40 min (Frolov et al., 2017). As our group suggests, motor function recovery and the brain networks of stroke patients could be improved significantly by 4-week SMR-BCI intervention combined with convention training compared to only conventional treatment (Wu et al., 2020), which leads us to ponder whether a high training intensity with short duration SMR-BCI intervention will get better influence. If that works, stroke patients will restore the ability to live independently faster.

As mentioned above, there are two purposes of this study. Firstly, to investigate the efficacy of non-invasive EEG-based SMR-BCI with audio-cue, MO, and multisensory (robotic, visual, and auditory) feedback, together with conventional therapy, for upper limb rehabilitation of stroke patients. Secondly, to discuss the influence of stroke rehabilitation after a high training intensity with short duration SMR-BCI intervention. […]

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FIGURE 2
The schematic diagram of the SMR-BCI system. According to audio-cue, subjects imagine “grabbing the object” or “putting the object down” accompanied by observing the video. BCI system calculates the mu suppression of subjects’ EEG data and recognizes patients’ intention via comparing the mu suppression value with the threshold. If the purpose is identified correctly, the system will give multisensory (robotic, auditory, and visual) feedback. On the contrary, the system will still provide corresponding auditory and visual feedback, but the robot will maintain the previous state.

[ARTICLE] Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function after Stroke: A Preliminary Study – Full Text

Abstract

Background

Recently, the brain-computer interface (BCI) has seen rapid development, which may promote the recovery of motor function in chronic stroke patients.

Methods

Twelve stroke patients with severe upper limb and hand motor impairment were enrolled and randomly assigned into two groups: motor imagery (MI)-based BCI training with multimodal feedback (BCI group, n = 7) and classical motor imagery training (control group, n = 5). Motor function and electrophysiology were evaluated before and after the intervention. The Fugl-Meyer assessment-upper extremity (FMA-UE) is the primary outcome measure. Secondary outcome measures include an increase in wrist active extension or surface electromyography (the amplitude and cocontraction of extensor carpi radialis during movement), the action research arm test (ARAT), the motor status scale (MSS), and Barthel index (BI). Time-frequency analysis and power spectral analysis were used to reflect the electroencephalogram (EEG) change before and after the intervention.

Results

Compared with the baseline, the FMA-UE score increased significantly in the BCI group (p = 0.006). MSS scores improved significantly in both groups, while ARAT did not improve significantly. In addition, before the intervention, all patients could not actively extend their wrists or just had muscle contractions. After the intervention, four patients regained the ability to extend their paretic wrists (two in each group). The amplitude and area under the curve of extensor carpi radialis improved to some extent, but there was no statistical significance between the groups.

Conclusion

MI-based BCI combined with sensory and visual feedback might improve severe upper limb and hand impairment in chronic stroke patients, showing the potential for application in rehabilitation medicine.

1. Introduction

Stroke remains the leading cause of long-term disability, among which upper limb paralysis is particularly common and prevents patients from returning to self-care [1]. Rehabilitation has been shown to recover some motor functions from stroke. Several clinical controlled trials have confirmed that it is not hard to regain partial control of the shoulder and elbow from positive and intensive rehabilitation training [2–4]. However, it is difficult to improve the recovery of the control of severely paretic wrist and fingers, which prevents patients from returning to family and society [5]. Hence, there exists a pressing need to seek new interventions to improve the motor function of the paralysed upper limb. Sensory disorders, including deep and superficial sensory, are also common in stroke patients [6–8]. Studies have shown that the recovery of sensory impairments promotes the recovery of motor impairments; hence, increasing sensory input and output during exercise training may play an important role [9–11].

The brain-computer interface (BCI) is new technology that has been developing rapidly, and it directly acts on the central nervous system. By collecting and analysing the biological electrical signals from the human brain, BCI technology could establish a direct communication and control pathway between the human brain and computers or other electronic devices [12]. This unconventional pathway has the potential to help stroke patients regain movement [13–15]. There are many ways to generate brain signals, among which motor imagery (MI) is more common [16,17]. The phenomenon of event-related desynchronisation (ERD)/event-related synchronisation (ERS) occurs when patients perform motor imagination [18]. In fact, many rehabilitation interventions are not appropriate for severely paralysed stroke patients, which means that these patients are excluded from therapy [19]. MI requires patients to have good cognitive function and can be carried out after standardised training and guidance, even for patients with severe hemiplegia [20–22]. Previous clinical studies have shown that MI or a combination of it and physical therapy can promote recovery of the upper extremities, which is important for daily activities and skills [23–25]. EEG is widely used because of its noninvasive, portability, and good temporal resolution. Researchers have demonstrated that MI-based BCI has the potential to be used in stroke rehabilitation [26–28].

BCI training is often combined with virtual reality (VR), which provides a three-dimensional visual interaction during training [29]. Adding VR to BCI might arouse patients’ interest, which is conducive to improving patient compliance [30]. Adverse reactions such as dizziness and eyestrain might occur during treatment.

In previous research, BCI was mostly used as an intermediate medium to output signals that can control external devices, such as exoskeleton robots and functional electrical stimulation (FES) [31,32]. Studies have confirmed its clinical efficacy, and the improvement has a certain degree of continuity [33]. In our previous study [34], continuous passive motion (CPM) was used as an external device to improve wrist extension in chronic stroke patients. The results showed that after six weeks of interventions, 81% of the patients who completed the study had regained wrist extension. Meanwhile, the spatial and spectrum pattern of the EEG signal also improved after the training. However, this was before and after study and did not set up a control group. Also, external devices might have some insufficiencies, such as economic costs and patient adaptability. Patients might mainly focus on internal motor imagery during MI-based BCI training if external devices do not exist. In the current study, we further investigated the effect of sensory, visual, and EEG feedback on the recovery of upper limb motor function in chronic stroke patients. […]

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Figure 1. Illustration of the MI-BCI intervention procedures combined with multimodal feedback.

[Abstract] Brain-Computer Interface System for Hand Rehabilitation

Abstract

This paper describes a brain-computer interface (Bel) system for hand rehabilitation. The system is composed of an EEG amplifier, a desktop computer, and a hand orthosis. A healthy subject participated in the experiment. When performing hand movement tasks, his EEG signals were recorded. A support-vector machine (SVM)-based classifier was trained using the processed data. Then, the system with the learned SVM-classifier was tested using test data. As a result, it was confirmed that the classifier had test accuracy of 73.3 %, and that fingers movements (extension and flexion) of the experimental subj ect were performed by the hand orthosis which was activated by the subject’s intention (motor imagery).

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[ARTICLE] Therapeutic Instrumental Music Training and Motor Imagery in Post-Stroke Upper-Extremity Rehabilitation: A Randomized-Controlled Pilot Study – Full Text

Abstract

Objective

To investigate the potential benefits of three Therapeutic Instrumental Music Performance (TIMP)-based interventions in rehabilitation of the affected upper-extremity [UE] for adults with chronic post-stroke hemiparesis.

Design

Randomized-controlled pilot study

Setting

University research facility

Participants

Thirty community-dwelling volunteers [16 male/14 female; ages 33-76; mean age =55.9] began and completed the protocol. All participants had sustained a unilateral stroke > 6 months prior to enrollment [mean time post-stroke =66.9 months].

Interventions

Two baseline assessments, a minimum of one week apart; nine intervention sessions (3x/wk for 3 wks), in which rhythmically-cued, functional arm movements were mapped onto musical instruments; one post-test following the final intervention. Participants were block-randomized to one of three conditions: Group 1 – 45 minutes TIMP; Group 2 – 30 minutes TIMP, 15 minutes metronome-cued motor imagery (TIMP+cMI); Group 3 – 30 minutes TIMP, 15 minutes motor imagery without cues (TIMP+MI). Assessors and investigators were blinded to group assignment.

Main Outcome Measures

Fugl-Meyer Upper-Extremity (FM-UE); Wolf Motor Function Test- Functional Ability Scale (WMFT-FAS)

Secondary Measures

Motor Activity Log (MAL) – Amount of Use Scale; Trunk Impairment Scale.

Results

All groups made statistically significant gains on the FM-UE (TIMP, p=.005, r=.63; TIMP+cMI, p=.007, r=.63; TIMP+MI, p=.007, r=.61) and the WMFT-FAS (TIMP, p=.024, r=.53; TIMP+cMI, p=.008, r=.60; TIMP+MI, p=.008, r=.63). Comparing between-group percent change differences, on the FM-UE, TIMP scored significantly higher than TIMP+cMI (p=.032, r=.57), but not TIMP+MI. There were no differences in improvement on WMFT-FAS across conditions. On the MAL, gains were significant for TIMP (p=.030, r=.54) and TIMP+MI (p =.007, r=.63).

Conclusion

TIMP-based techniques, with and without motor imagery, led to significant improvements in paretic arm control on primary outcomes. Replacing a physical training segment with imagery-based training resulted in similar improvements; however, synchronizing internal and external cues during auditory-cued motor imagery may pose additional sensorimotor integration challenges.

Introduction

Among all neurological disorders, stroke contributes the largest proportion of disability-adjusted life-years (42.2%)¹. As millions of individuals cope with functional health loss, the economic burden due to post-stroke care continues to rise². People living with the effects of stroke score consistently low on life satisfaction, perceived health, and health-related quality of life³.

While a stroke may generate a number of disabling conditions, the most common sequela is motor impairment⁴. Volitional movements are often segmented, slow, and indirect⁵. If a functional threshold of recovery is not achieved, the affected individual may resort to compensatory movements⁶, and paretic learned non-use may ensue⁷.

Rehabilitation is thought to modulate motor recovery by interacting with underlying biological processes primarily during the first six months following a stroke⁸. Many individuals at the chronic stage no longer receive rehabilitation services; however, evidence is growing of significant treatment benefits during this phase^9-11. It is critical for persons at the chronic stage to continue to engage in rehabilitation that focuses on effective learning and training strategies, because behavioral experience has been shown to modify functional alterations in spared regions of the brain.¹² These strategies may include enhanced movement feedback, and opportunities for more independent training allowing for higher intensity rates. The music and imagery-based techniques in this study have been shown to address these needs^13,14 but have not been researched in integrated applications. Our study tries to address this gap by studying music-based interventions alone and in combination with imagery-based motor training.

Studies have shown beneficial effects of music interventions on motor control. The provision of structured temporal auditory information has been shown to lend significant stability to kinematic parameters during hemiparetic arm reaching^15,16. Studies in mapping functional movements on musical instruments found significant gains in hemiparetic arm rehabilitation¹³. The Neurologic Music Therapy technique¹⁷ used in this study, Therapeutic Instrumental Music Performance (TIMP), was developed through two research streams: Rhythmic Auditory Stimulation, which provides predictable anticipatory rhythmic cues to entrain movement^18,19, and Sonification, which provides augmented auditory feedback by mapping sound on kinematic parameters²⁰.

MI activates motor regions in the brain similar to physical practice²¹ and is widely used in sports training, but applications in neurorehabilitation have been more limited. For example, researchers found enhanced treatment efficacy when modified constraint-induced therapy was followed by MI practice^14,22. MI training offers many advantages, including more autonomous training time, potentially increasing the rate and intensity of therapy applications without additional physical load. However, a frequently reported shortcoming refers to reduced motor imagery abilities associated with decline in cognitive function. Thus, effective MI may need to be paired with a physically active component that produces a robust and stable representation of movement retainable during mental rehearsal. Combining a novel, music-based motor intervention with MI presents a potentially attractive means to enhance and extend the effectiveness of rehabilitation. TIMP may be such an intervention due to its augmented spatiotemporal structure and its rich sensory-based feedback-feedforward environment.

Therefore, the central goal of this study was to investigate if TIMP paired with MI and TIMP paired with cued MI (cMI), in which a rhythmic auditory cue used during active training was retained during imagery, showed better motor outcomes than TIMP alone. The effectiveness of all three conditions against no training was investigated by comparing intervention outcomes to a stable baseline control, determined by comparing two baseline measurements before interventions commenced. Based on previous research findings (e.g. ^14,22), it was anticipated that there would be greater reductions in impairment and improvements in functional capacity using MI in conjunction with active TIMP practice. It was also anticipated that cMI, retaining an auditory timing cue, would yield superior results to MI without an external cue.[…]

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