Posts Tagged Neurorehabilitation

[Abstract] Pushing the limits of recovery in chronic stroke survivors: User perceptions of the Queen Square Upper Limb Neurorehabilitation Programme – Full Text PDF

Abstract

Introduction: The Queen Square Upper Limb (QSUL) Neurorehabilitation Programme is a clinical service within the National Health Service in the United Kingdom that provides 90 hours of therapy over three weeks to stroke survivors with persistent upper limb impairment. This study aimed to explore the perceptions of participants of this programme, including clinicians, stroke survivors and carers.

Design: Descriptive qualitative.

Setting: Clinical outpatient neurorehabilitation service.

Participants: Clinicians (physiotherapists, occupational therapists, rehabilitation assistants) involved in the delivery of the QSUL Programme, as well as stroke survivors and carers who had participated in the programme were purposively sampled. Each focus group followed a series of semi-structured, open questions that were tailored to the clinical or stroke group. One independent researcher facilitated all focus groups, which were audio-recorded, transcribed verbatim and analysed by four researchers using a thematic approach to identify main themes.

Results: Four focus groups were completed: three including stroke survivors (n = 16) and carers (n = 2), and one including clinicians (n = 11). The main stroke survivor themes related to psychosocial aspects of the programme (″ you feel valued as an individual ″), as well as the behavioural training provided (″ gruelling, yet rewarding& [Prime]). The main clinician themes also included psychosocial aspects of the programme (″ patient driven ethos − no barriers, no rules ″), and knowledge, skills and resources of clinicians (″ it is more than intensity, it is complex ″).

Conclusions: As an intervention, the QSUL Programme is both comprehensive and complex. The impact of participation in the programme spans psychosocial and behavioural domains from the perspectives of both the stroke survivor and clinician.

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[ARTICLE] Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people – Full Text

Abstract

Background

Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain activity. Thus, this study aimed to investigate the effects of robotic assistance (RA) during treadmill walking (TW) on cortical activity and the relationship between RA-related changes of cortical activity and biomechanical gait characteristics.

Methods

Twelve healthy, right-handed volunteers (9 females; M = 25 ± 4 years) performed unassisted walking (UAW) and robot-assisted walking (RAW) trials on a treadmill, at 2.8 km/h, in a randomized, within-subject design. Ground reaction forces (GRFs) provided information regarding the individual gait patterns, while brain activity was examined by measuring cerebral hemodynamic changes in brain regions associated with the cortical locomotor network, including the sensorimotor cortex (SMC), premotor cortex (PMC) and supplementary motor area (SMA), using functional near-infrared spectroscopy (fNIRS).

Results

A statistically significant increase in brain activity was observed in the SMC compared with the PMC and SMA (p < 0.05), and a classical double bump in the vertical GRF was observed during both UAW and RAW throughout the stance phase. However, intraindividual gait variability increased significantly with RA and was correlated with increased brain activity in the SMC (p = 0.05; r = 0.57).

Conclusions

On the one hand, robotic guidance could generate sensory feedback that promotes active participation, leading to increased gait variability and somatosensory brain activity. On the other hand, changes in brain activity and biomechanical gait characteristics may also be due to the sensory feedback of the robot, which disrupts the cortical network of automated walking in healthy individuals. More comprehensive neurophysiological studies both in laboratory and in clinical settings are necessary to investigate the entire brain network associated with RAW.

Background

Safe and independent locomotion represents a fundamental motor function for humans that is essential for self-contained living and good quality of life [1,2,3,4,5]. Locomotion requires the ability to coordinate a number of different muscles acting on different joints [6,7,8], which are guided by cortical and subcortical brain structures within the locomotor network [9]. Structural and functional changes within the locomotor network are often accompanied by gait and balance impairments which are frequently considered to be the most significant concerns in individuals suffering from brain injuries or neurological diseases [51011]. Reduced walking speeds and step lengths [12] as well as non-optimal amount of gait variability [13,14,15] are common symptoms associated with gait impairments that increase the risk of falling [16].

In addition to manual-assisted therapy, robotic neurorehabilitation has often been applied in recent years [1718] because it provides early, intensive, task-specific and multi-sensory training which is thought to be effective for balance and gait recovery [171920]. Depending on the severity of the disease, movements can be completely guided or assisted, tailored to individual needs [17], using either stationary robotic systems or wearable powered exoskeletons.

Previous studies investigated the effectiveness of robot-assisted gait training (RAGT) in patients suffering from stroke [2122], multiple sclerosis [23,24,25,26], Parkinson’s disease [2728], traumatic brain injury [29] or spinal cord injury [30,31,32]. Positive effects of RAGT on walking speed [3334], leg muscle force [23] step length, and gait symmetry [2935] were reported. However, the results of different studies are difficult to summarize due to the lack of consistency in protocols and settings of robotic-assisted treatments (e.g., amount and frequency of training sessions, amount and type of provided robotic support) as well as fragmentary knowledge of the effects on functional brain reorganization, motor recovery and their relation [3637]. Therefore, it is currently a huge challenge to draw guidelines for robotic rehabilitation protocols [2236,37,38]. To design prologned personalized training protocols in robotic rehabilitation to maximize individual treatment effects [37], it is crucial to increase the understanding of changes in locomotor patterns [39] and brain signals [40] underlying RAGT and how they are related [3641].

A series of studies investigated the effects of robotic assistance (RA) on biomechanical gait patterns in healthy people [3942,43,44]. On one side, altered gait patterns were reported during robot-assisted walking (RAW) compared to unassisted walking (UAW), in particular, substantially higher muscle activity in the quadriceps, gluteus and adductor longus leg muscles and lower muscle activity in the gastrocnemius and tibialis anterior ankle muscles [3942] as well as reduced  lower-body joint angles due to the little medial-lateral hip movements [45,46,47]. On the other side, similar muscle activation patterns were observed during RAW compared to UAW [444849], indicating that robotic devices allow physiological muscle activation patterns during gait [48]. However, it is hypothesized that the ability to execute a physiological gait pattern depends on how the training parameters such as body weight support (BWS), guidance force (GF) or kinematic restrictions in the robotic devices are set [444850]. For example, Aurich-Schuler et al. [48] reported that the movements of the trunk and pelvis are more similar to UAW on a treadmill when the pelvis is not fixed during RAW, indicating that differences in musle activity and kinematic gait characteristics between RAW and UAW are due to the reduction in degrees of freedom that user’s experience while walking in the robotic device [45]. In line with this, a clinical concern that is often raised with respect to RAW is the lack of gait variability [454850]. It is assumed that since the robotic systems are often operated with 100% GF, which means that the devices attempt to force a particular gait pattern regardless of the user’s intentions, the user lacks the ability to vary and adapt his gait patterns [45]. Contrary to this, Hidler et al. [45] observed differences in kinematic gait patterns between subsequent steps during RAW, as demonstrated by variability in relative knee and hip movements. Nevertheless, Gizzi et al. [49] showed that the muscular activity during RAW was clearly more stereotyped and similar among individuals compared to UAW. They concluded that RAW provides a therapeutic approach to restore and improve walking that is more repeatable and standardized than approaches based on exercising during UAW [49].

In addition to biomechanical gait changes, insights into brain activity and intervention-related changes in brain activity that relate to gait responses, will contribute to the optimization of therapy interventions [4151]. Whereas the application of functional magnetic resonance imaging (fMRI), considered as gold standard for the assessment of activity in cortical and subcortical structures, is restricted due to the vulnerability for movement artifacts and the range of motion in the scanner [52], functional near infrared spectroscopy (fNIRS) is affordable and easily implementable in a portable system, less susceptible to motion artifacts, thus facilitation a wider range of application with special cohorts (e.g., children, patients) and in everyday environments (e.g., during a therapeutic session of RAW or UAW) [5354]. Although with lower resolution compared to fMRI [55], fNIRS also relies on the principle of neurovascular coupling and allows the indirect evaluation of cortical activation [5657] based on hemodynamic changes which are analogous to the blood-oxygenation-level-dependent responses measured by fMRI [56]. Despite limited depth sensitivity, which restricts the measurement of brain activity to cortical layers, it is a promising tool to investigate the contribution of cortical areas to the neuromotor control of gross motor skills, such as walking [53]. Regarding the cortical correlates of walking, numerous studies identified either increaesed oxygenated hemoglobin (Hboxy) concentration changes in the sensorimotor cortex (SMC) by using fNIRS [5357,58,59] or suppressed alpha and beta power in sensorimotor areas by using electroencephalography (EEG) [60,61,62] demonstrating that motor cortex and corticospinal tract contribute directly to the muscle activity of locomotion [63]. However, brain activity during RAW [366164,65,66,67,68], especially in patients [6970] or by using fNIRS [6869], is rarely studied [71].

Analyzing the effects of RA on brain activity in healthy volunteers, Knaepen et al. [36] reported significantly suppressed alpha and beta rhythms in the right sensory cortex during UAW compared to RAW with 100% GF and 0% BWS. Thus, significantly larger involvement of the SMC during UAW compared to RAW were concluded [36]. In contrast, increases of Hboxy were observed in motor areas during RAW compared UAW, leading to the conclusion that RA facilitated increased cortical activation within locomotor control systems [68]. Furthermore, Simis et al. [69] demonstrated the feasibility of fNIRS to evaluate the real-time activation of the primary motor cortex (M1) in both hemispheres during RAW in patients suffering from spinal cord injury. Two out of three patients exhibited enhanced M1 activation during RAW compared with standing which indicate the enhanced involvement of motor cortical areas in walking with RA [69].

To summarize, previous studies mostly focused the effects of RA on either gait characteristics or brain activity. Combined measurements investigating the effects of RA on both biomechanical and hemodynamic patterns might help for a better understanding of the neurophysiological mechanisms underlying gait and gait disorders as well as the effectiveness of robotic rehabilitation on motor recovery [3771]. Up to now, no consensus exists regarding how robotic devices should be designed, controlled or adjusted (i.e., device settings, such as the level of support) for synergistic interactions with the human body to achieve optimal neurorehabilitation [3772]. Therefore, further research concerning behavioral and neurophysiological mechanisms underlying RAW as well as the modulatory effect of RAGT on neuroplasticy and gait recovery are required giving the fact that such knowledge is of clinical relevance for the development of gait rehabilitation strategies.

Consequently, the central purpose of this study was to investigate both gait characteristics and hemodynamic activity during RAW to identify RAW-related changes in brain activity and their relationship to gait responses. Assuming that sensorimotor areas play a pivotal role within the cortical network of automatic gait [953] and that RA affects gait and brain patterns in young, healthy volunteers [39424568], we hypothesized that RA result in both altered gait and brain activity patterns. Based on previous studies, more stereotypical gait characteristics with less inter- and intraindividual variability are expected during RAW due to 100% GF and the fixed pelvis compared to UAW [4548], wheares brain activity in SMC can be either decreased [36] or increased [68].

Methods

This study was performed in accordance with the Declaration of Helsinki. Experimental procedures were performed in accordance with the recommendations of the Deutsche Gesellschaft für Psychologie and were approved by the ethical committee of the Medical Association Hessen in Frankfurt (Germany). The participants were informed about all relevant study-related contents and gave their written consent prior to the initiation of the experiment.

Participants

Twelve healthy subjects (9 female, 3 male; aged 25 ± 4 years), without any gait pathologies and free of extremity injuries, were recruited to participate in this study. All participants were right-handed, according to the Edinburg handedness-scale [73], without any neurological or psychological disorders and with normal or corrected-to-normal vision. All participants were requested to disclose pre-existing neurological and psychological conditions, medical conditions, drug intake, and alcohol or caffeine intake during the preceding week.

Experimental equipment

The Lokomat (Hocoma AG, Volketswil, Switzerland) is a robotic gait-orthosis, consisting of a motorized treadmill and a BWS system. Two robotic actuators can guide the knee and hip joints of participants to match pre-programmed gait patterns, which were derived from average joint trajectories of healthy walkers, using a GF ranging from 0 to 100% [7475] (Fig. 1a). Kinematic trajectories can be adjusted to each individual’s size and step preferences [45]. The BWS was adjusted to 30% body weight for each participant, and the control mode was set to provide 100% guidance [64].

figure1

Montage and Setup. a Participant during robot-assisted walking (RAW), with functional near-infrared spectroscopy (fNIRS) montage. b fNIRS montage; S = Sources; D = Detectors c Classification of regions of interest (ROI): supplementary motor area/premotor cortex  (SMA/PMC) and sensorimotor cortex (SMC) 

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[ARTICLE] Musical Sonification of Arm Movements in Stroke Rehabilitation Yields Limited Benefits – Full Text

Neurologic music therapy in rehabilitation of stroke patients has been shown to be a promising supplement to the often strenuous conventional rehabilitation strategies. The aim of this study was threefold: (i) replicate results from a previous study with a sample from one clinic (henceforth called Site 1; N = 12) using an already established recording system, and (ii) conceptually replicate previous findings with a less costly hand-tracking system in Site 2 (N = 30), and (iii) compare both sub-studies’ outcomes to estimate the efficiency of neurologic music therapy. Stroke patients in both sites were randomly assigned to treatment or control groups and received daily training of guided sequential upper limb movements additional to their standard stroke rehabilitation protocol. Treatment groups received sonification (i.e., changes in musical pitch) of their movements when they moved their affected hand up and down to reproduce a sequence of the first six notes of a C major scale. Controls received the same movement protocol, however, without auditory feedback. Sensors at the upper arm and the forearm (Xsens) or an optic sensor device (Leapmotion) allowed to measure kinematics of movements and movement smoothness. Behavioral measures pre and post intervention included the Fugl-Meyer assessment (FMA) and the Stroke Impact Scale (SIS) and movement data. Bayesian regression did not show evidence supporting an additional effect of sonification on clinical mobility assessments. However, combined movement data from both sites showed slight improvements in movement smoothness for the treatment group, and an advantage for one of the two motion capturing systems. Exploratory analyses of EEG-EMG phase coherence during movement of the paretic arm in a subset of patients suggested increases in cortico-muscular phase coherence specifically in the ipsilesional hemisphere after sonification therapy, but not after standard rehabilitation therapy. Our findings show that musical sonification is a viable treatment supplement to current neurorehabilitation methods, with limited clinical benefits. However, given patients’ enthusiasm during training and the low hardware price of one of the systems it may be considered as an add-on home-based neurorehabilitation therapy.

Introduction

Stroke survivors frequently suffer from severe disabilities. Stroke may lead to impairments in motor and sensory systems, emotion regulation, language perception, and cognitive functions (Morris and Taub, 2008). Impaired arm function caused by gross-motor disability is also a common consequence of stroke immensely affecting quality of life in a considerable number of patients. In this case, regaining control over body movements is one of the crucial components in post-stroke recovery. There is an urgent need for effective motor rehabilitation approaches to improve quality of life in stroke survivors. Different therapeutic approaches such as Constraint Induced Movement Therapy (CIMT), mental practice, robot-aided therapy, electromyographic biofeedback, and repetitive task training have been applied to improve arm function after stroke (Langhorne et al., 2009). Of note, in a recent review it has been suggested that neurologic music therapy might be more effective than conventional physiotherapy (for a recent review see Sihvonen et al., 2017).

Motivational factors seem to play an important role for the beneficial effects of neurologic music therapy. From the patients’ informal descriptions of their experience with music-supported training, it appears that this is frequently highly enjoyable and a highlight of their rehabilitation process, regardless of the form of auditory stimulation, be it piano tones, or sonification of movement with other timbres [for a review see Altenmüller and Stewart (2018)]. However, effects of music supported therapy in stroke rehabilitation are not always consistent. In a recent review, seven controlled studies that evaluated the efficacy of music as an add-on therapy in stroke rehabilitation were identified (Sihvonen et al., 2017). In these studies, training of finger dexterity of the paretic hand was done using either a piano-keyboard, or, for wrist movements, drum-pads tuned to a C major scale. Superiority of the music group over fine motor training without music and over conventional physiotherapy was evident in one study after intervention comprising five 30-min sessions per week for 3 weeks (Schneider et al., 2010). The beneficial effect seen in the music group could be specifically attributed to the musical component of the training rather than the motor training per se, since patients practicing with mute instruments remained inferior to the music group. Here, the Fugl-Meyer Assessment (FMA) was applied before and after 20 sessions of either music supported therapy on a keyboard or equivalent therapy without sound. FMA scores of the motor functions of the upper limb improved by 16 in the music group and by 5 in the control group, both improvements being statistically significant although to a lesser degree in the control group (p = 0.02 vs. p = 0.04; Tong et al. (2015)).

With regard to the neurophysiological mechanisms of neurological music therapy, it was demonstrated that patients undergoing music supported therapy not only regained their motor abilities at a faster rate but also improved in timing, precision and smoothness of fine motor skills as well as showing increases in neuronal connectivity between sensorimotor and auditory cortices as assessed by means of EEG-EEG-coherence (Altenmüller et al., 2009Schneider et al., 2010).

These findings are corroborated by a case study of a patient who underwent music supported training 20 months after suffering a stroke. Along with the clinical improvement, functional magnetic resonance imaging (fMRI) demonstrated activation of motor and premotor areas, when listening to simple piano tunes, thus providing additional evidence for the establishment of an auditory-sensorimotor co-representation due to the training procedure (Rojo et al., 2011). Likewise, in a larger group of 20 chronic stroke patients, increases in motor cortex excitability following 4 weeks of music-supported therapy were demonstrated using transcranial magnetic stimulation (TMS), which were accompanied by marked improvements of fine motor skills (Amengual et al., 2013).

In addition to functional reorganization of the auditory-sensorimotor network, recent findings have reported changes in cognition and emotion after music-supported therapy in chronic stroke patients. Fujioka et al. (2018) demonstrated in a 10-week-long randomized controlled trial (RCT), including 14 patients with music supported therapy and 14 patients receiving conventional physiotherapy, that both groups only showed minor improvements. However, the music group performed significantly better in the trail making test, indicating an improvement in cognitive flexibility, and furthermore showed enhanced social and communal participation in the Stroke Impairment Scale and in PANAS (Positive and Negative Affect Schedule, Watson et al., 1988), lending support to the prosocial and motivational effects of music. In another RCT with an intervention of only 4 weeks, Grau-Sánchez et al. (2018) demonstrated no superiority in fine motor skills in the music group as compared to a control group, but instead an increase in general quality of life as assessed by the Profile of Mood states and the stroke specific quality of live questionnaire. Despite growing evidence, the neurophysiological mechanisms of neurological music therapy remain poorly understood.

Most of the existing studies on music-supported therapy have focused on rehabilitation of fine motor functions of the hand. Much less evidence exists on post-stroke rehabilitation of gross motor functions of the upper limbs. In a previous study we thus developed a movement sonification therapy in order to train upper arm and shoulder functions (Scholz et al., 2015). Gross movements of the arm were transformed into discrete sounds, providing a continuous feedback in a melodic way, tuned to a major scale (i.e., patients could use movements of their paretic arms as a musical instrument). In this way, sound perception substituted for defective proprioception. In a first pilot study in subacute stroke patients we were able to demonstrate that musical sonification therapy reduced joint pain in the Fugl-Meyer pain subscale (difference between groups: −10; d = 1.96) and improved smoothness of movements (d = 1.16) in comparison to movement therapy without sound (Scholz et al., 2016). Here, we extend these findings by comparing the effects of the established musical sonification setup (Scholz et al., 2016) with a newly developed, less expensive sonification device in a group of subacute stroke patients with upper limb motor impairments. The only apparent differences between both data acquisition methods were the improved sound quality and the loss of need to strap sensors to patient limbs. In order to further elucidate the neurophysiological underpinnings of musical sonification therapy we simultaneously recorded EEG and EMG data from a subset of patients to analyze cortico-muscular phase coherence during upper limb movements (Chen et al., 2018Pan et al., 2018). According to previous studies (Pan et al., 2018) we hypothesized that cortico-muscular phase coherence increases in the ipsilesional hemisphere after musical sonification therapy. […]

 

Continue —->  Frontiers | Musical Sonification of Arm Movements in Stroke Rehabilitation Yields Limited Benefits | Neuroscience

Figure 2. Experimental setup. (A) three-dimensional space (the Leapmotion controller at Site 2 was placed on the board at the position marked in purple), with axis labels describing qualitative sound changes when the hand was moved relative to the frame (and hence, the body). (B) Xsens sensors as used at Site 1, attached to wrist and upper arm of patient. (C) Leapmotion controller as used at Site 2, with the space axes superimposed. Panel (A) taken from Scholz et al. (2016).

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[Research] Vagal nerve stimulation may improve post-stroke motor recovery

The Vagus Nerve Stimulation (VNS) may promote reorganization of motor networks via engaging a variety of molecular and neuronal mechanisms through ascending neuromodulatory systems. A recently published review from Frontiers in Neuroscience (N.D. Engineer et al. Targeted Vagus nerve stimulation for rehabilitation after stroke, Front Neurosci. 2019, 29;13:280) has laid out how recent experimental and clinical studies are providing increasing evidence for a beneficial effect of vagus nerve stimulation for the motor recovery after stroke of both, ischemic and hemorrhagic origin. Two multi-site, randomized controlled pilot trials have suggested that when paired with neurorehabilitation, VNS stimulation may generate temporally precise neuromodulatory feedback within the synaptic eligibility trace and may hence, drive synaptic plasticity.

  1. A single-blinded, randomized feasibility study evaluating VNS paired with motor rehabilitation was performed by Dawson et al. (2016) in 20 participants > 6 months after ischemic stroke who had moderate to severe upper limb weakness. Subjects were randomized to VNS paired with rehabilitation (n = 9; implanted) or rehabilitation alone (n = 11; not implanted). VNS was triggered by a physiotherapist pushing a button during task-specific movements. The main outcome measures were a change in upper extremity Fugl-Meyer Assessment (FMAUE) score and response rate – FMA-UE change _6 points was considered clinically meaningful. After 6 weeks of in-clinic rehabilitation, participants in the paired VNS group showed a 9.6-point improvement from baseline while the control group improved by 3 points in the per-protocol analysis (between group difference = 6.5 points, CI: 0.4 to 12.6, p = 0.038). The response rates were 66 and 36.4% in VNS and control groups, respectively. No serious adverse device effects were reported.
  2. The second study was a multicenter, fully blinded and randomized study (Kimberley et al., 2018). All participants were implanted with the VNS device, which allowed the control group to crossover to receive paired VNS therapy after completion of blinded follow-up. This permitted a within subject comparison of gains. To evaluate the lasting effects of VNS stimulation combined with home-based physiotherapy was included as part of the study. Seventeen participants who had moderate to severe upper extremity impairment after stroke were enrolled at four sites. Both groups had 1 month of at-home exercises with no VNS followed by 2 months of home-based therapy. During home therapy, participants in both groups activated the VNS device at the start of each 30-min session via a magnetswipe over the implanted pulse generator to deliver either Active or Paired VNS (0.8 mA) or Control VNS (0 mA), respectively. After 2 months of home-based therapy, thepaired VNS group continued the VNS therapy while the Control Group switched over to receive paired VNS. After 6 weeks of in-clinic therapy, the FMA-UE score increased by 7.6 points for the VNS group and 5.3 points for controls. Three months after the end of in-clinic therapy (post-90), the FMA-UE increased by 9.5 in the paired VNS group and 3.8 points in controls. At post-90, response rate (FMA-UE change _6 points) was 88% in the VNS group and 33% in controls (p = 0.03).

Noteworthy in both studies seemed the greater improvement of the upper limb function when physiotherapy was applied simultaneously with vagal nerve stimulation. VNS likely supported the recovery of upper limb functions via activation of multiple neuromodulatory networks that regulate synaptic plasticity. This may include the noradrenergic, cholinergic, and serotonergic systems (Nichols et al., 2011; Hulsey et al., 2017). These neuromodulators, in turn, act synergistically to alter spike-timing dependent plasticity (STDP) properties in active networks. The studies above align well with the time scale of the synaptic eligibility trace. VNS may drive temporally precise neuromodulatory release to reinforce ongoing neural activity related to the therapeutic event. An open question is whether similar improvement can be achieved using non-invasive vagal nerve stimulation. To this moment, the identifying and consistently delivering stimulation within a particular range of parameters appears to be of greater challenge with non-invasive VNS than with the implanted VNS device.

Physiotherapy combined with vagal nerve stimulation seems to be a new and promising approach to enhance the functional recovery after stroke.

Key points:

  • Vagus Nerve Stimulation (VNS) may promote reorganization of motor networks
  • Experimental and clinical studies pointed towards a beneficial effect for the motor recovery after stroke
  • VNS may drive temporally precise neuromodulatory release to reinforce ongoing neural activity

References:

Targeted Vagus Nerve Stimulation for Rehabilitation After Stroke. https://www.ncbi.nlm.nih.gov/pubmed/30983963

 

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[WEB SITE] UiTM’s Fazah and her VR Breakthrough to Redefining NeuroRehabilitation

While gaming devices can be used as a treatment for stroke rehabilitation, the “off the shelf” games were not specific to focus on the rehabilitation goals. Sometimes, therapy was limited due to various constraints which include affordability, human resources and infrastructure, adding challenges to deliver the rehabilitation programme.

This became a driving force to Universiti Teknologi MARA (UiTM), Malaysia’s rehabilitation physician, Associate Professor Dr. Fazah Akhtar Hanapiah, to design her serious games with a specific function which was more virtual, moving away from the physical – the Medical Rehabilitation Virtual Reality (MRVR) platform.

A medical doctor at the Faculty of Medicine UiTM, Malaysia and also a fellow at I-PPerForM (Institute of Pathology, Laboratory and Forensic Medicine), she wanted “to improve the outcome of patients with complex disability and see them get better”. For sustainability of such projects, a good eco-system is required between R&D and deliverance to the required community.  VR can address the gaps to deliver rehabilitation in an enriched environment with high fidelity.

This is one of the untapped areas of research in the world and she can proudly say that UiTM is one of the pioneers with a comprehensive and multidisciplinary expert team comprising of medical doctors, physiotherapists, occupational therapists, clinical psychologists, computer scientists and VR experts from the industry (Motiofixo Sdn Bhd).

Her breakthrough of this MRVR was where she incorporated VR technology to gamify rehabilitation medicine and create a platform that encourages patients to fully engage in therapy either it be hospital based, clinic or community center based or even at home. VR is one of the ways where you can bring treatment to the doorstep, bringing technology to a person in need.

In a recent video that featured her team and a stroke patient in a rural setting in Malaysia, the innovation with the high-powered technology, combined with the human spirit provided by the family and friends aided a 57-year old stroke victim’s recovery.

From 2012 to 2019, more than 300,000 Malaysians suffered from stroke and bringing therapy out of the hospital and making it more accessible is very critical.

Fazah says “the reason for trying virtual reality was due to my passion in research with rehabilitation technology and also I wanted to do something impactful and meaningful for my patients and their families.”

This MRVR (Medical Rehabilitation VR) programme is currently in the research prototype stage with collaboration with other UiTM faculties and a private firm.

To read more on Fazah’s breakthrough, please read http://orcid.org/0000-0003-3409-7210

via UiTM’s Fazah and her VR Breakthrough to Redefining NeuroRehabilitation – QS WOWNEWS

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[ARTICLE] Virtual reality experiences, embodiment, videogames and their dimensions in neurorehabilitation – Full Text

Abstract

Background

In the context of stroke rehabilitation, new training approaches mediated by virtual reality and videogames are usually discussed and evaluated together in reviews and meta-analyses. This represents a serious confounding factor that is leading to misleading, inconclusive outcomes in the interest of validating these new solutions.

Main body

Extending existing definitions of virtual reality, in this paper I put forward the concept of virtual reality experience (VRE), generated by virtual reality systems (VRS; i.e. a group of variable technologies employed to create a VRE). Then, I review the main components composing a VRE, and how they may purposely affect the mind and body of participants in the context of neurorehabilitation. In turn, VRS are not anymore exclusive from VREs but are currently used in videogames and other human-computer interaction applications in different domains. Often, these other applications receive the name of virtual reality applications as they use VRS. However, they do not necessarily create a VRE. I put emphasis on exposing fundamental similarities and differences between VREs and videogames for neurorehabilitation. I also recommend describing and evaluating the specific features encompassing the intervention rather than evaluating virtual reality or videogames as a whole.

Conclusion

This disambiguation between VREs, VRS and videogames should help reduce confusion in the field. This is important for databases searches when looking for specific studies or building metareviews that aim at evaluating the efficacy of technology-mediated interventions.

Background

In the context of stroke rehabilitation, new training approaches mediated by virtual reality and videogames are usually discussed and evaluated together in reviews and meta-analyses for upper limb [], and balance and gait []. Certainly, the expected superiority of virtual reality over conventional therapy post stroke has been questioned when using off-the-shelf (e.g., Nintendo Wii) or ad-hoc videogames. This conclusion, however, is based on the wrong assumption that videogames deliver same experiences than virtual reality applications. In my opinion, this represents a serious confounding factor that may lead to misleading, inconclusive outcomes in the interest of validating these new solutions. Indeed, in Laver’s Cochrane article, a positive effect for virtual reality versus conventional therapy for improving upper limb function post stroke is found only when dedicated virtual reality based interventions, i.e. specifically designed for rehabilitation settings, are used. The effect vanishes when standard off-the-shelf videogames are considered. Indeed, the use of Nintendo Wii (but referring to it as virtual reality) often leads to a non-inferiority clinical outcome, being as effective as conventional therapy [] or alternative playful interventions such as playing cards []. In another study with mobile-based and dedicated games (again referred to as virtual reality), partial functional and motor improvements were observed as compared to standard occupational therapy [].

This heterogeneity in the reported virtual reality and videogames studies for neurorehabilitation calls for use of appropriate labelling for the approaches and variables assessed. A correct identification of the specific factors (and their weight) contributing to any eventual change post treatment are required for interpreting those changes and building further evidence on the specific solution. Therefore, in this paper I propose to reframe the traditional interpretation of the term virtual reality. I advocate disentangling two conceptual components that may help the field standardize its use: virtual reality experience (VRE) and virtual reality systems (VRS). I put emphasis on exposing fundamental similarities and differences between VREs and videogames, often mistakenly used as synonyms or exchangeable terms despite the different underlying interventional techniques and brain mechanisms they can enable. I then use neurorehabilitation as exemplary application field to discuss the implications of differentiating between them.[…]

 

Continue —->  Virtual reality experiences, embodiment, videogames and their dimensions in neurorehabilitation

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[Editorial] Proportional Recovery in the Spotlight – Neurorehabilitation and Neural Repair

By Randolph J. Nudo

Prediction of who will recover after stroke has been a perennial focus for both researchers and clinicians in the field of neurorehabilitation. The prospects of applying a population-based model to predict outcome in individual patients might ultimately allow more focused approaches to stroke rehabilitation and foster a better distribution of precious health care resources. Aside from anatomical biomarkers, such as the integrity of the corticospinal tract, recent attention has focused on the proportional recovery rule, formally proposed in this journal more than 10 years ago by Prabhakaran et al,1 who described a surprisingly linear relationship between Fugl-Meyer Assessment upper extremity scores obtained within 3 days after stroke and those obtained at 3 months poststroke, illustrating the general principle of spontaneous recovery with a level of predictability not previously appreciated. This relationship appears to hold for most individuals (so-called “fitters” or “recoverers”), but a subset of individuals (so-called “non-fitters” or “non-recoverers”) fall off the linear regression line. First applied to upper limb motor impairment, the proportional recovery rule has been examined in a variety of motor and nonmotor impairments, and results have generally been in agreement with the initial linear relationship. Recent controversy surrounding the proportional recovery rule has been based on statistical factors such as mathematical coupling and nonlinearity of outcome scales, questioning not only the accuracy but also the underlying validity of this predictive population-based model. Two articles in the current issue of Neurorehabilitation and Neural Repair highlight some of the emerging views and suggestions for future research regarding this model. The first article by Senesh and Reinkensmeyer examines the reasons why “non-fitters” do not recover according to the proportional recovery algorithm. They argue that the local slope of the linear regression reflects the difficulty of test item scores related to arm and hand movement at follow-up, consistent with the view that non-fitters lack sufficient corticospinal tract. They suggest that at least some non-fitters may have a heightened response to intensive movement training and should be targeted early after stroke for such rehabilitative training. In the second article by Kundert et al, the statistical validity of the proportional recovery rule is examined in the context of recent criticisms regarding its underlying assumptions. Despite 2 recent articles critical of statistical relationships of baseline impairment scores to follow-up scores, especially when used for patient-level predictions, Kundert et al contend that the systematic non-artifactual relationship between initial impairment and motor recovery provides a valid statistical and biologically meaningful model, and that future studies of proportional recovery should use more sophisticated analysis techniques and rigorous methods to assess validity, including comparisons to alternative models.

Randolph J. Nudo, PhD
Editor-in-Chief

1. Prabhakaran, S, Zarahn, E, Riley, C, et alInter-individual variability in the capacity for motor recovery after ischemic stroke. Neurorehabil Neural Repair. 2008;22:6471. doi:10.1177/1545968307305302
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[Abstract] Ergometer training in stroke rehabilitation: systematic review and meta-analysis

Abstract

Objective

Ergometer training is routinely used in stroke rehabilitation. How robust is the evidence of its effects?

Data source

The PubMed database and PEDro database were reviewed prior to 22/01/2019.

Study selection

Randomized controlled trials investigating the effects of ergometer training on stroke recovery were selected.

Data extraction

Two reviewers independently selected the studies, performed independent data extraction, and assessed the risk of bias.

Data synthesis

A total of 28 studies (including 1115 stroke subjects) were included. The data indicates that

(1) ergometer training leads to a significant improvement of walking ability, cardiorespiratory fitness, motor function and muscular force of lower limbs, balance and postural control, spasticity, cognitive abilities, as well as the brain’s resistance to damage and degeneration,

(2) neuromuscular functional electrical stimulation assisted ergometer training is more efficient than ergometer training alone,

(3) high-intensity ergometer training is more efficient that low-intensity ergometer training, and

(4) ergometer training is more efficient than other therapies in supporting cardiorespiratory fitness, independence in activities of daily living, and balance and postural control, but less efficient in improving walking ability.

Conclusion

Ergometer training can support motor recovery after stroke. However, current data is insufficient for evidence-based rehabilitation. More data is required about the effects of ergometer training on cognitive abilities, emotional status, and quality of life in stroke subjects.

via Ergometer training in stroke rehabilitation: systematic review and meta-analysis – Archives of Physical Medicine and Rehabilitation

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[WEB SITE] Neurorehabilitation: Fighting strokes with robotics

Having a stroke can be a scary experience, but the long road to recovery might be getting shorter, thanks to research out of ECU.

Imagine suddenly losing control of a limb or your ability to communicate.

And while this happens, excruciating pain spreads across your head.

This was Joanna’s experience when she had a  at the age of 44.

“I was sick three days up to having my stroke,” Joanna explains. “I had vomiting, headaches and was not making much sense when talking.”

“Three days later, I was sitting down and then it felt like my head was being squeezed between two vices. Excruciating pain.”

Risk factor

In Australia, strokes affect around 55,000 people a year and are the third most common cause of death and a leading cause of disability.

There’s a range of factors that increase the risk of strokes, including diet, exercise and .

But one of the most telling  is, simply, age.

From the age of 45, the risk of a stroke in men is one in four, and for women, it’s one in five.

Fortunately, our knowledge of strokes and how to combat them has improved a lot in the past few decades.

A big part of the solution is getting help quickly, according to Edith Cowan University (ECU) Professor Dylan Edwards.

“If it’s the blockage of a blood vessel, it can be treated very well by anti-coagulant therapy that will break up the blood clot and restore the blood flow to the brain,” Dylan says.

“Typically, you notice somebody is having a stroke by them having issues with their speech or they have a weakness or funny sensation in one side of their body.”

But surviving a stroke is only part of the journey, and with 65% of stroke survivors suffering from some form of disability, restoring motor skills is a critical part of rehabilitation.

Road to recovery

Recovery from stroke can be a long and frustrating road for even the smallest paralysation.

For stroke survivor Joanna, the frustration she felt not being able to move normally made the recovery process even more challenging.

“The emotional side of having the stroke has affected me more than anything else,” Joanna says.

“You slowly get used to the fact that you can’t move your left side, and you know that you’ll get therapy. But when I had people come visit, when they left, I was in tears [out of frustration].”

Joanna eventually started to get some feeling back in her left side, just to her thumb at first.

“It was still a shock that I had lost all of that, so just a little bit of movement was enough to keep me going and stay motivated.”

Fighting back with technology

At ECU’s Lab for NeuroRehabilitation and Robotics, Dylan and his team have been researching how to help people recover their motor control after a brain or spinal cord injury.

Part of their research focuses on understanding the recovery of stroke survivors, using a robotic sensory platform called the Kinarm Exoskeleton Lab.

“The Kinarm looks like a fancy piece of gym equipment,” Dylan explains. “You sit inside the device and position your arms on top of movable handles, and you’re wheeled into this virtual reality environment.”

For the user in the chair, it feels like you’re playing a series of games, moving the chair’s arms to get a response on the screen—such as bouncing balls off paddles.

But the real work is happening behind the scenes.

“All of this information is acquired by these high-powered computers and analysed for how the person is performing,” Dylan says. “This [helps] identify the precise proprioceptive issue with an individual stroke survivor so we can prescribe therapy more effectively.”

In simplest terms, the Kinarm helps identify issues where the user is telling their arm to move but the resulting movement is not what they were trying to do.

This could be an arm not extending the full distance or slower reaction times.

With strokes usually affecting one side of the body more than the other, the unaffected side can provide a good baseline for what their normal reactions should be.

But what if both sides of the body have been affected? The Kinarm can pick up on that too, detecting deficits in what would be considered the unaffected side and showing this in the test results.

R&R—Robotics and Recovery

For Joanna, using the Kinarm has been a challenging experience, even three years after her stroke.

“It actually made you concentrate more in the game to hit the balls coming down,” she explains.

“I think that made you use the brain to try and keep up with your eye, which it didn’t, but I gave it my best shot. I also noticed my peripheral vision has gone.”

“It highlighted for me the improvements I have got since my stroke, which is nice for me three years on to see how it was then to what I could actually achieve on the Kinarm now.”

The data collected helps doctors prescribe the most beneficial treatment for their patients, based on the results of the tests.

Whether it’s heading towards recovering the function in a limb or something as simple as the mobility of a single joint, Dylan believes even small changes are worth pursuing.

“Some degree of independence—even though it might be apparent to an onlooker or a carer—can be very meaningful for a patient.”

“Small changes that we have made in the past through prescribing therapies effectively are things like being able to stabilise yourself on the train and send a text message.”

Recovering movement and lives

While full recovery from a stroke is not guaranteed, any improvement to quality of life can mean everything for survivors. Restoring simple movements can help patients build up their self-confidence to return to their everyday lives.

“Often stroke patients are in the older age bracket, and many of them are working,” Dylan says. “It’s very depressing to be disengaged from a functional work life, and going back to work might just be having the confidence of turning over a page of paper at your desk.”

As we learn more about how the body and brain recover after these , there’s hope we can find ways to better support those who have experienced extensive motor damage.

While there’s medication and training regimes to follow, at its core, it comes down to the drive to actively engage in recovering.

And even if it’s just through small victories, a spark from ECU’s Lab for NeuroRehabilitation and Robotics could help light the fire of determination in .


Explore further

Regulating blood supply to limbs improves stroke recovery

 

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[Editorial] Virtual reality in stroke rehabilitation: virtual results or real values?

1Laboratory for the Study of Mind and Action in Rehabilitation Technologies, IRCCS Fondazione Santa Lucia, Rome, Italy.

Seven Capital Devices for the Future of Stroke Rehabilitation was the title of a review published seven years ago by our group, in which we analyzed the most promising technologies for neurorehabilitation1. They were: robots, virtual reality, brain computer interfaces, wearable devices for human movement analysis, noninvasive brain stimulators (such as transcranial direct current stimulation and transcranial magnetic stimulation), neuroprostheses, and computers/tablets for electronic clinical records and planning1.

Seven years later, we can now take stock of the situation. We must be honest: on one hand, we can surely affirm that the above-proposed technologies have really been the most developed and applied in these last years, but on the other hand, we should say that questions about their efficacy are still open, as reported by Cochrane reviews highlighting the need of further studies2,3.

However, every month, new studies claiming the efficacy of technological rehabilitation are published, and this continuously-growing amount of literature reveals the lack of definitive proof; otherwise all these studies would have been unnecessary. This “efficacy paradox” could potentially give us many more years of research without any conclusive results, especially because the more technology is adaptable to the needs of the patients (as clinicians want), the less the protocol to test the efficacy of that technology is standardizable (as researchers want)4.

Furthermore, the pressure on researchers to publish, the optimism about the use of technologies of some clinicians, the hopes of patients and their caregivers about new miraculous approaches, and the commercial interests of technology companies, may lead to some misleading claims in the mass media. For example, in many scientific and journalistic papers, some electromechanical devices without any intelligence on board are improperly called “robots”, nonimmersive video games are called “virtual reality”, the expressions “mind power” or “force of thought” are associated with brain computer interfaces1. Market analysts expect that the greatest developing field for robots in the next five years will be rehabilitation, compared with other fields5. Conversely, computers, the Internet and smartphones have changed our lives and were not directly developed for rehabilitation, but this clinical field may benefit from all the developed know-how. Virtual reality should be differentiated by video games, referring to a high-end user-computer interface involving real-time stimulation based on the three “I’s”: immersive experience, interaction, and imagination6.

In this scenario, the recent study by Ogun and colleagues clearly shows all the potentials of using a Leap Motion controller interfaced with 3D immersive virtual reality to improve the upper extremity functions in patients with ischemic stroke7. The Leap Motion controller is an optical tracking system including three infrared light emitters and two infrared cameras for tracking hand and finger kinematics, interfacing them with a virtual environment developed as a human-computer interface. In 2014, our group published the first feasibility pilot study proposing the use of Leap Motion in neurorehabilitation, noting its advantageous features: it is precise, markerless, low-cost, small, and easy to use8.

Ogun and colleagues have confirmed our intuition: they found that virtual reality rehabilitation guided by a Leap Motion controller appeared to be effective in improving upper extremity function and self-care skills (but not functional independence), more than conventional therapy, in a wide sample of patients7.

Many studies have reported that the sense of presence, of body ownership and agency elicited by virtual reality are similar to those in the real environment, and daily life activities have been replicated in virtual environments for training patients. But what is the real value of virtual reality in rehabilitation if it is just a replication of a real environment? Virtual reality can also elicit amusement, arousal and valence, even more than in the real environment, as happens in virtual reality-based video games. Amusement can improve participation, arousal can improve brain activities, valence can improve learning9. It seems to be time for a generation of amusing and immersive virtual reality for improving real outcomes in neurorehabilitation.

REFERENCES

1. Iosa M, Morone G, Fusco A, Bragoni M, Coiro P, Multari M, et al. Seven capital devices for the future of stroke rehabilitation. Stroke Res Treat. 2012;2012:187965. https://doi.org/10.1155/2012/187965 [ Links ]

2. Mehrholz J, Pohl M, Platz T, Kugler J, Elsner B. Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke. Cochrane Database Syst Rev. 2018 Sep;9:CD006876. https://doi.org/10.1002/14651858.CD006876.pub5 [ Links ]

3. Laver KE, Lange B, George S, Deutsch JE, Saposnik G, Crotty M. Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev. 2017 Nov;11:CD008349. https://doi.org/10.1002/14651858.CD008349.pub4 [ Links ]

4. Iosa M, Morone G, Cherubini A, Paolucci S. The Three laws of neurorobotics: a review on what neurorehabilitation robots should do for patients and clinicians. J Med Biol Eng. 2016;36(1):1–11. https://doi.org/10.1007/s40846-016-0115-2 [ Links ]

5. Ugalmugale S, Mupid S. Healthcare assistive robot market size by product. City: Global Market Insights, 2017. [ Links ]

6. Burdea GC, Coiffet P. Virtual reality technology. 2nd ed. Hoboken, NJ: John Wiley & Sons; 2003. [ Links ]

7. Ögün1 MN, Kurul R, Yaşar MF, Turkoglu SA, Avcı S, Yildiz N. Effect of leap motion-based 3D immersive virtual reality usage on upper extremity function in ischemic stroke patients. Arq Neuropsiquiatr 2019;77(10):681-88. https://doi.org/10.1590/0004-282X20190129 [ Links ]

8. Iosa M, Morone G, Fusco A, Castagnoli M, Fusco FR, Pratesi L, et al. Leap motion controlled videogame-based therapy for rehabilitation of elderly patients with subacute stroke: a feasibility pilot study. Top Stroke Rehabil. 2015 Aug;22(4):306–16. https://doi.org/10.1179/1074935714Z.0000000036 [ Links ]

9. Tieri G, Morone G, Paolucci S, Iosa M. Virtual reality in cognitive and motor rehabilitation: facts, fiction and fallacies. Expert Rev Med Devices. 2018 Feb;15(2):107–17. https://doi.org/10.1080/17434440.2018.1425613 [ Links ]

 

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