Posts Tagged chronic

[ARTICLE] Effects of a Brain-Computer Interface With Virtual Reality (VR) Neurofeedback: A Pilot Study in Chronic Stroke Patients – Full Text

Rehabilitation for stroke patients with severe motor impairments (e.g., inability to perform wrist or finger extension on the affected side) is burdensome and difficult because most current rehabilitation options require some volitional movement to retrain the affected side. However, although these patients participate in therapy requiring volitional movement, previous research has shown that they may receive modest benefits from action observation, virtual reality (VR), and brain-computer interfaces (BCIs). These approaches have shown some success in strengthening key motor pathways thought to support motor recovery after stroke, in the absence of volitional movement. The purpose of this study was to combine the principles of VR and BCI in a platform called REINVENT and assess its effects on four chronic stroke patients across different levels of motor impairment. REINVENT acquires post-stroke EEG signals that indicate an attempt to move and drives the movement of a virtual avatar arm, allowing patient-driven action observation neurofeedback in VR. In addition, synchronous electromyography (EMG) data were also captured to monitor overt muscle activity. Here we tested four chronic stroke survivors and show that this EEG-based BCI can be safely used over repeated sessions by stroke survivors across a wide range of motor disabilities. Finally, individual results suggest that patients with more severe motor impairments may benefit the most from EEG-based neurofeedback, while patients with more mild impairments may benefit more from EMG-based feedback, harnessing existing sensorimotor pathways. We note that although this work is promising, due to the small sample size, these results are preliminary. Future research is needed to confirm these findings in a larger and more diverse population.


Stroke is a leading cause of adult long-term disability worldwide (Mozaffarian et al., 2015), and an increasing number of stroke survivors suffer from severe cognitive and motor impairments each year. This results in a loss of independence in their daily life, such as decreased ability to perform self-care tasks and decreased participation in social activities (Miller et al., 2010). Rehabilitation following stroke focuses on maximizing restoration of lost motor and cognitive functions and on relearning skills to better perform activities of daily living (ADLs). There is increasing evidence that the brain remains plastic at later stages after stroke, suggesting additional recovery remains possible (Page et al., 2004Butler and Page, 2006). To maximize brain plasticity, several rehabilitation strategies have been exploited, including the use of intensive rehabilitation (Wittenberg et al., 2016), repetitive motor training (Thomas et al., 2017), mirror therapy (Pérez-Cruzado et al., 2017), motor-imagery (Kho et al., 2014), and action observation (Celnik et al., 2008), amongst others.

Recently, growing evidence of the positive impact of virtual reality (VR) techniques on recovery following stroke has accumulated (Bermúdez i Badia et al., 2016). When combined with conventional therapy, VR is able to effectively incorporate rehabilitation strategies such as intensity, frequency, and duration of therapy in a novel and low-cost approach in the stroke population (Laver et al., 2017). However, patients with low levels of motor control cannot benefit from current VR tools due to their low volitional motor control, range of motion, pain, and fatigue. Rehabilitation for these individuals is challenging because most current training options require some volitional movement to train the affected side, however, research has shown that individuals with severe stroke may receive modest benefits from action observation and brain-computer interfaces (BCIs) (Silvoni et al., 2011).

Merging BCIs with VR allows for a wide range of experiences in which patients can feel immersed in various aspects of their environment. This allows patients to control their experiences in VR using only brain activity, either directly (e.g., movement in VR through explicit control) or indirectly (e.g., modulating task difficulty level based on workload as implicit control) (Vourvopoulos et al., 2016Friedman, 2017). This direct brain-to-VR communication can induce a sensorimotor contingency between the patient’s internal intentions and the environment’s responsive actions, increasing the patient’s sense of embodiment of their virtual avatar (Slater, 2009Ramos-Murguialday et al., 2013).

After a stroke resulting in severe motor impairments (e.g., inability to perform wrist or finger extension on the affected side), research shows that action observation combined with physical training enhances the effects of motor training (Celnik et al., 2008), eliciting motor-related brain activity in the lesioned hemisphere, leading to modest motor improvements (Ertelt et al., 2007Garrison et al., 2013). Moreover, action observation in a head-mounted VR increases motor activity in both healthy and the post-stroke brains (Ballester et al., 2015Vourvopoulos and Bermúdez i Badia, 2016a).

In addition, neurofeedback through BCIs has been proposed for individuals with severe stroke because BCIs do not require active motor control. Research on BCIs for rehabilitation has shown that motor-related brain signals are reinforced by rewarding feedback so they can be used to strengthen key motor pathways that are thought to support motor recovery after stroke (Wolpaw, 2012). Such feedback has previously shown modest success in motor rehabilitation for severe stroke patients (Soekadar et al., 2015).

The most common brain signal acquisition technology used with BCIs in stroke patients is non-invasive electroencephalography (EEG) (Wolpaw, 2012), which provide a cost-effective BCI platform (Vourvopoulos and Bermúdez i Badia, 2016b). In BCI paradigms for motor rehabilitation, EEG signals related to motor planning and execution are utilized. During a motor attempt, the temporal pattern of the Alpha rhythm (8–12 Hz) desynchronizes. The Alpha rhythm is also termed Rolandic mu or the sensorimotor rhythm (SMR) when it is localized over the sensorimotor cortices of the brain. Mu rhythms (8–12 Hz) are considered indirect indications of the action observation network (Kropotov, 2016) and reflect general sensorimotor activity. Mu rhythms are often detected with changes in the Beta rhythm (12–30 Hz) in the form of event-related desynchronization (ERD), in which a motor action is executed (Pfurtscheller and Lopes da Silva, 1999). These EEG rhythms, or motor-related EEG signatures, are primarily detected during task-based EEG (i.e., when the patient is actively moving or imagining movement) and used for neurofeedback.

Further, neurofeedback-induced changes in brain activity have also been linked to changes in brain activity at rest. That is, after training one’s brain activity using neurofeedback, the intrinsic, resting brain activity (i.e., EEG activity in the absence of a task) may also show changes. This resting brain activity can be used to assess more generalized brain changes, and baseline resting-state signatures may be used to predict recovery (Wu et al., 2015) or response to treatments (Zhou et al., 2018). When combined with neural injury information, resting EEG parameters can also help predict the efficacy of stroke therapy.

In this study, our goal was to combine the principles of virtual reality and BCIs to elicit optimal rehabilitation gains for stroke survivors. We hypothesized that merging BCIs with VR should induce illusions of movement and a strong feeling of embodiment within a virtual body via the action observation network, activating brain areas that overlap with those controlling actual movement, which is important for mobilizing neuroplastic changes (Dobkin, 2007). Using a VR-based BCI, those with severe stroke impairments can trigger voluntary movements of the virtual arm in a closed neurofeedback loop. This helps to increase the illusion of one’s own movements through the coordination between one’s intention and the observed first-person virtual action. Therefore, we developed a training platform called REINVENT, which uses post-stroke brain signals that indicate an attempt to move and then drives the movement of a virtual avatar arm, providing patient-driven action observation in head-mounted VR (Spicer et al., 2017). Our previous work using REINVENT with healthy individuals indeed showed that the combination of VR integrated into a BCI encouraged greater embodiment, and greater embodiment was related to greater neurofeedback performance (Anglin et al., 2019).

For this study, we recruited four chronic stroke survivors to undergo a longitudinal BCI-VR intervention using REINVENT to provide EEG-based neurofeedback with simultaneous EMG acquisition. We assessed intervention results using clinical measures, Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Imaging (MRI) and compared these measures before and after the intervention. The purpose of this study was twofold. First, we sought to determine whether REINVENT is feasible for stroke patients to use across repeated sessions and second, whether REINVENT might be able to strengthen motor-related brain signals in individuals with differing levels of motor impairment after stroke.[…]


Continue —>  Frontiers | Effects of a Brain-Computer Interface With Virtual Reality (VR) Neurofeedback: A Pilot Study in Chronic Stroke Patients | Frontiers in Human Neuroscience

Figure 1. System architecture of a closed neurofeedback loop. From left, (1) the evoked physiological responses are captured at the interfacing layer through the data acquisition clients, (2) sent to the processing layer where the signals are filtered and logged, and then, (3) the extracted features (e.g., EEG bands) are sent to the interaction layer where VR training occurs. Written permission to use this photo was obtained from the individual.

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[Abstract] Soymilk ingestion immediately after therapeutic exercise enhances rehabilitation outcomes in chronic stroke patients: A randomized controlled trial. – NeuroRehabilitation


Study investigated the effects of an 8-week rehabilitation exercise program combined with soymilk ingestion immediately after exercise on functional outcomes in chronic stroke patients.

Twenty-two stroke patients were randomly allocated to either the soymilk or the placebo (PLA) group and received identical 8-weeks rehabilitation intervention (3 sessions per week for 120 minutes each session) with corresponding treatment beverages. The physical and functional outcomes were evaluated before, during, and after the intervention. The 8-week rehabilitation program enhanced functional outcomes of participants.

The immediate soymilk ingestion after exercise additionally improved hand grip strength, walking speed over 8 feet, walking performance per unit lean mass, and 6-Minute Walk Test performance compared with PLA after the intervention. However, the improvements in the total score for Short Physical Performance Battery and lean mass did not differ between groups.

This study demonstrated that, compared with rehabilitation alone, the 8-week rehabilitation program combined with immediate soymilk ingestion further improved walking speed, exercise endurance, grip strength, and muscle functionality in chronic stroke patients.

via Articles, Books, Reports, & Multimedia: Search REHABDATA | National Rehabilitation Information Center

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[WEB SITE] imHere Homepage – mHealth Platform for Self-management


Interactive Mobile Health and Rehabilitation

iMHere is an mHealth platform promoting clinician-guided self-care to patients with chronic diseases. Internet accessibility provides a secure bridge between patients’ smartphone applications and a web-based clinician portal, and successfully empowers patients to perform subjective self-care and preventative measures. The app was designed to send monitorial data to the portal and also receive output regarding self-care regimens as recommended by the attending clinician. The combination of interactive, real-time medical monitoring with patient control offers a powerful, unique solution for patients living with chronic illnesses where cognitive and physical disabilities present significant barriers to effective self-care.

Using a web-based portal, the clinician (typically a nurse coordinator, social worker, case manager, or patient advocate) could monitor patients’ compliance with regimens and indicate self-care plans to be delivered to the patient via the app, allowing the clinician to monitor a patient’s status and intervene as needed. Clinicians could use the portal to tailor a regimen or treatment plan for each and every patient (e.g. scheduled medication, wound care instructions, etc.) and the portal would consolidate the plan to the smartphone app in real time—an advancement over existing comparable health portals which cannot push data to the app. Results of clinical implementation suggest that the iMHere app was successful in delivering values for patients and in engaging them to comply with treatment. In the first 6 months of the clinical implementation, patients have been consistently using the app for self-management tasks and to follow the regimes set up by their respective clinicians. We observed that the daily usage increased significantly in the first two months (from approximately 1.3-times/day to over 3-times/day), and then plateau at around 3.5 times per day per patient. This pattern of increasing usage in the first two months and the subsequent plateau is relatively consistent across all patients. The app is currently available in Android platform with an iPhone version under development.

via imHere Homepage – mHealth Platform for Self-management

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[ARTICLE] Long-Dose Intensive Therapy Is Necessary for Strong, Clinically Significant, Upper Limb Functional Gains and Retained Gains in Severe/Moderate Chronic Stroke – Full Text

Background. Effective treatment methods are needed for moderate/severely impairment chronic stroke.

Objective. The questions were the following: (1) Is there need for long-dose therapy or is there a mid-treatment plateau? (2) Are the observed gains from the prior-studied protocol retained after treatment?

Methods. Single-blind, stratified/randomized design, with 3 applied technology treatment groups, combined with motor learning, for long-duration treatment (300 hours of treatment). Measures were Arm Motor Ability Test time and coordination-function (AMAT-T, AMAT-F, respectively), acquired pre-/posttreatment and 3-month follow-up (3moF/U); Fugl-Meyer (FM), acquired similarly with addition of mid-treatment.

Findings. There was no group difference in treatment response (P ≥ .16), therefore data were combined for remaining analyses (n = 31; except for FM pre/mid/post, n = 36). Pre-to-Mid-treatment and Mid-to-Posttreatment gains of FM were statistically and clinically significant (P < .0001; 4.7 points and P < .001; 5.1 points, respectively), indicating no plateau at 150 hours and benefit of second half of treatment. From baseline to 3moF/U: (1) FM gains were twice the clinically significant benchmark, (2) AMAT-F gains were greater than clinically significant benchmark, and (3) there was statistically significant improvement in FM (P < .0001); AMAT-F (P < .0001); AMAT-T (P < .0001). These gains indicate retained clinically and statistically significant gains at 3moFU. From posttreatment to 3moF/U, gains on FM were maintained. There were statistically significant gains in AMAT-F (P = .0379) and AMAT-T P = .003.

Many stroke survivors do not fully recover upper limb function following stroke, leading to significant disability and diminished quality of life.1 Effective treatments are needed for chronic, severely impaired stroke survivors.2 Other studies showed improved upper limb motor function in chronic stroke for mild/moderately impaired,313 with traditional “constraint induced” treatment studies enrolling only those with preserved wrist and finger extension (acceptance rate, 10%).14 However, for those with moderate/severe impairment after stroke, improvement in function has been more difficult to realize. A recent study of constraint-induced movement therapy in more severe stroke reported no clinically significant change in upper limb Fugl-Meyer assessment scores.15 Others have also tested the application of technologies and devices, in moderately/severely impaired chronic stroke survivors, with the following: functional electrical stimulation (FES),1618 sequenced bilateral and unilateral task orientated training,19 mirror therapy,20 progressive abduction loading therapy,21 contralaterally controlled FES,22 and robotics.2327 Limitations included small sample size,1618,2223 lacking control group,16,23 lacking statistically significant gains on impairment or functional measures,23 lacking clinically significant change,20,21,2325,27 lacking retention of clinically significant gains,16,19,25,26 or lacking study of retention.20,23 Furthermore, many studies do not include both a measure of impairment and an array of actual everyday functional tasks. Our work has focused on moderately/severely impaired chronic stroke survivors, and in prior work we developed and tested a protocol that combines technology applications and motor learning.28,29 We found clinically and statistically significant gains for those with moderate/severe stroke considerably beyond that reported by others (eg, gains in coordination, Fugl-Myer coordination scale [FM], and gains on the Arm Motor Ability Test [AMAT; 13 complex functional tasks]).

Others have cited this work stating that “a change in impairment of this magnitude was previously considered almost impossible in chronic stroke patients,”30 and that this is important first evidence for use of high dose neurorehabilitation.31 Therefore, we considered it important to replicate the administration of the upper limb motor learning protocol in a follow-on study and again quantify response. Another consideration was that we had not given technology a full chance in application to the “whole arm,” that is, both distal and proximal upper limb regions. Therefore, a first purpose was to replicate administration of the upper limb motor learning protocol and to include a treatment group that would receive technology applications to both distal and proximal limb regions. In addition, there were 2 important and unanswered questions regarding the dose and efficacy of this new treatment protocol.

The first question is whether a shorter treatment duration (ie, <300 hours) could produce the same degree of recovery, given that the existing protocol was tested in the paradigm of long-duration dose of 300 hours of therapy. Therefore, in the current work, we administered the same protocol as in prior work,28 and acquired mid-treatment (at 150 hours of treatment) data on the Fugl-Meyer impairment measure, which underlies complex functional task performance. We studied whether a mid-treatment plateau occurred or whether significant recovery occurred in response to the second half of treatment (mid-treatment to posttreatment).

The second question is whether the observed gains can be retained after cessation of treatment. Therefore, we studied retention of gains at 3 months after treatment ended.[…]


Continue —> Long-Dose Intensive Therapy Is Necessary for Strong, Clinically Significant, Upper Limb Functional Gains and Retained Gains in Severe/Moderate Chronic Stroke – Janis J. Daly, Jessica P. McCabe, John Holcomb, Michelle Monkiewicz, Jennifer Gansen, Svetlana Pundik, 2019

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[Abstract] A novel neurocognitive rehabilitation tool in the recovery of hemiplegic hand grip after stroke: a case report.


Stroke has significant physical, psychological and social consequences. Recent rehabilitation approaches suggest that cognitive exercises with dual-task (sensory-motor) exercises positively influence the recovery and function of the hemiplegic hand grip. The purpose of this study was to describe a rehabilitation protocol involving the use of a new neurocognitive tool called “UOVO” for hand grip recovery after stroke. A 58-year-old right-handed male patient in the chronic stage of stroke, presenting with left-sided hemiparesis and marked motor deficits at the level of the left hand and forearm, was treated with the UOVO, a new rehabilitation instrument based on the neurocognitive rehabilitation theory of Perfetti. The patient was evaluated at T0 (before treatment), T1 (after treatment) and T2 (2 months of follow-up). At T2, the patient showed improvements of motor functions, shoulder, elbow and wrist spasticity, motility and performance. This case report explores the possibility of improving traditional rehabilitation through a neurocognitive approach with a dual-task paradigm (including motor and somato-sensory stimulation), specifically one involving the use of an original rehabilitation aid named UOVO, which lends itself very well to exercises proposed through the use of motor imagery. The results were encouraging and showed improvements in hemiplegic hand grip function and recovery. However, further studies, in the form of randomized controlled trials, will be needed to further explore and confirm our results.


via A novel neurocognitive rehabilitation tool in the recovery of hemiplegic hand grip after stroke: a case report. – PubMed – NCBI

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[Abstract] Learning a Bimanual Cooperative Skill in Chronic Stroke Under Noninvasive Brain Stimulation: A Randomized Controlled Trial


Background. Transcranial direct current stimulation (tDCS) has been suggested to improve poststroke recovery. However, its effects on bimanual motor learning after stroke have not previously been explored.

Objective. We investigated whether dual-tDCS of the primary motor cortex (M1), with cathodal and anodal tDCS applied over undamaged and damaged hemispheres, respectively, improves learning and retention of a new bimanual cooperative motor skill in stroke patients.

Method. Twenty-one chronic hemiparetic patients were recruited for a randomized, double-blinded, cross-over, sham-controlled trial. While receiving real or sham dual-tDCS, they trained on a bimanual cooperative task called CIRCUIT. Changes in performance were quantified via bimanual speed/accuracy trade-off (Bi-SAT) and bimanual coordination factor (Bi-Co) before, during, and 0, 30, and 60 minutes after dual-tDCS, as well as one week later to measure retention. A generalization test then followed, where patients were asked to complete a new CIRCUIT layout.

Results. The patients were able to learn and retain the bimanual cooperative skill. However, a general linear mixed model did not detect a significant difference in retention between the real and sham dual-tDCS conditions for either Bi-SAT or Bi-Co. Similarly, no difference in generalization was detected for Bi-SAT or Bi-Co.

Conclusion. The chronic hemiparetic stroke patients learned and retained the complex bimanual cooperative task and generalized the newly acquired skills to other tasks, indicating that bimanual CIRCUIT training is promising as a neurorehabilitation approach. However, bimanual motor skill learning was not enhanced by dual-tDCS in these patients.

via Learning a Bimanual Cooperative Skill in Chronic Stroke Under Noninvasive Brain Stimulation: A Randomized Controlled Trial – Maral Yeganeh Doost, Jean-Jacques Orban de Xivry, Benoît Herman, Léna Vanthournhout, Audrey Riga, Benoît Bihin, Jacques Jamart, Patrice Laloux, Jean-Marc Raymackers, Yves Vandermeeren, 2019

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[Abstract] Four-week training involving ankle mobilization with movement versus static muscle stretching in patients with chronic stroke: a randomized control trial.


Patients with stroke generally have diminished balance and gait. Mobilization with movement (MWM) can be used with manual force applied by a therapist to enhance talus gliding movement. Furthermore, the weight-bearing position during the lunge may enhance the stretch force.

This study aimed to compare the effects of a 4-week program of MWM training with those of static muscle stretching (SMS). Ankle dorsiflexion passive range of motion (DF-PROM), static balance ability (SBA), the Berg balance scale (BBS), and gait parameters (gait speed and cadence) were measured in patients with chronic stroke.

Twenty patients with chronic stroke participated in this study. Participants were randomized to either the MWM (n = 10) or the SMS (n = 10) group. Patients in both groups underwent standard rehabilitation therapy for 30 min per session. In addition, MWM and SMS techniques were performed three times per week for 4 weeks. Ankle DF-PROM, SBA, BBS score, and gait parameters were measured after 4 weeks of training.

After 4 weeks of training, the MWM group showed significant improvement in all outcome measures compared with baseline (p < 0.05). Furthermore, SBA, BBS, and cadence showed greater improvement in the MWM group compared to the SMS group (p < 0.05).

This study demonstrated that MWM training, combined with standard rehabilitation, improved ankle DF-PROM, SBA, BBS scores, and gait speed and cadence. Thus, MWM may be an effective treatment for patients with chronic stroke.

via Four-week training involving ankle mobilization with movement versus static muscle stretching in patients with chronic stroke: a randomized control… – PubMed – NCBI

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[ARTICLE] Robot assisted training for the upper limb after stroke (RATULS): a multicentre randomised controlled trial – Full Text



Loss of arm function is a common problem after stroke. Robot-assisted training might improve arm function and activities of daily living. We compared the clinical effectiveness of robot-assisted training using the MIT-Manus robotic gym with an enhanced upper limb therapy (EULT) programme based on repetitive functional task practice and with usual care.


RATULS was a pragmatic, multicentre, randomised controlled trial done at four UK centres. Stroke patients aged at least 18 years with moderate or severe upper limb functional limitation, between 1 week and 5 years after their first stroke, were randomly assigned (1:1:1) to receive robot-assisted training, EULT, or usual care. Robot-assisted training and EULT were provided for 45 min, three times per week for 12 weeks. Randomisation was internet-based using permuted block sequences. Treatment allocation was masked from outcome assessors but not from participants or therapists. The primary outcome was upper limb function success (defined using the Action Research Arm Test [ARAT]) at 3 months. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN69371850.


Between April 14, 2014, and April 30, 2018, 770 participants were enrolled and randomly assigned to either robot-assisted training (n=257), EULT (n=259), or usual care (n=254). The primary outcome of ARAT success was achieved by 103 (44%) of 232 patients in the robot-assisted training group, 118 (50%) of 234 in the EULT group, and 85 (42%) of 203 in the usual care group. Compared with usual care, robot-assisted training (adjusted odds ratio [aOR] 1·17 [98·3% CI 0·70–1·96]) and EULT (aOR 1·51 [0·90–2·51]) did not improve upper limb function; the effects of robot-assisted training did not differ from EULT (aOR 0·78 [0·48–1·27]). More participants in the robot-assisted training group (39 [15%] of 257) and EULT group (33 [13%] of 259) had serious adverse events than in the usual care group (20 [8%] of 254), but none were attributable to the intervention.


Robot-assisted training and EULT did not improve upper limb function after stroke compared with usual care for patients with moderate or severe upper limb functional limitation. These results do not support the use of robot-assisted training as provided in this trial in routine clinical practice.


National Institute for Health Research Health Technology Assessment Programme.


Upper limb problems commonly occur after a stroke, comprising loss of movement, coordination, sensation, and dexterity, which lead to difficulties with activities of daily living (ADL) such as washing and dressing. About 80% of people with acute stroke have upper limb motor impairment, and of those with reduced arm function early after stroke, 50% still have problems after 4 years.
The strongest predictor of recovery is severity of initial neurological deficit; patients with severe initial upper limb impairment are unlikely to recover arm function, with clear impact upon their quality of life. Patients report that loss of arm function is one of the most distressing long-term consequences of stroke. Improving upper limb function has been identified as a top ten research priority by stroke survivors, carers, and clinicians.
How to optimise stroke patients’ upper limb recovery is unclear. Systematic reviews of therapy interventions suggest that patients benefit from therapy programmes in which they practise tasks directly rather than from interventions that focus on impairments. Intensity of therapy is also important; a Cochrane overviewof systematic reviews found moderate quality Grading of Recommendations, Assessment, Development and Evaluations evidence that arm function after a stroke can be improved by the provision of at least 20 h of additional repetitive task training.
Robot-assisted arm training has shown promise for improving ADL, arm function, and arm muscle strength after stroke.However, studies vary in patient characteristics, device used, duration and amount of training, control group, and outcome measures used. The benefits of robot-assisted arm training over conventional therapy of the same frequency and duration have not been shown.


Continue —> Robot assisted training for the upper limb after stroke (RATULS): a multicentre randomised controlled trial – The Lancet

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Figure 2ARAT success, total ARAT score, and Fugl–Meyer motor score at baseline, 3 months, and 6 months


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[THESIS] Validating Creativity: Use of the HTC Vive in Post-Stroke Upper Limb Rehabilitation – Abstract


Physical therapists often creatively use virtual reality (VR) gaming systems in rehabilitation for patients with neurological deficits. However, therapists need to be aware of what games are applicable to their patient population, as well as how the virtual environment affects patients’ perception of their motion. This study investigated how the game Google Tilt Brush, a 3D painting environment offered on the HTC Vive, could be applied in post-stroke upper limb rehabilitation, and explored limitations of the system through measuring reach distance of healthy subjects. Nine healthy subjects were recruited and asked to perform various reaching and drawing tasks while data on their movement was gathered using a Vicon motion capture system. The data showed that while in simple reaching tasks individual subjects may alter their reach distance by up to 3 cm in the virtual environment, across all subjects there is not a statistically significant change. Moreover, in more complicated drawing tasks, participants could reliably reach to particular points, but most participants missed the exact target by several centimeters. Overall, it seems that the HTC Vive and Google Tilt Brush can be utilized in post-stroke upper limb rehabilitation if therapists monitor patients to ensure they are accomplishing the desired movement.

via Validating Creativity: Use of the HTC Vive in Post-Stroke Upper Limb Rehabilitation

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[Abstract + References] Electromyographic indices of muscle fatigue of a severely paralyzed chronic stroke patient undergoing upper limb motor rehabilitation


Modern approaches to motor rehabilitation of severe upper limb paralysis in chronic stroke decode movements from electromyography for controlling rehabilitation orthoses. Muscle fatigue is a phenomenon that influences these neurophysiological signals and may diminish the decoding quality. Characterization of these potential signal changes during movement patterns of rehabilitation training could therefore help improve the decoding accuracy. In the present work we investigated how electromyographic indices of muscle fatigue in the Deltoid Anterior muscle evolve during typical forward reaching movements of a rehabilitation training in healthy subjects and a stroke patient. We found that muscle fatigue in healthy subjects changed the neurophysiological signal. In the patient, however, no consistent change was observed over several sessions.
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2. A. Ramos-Murguialday et al , “Brain-machine interface in chronic stroke rehabilitation: a controlled study,” Ann. Neurol., vol. 74, no. 1, pp. 100–108, 2013.

3. A. Sarasola-Sanz et al , “A hybrid brain-machine interface based on EEG and EMG activity for the motor rehabilitation of stroke patients,” IEEE Int Conf Rehabil Robot, vol. 2017, pp. 895–900, Jul. 2017.

4. R. M. Enoka and J. Duchateau , “Muscle fatigue: what, why and how it influences muscle function,” J Physiol, vol. 586, no. 1, pp. 11–23, Jan. 2008.

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6. A. Sarasola Sanz et al , “EMG-based multi-joint kinematics decoding for robot-aided rehabilitation therapies,” in 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), 2015.

7. P. V. Komi and P. Tesch , “EMG frequency spectrum, muscle structure, and fatigue during dynamic contractions in man,” Eur. J Appl Physiol, vol. 42, no. 1, pp. 41–50, Sep. 1979.

8. D. R. Rogers and D. T. MacIsaac , “A comparison of EMG-based muscle fatigue assessments during dynamic contractions,” J. Electromyogr. Kinesiol., vol. 23, no. 5, pp. 1004–1011, Oct. 2013.

9. B. Bigland-Ritchie , E. F. Donovan , and C. S. Roussos , “Conduction velocity and EMG power spectrum changes in fatigue of sustained maximal efforts,” J Appl Physiol Respir Env. Exerc Physiol, vol. 51, no. 5, pp. 1300–1305, Nov. 1981.

10. G. V. Dimitrov , T. I. Arabadzhiev , K. N. Mileva , J. L. Bowtell , N. Crichton , and N. A. Dimitrova , “Muscle Fatigue during Dynamic Contractions Assessed by New Spectral Indices,” Med. Sci. Sports Exerc., 2006.

11. N. A. Riley and M. Bilodeau , “Changes in upper limb joint torque patterns and EMG signals with fatigue following a stroke,” Disabil Rehabil, vol. 24, no. 18, pp. 961–969, Dec. 2002.

12. M. J. Campbell , A. J. McComas , and F. Petito , “Physiological changes in ageing muscles,” J. Neurol. Neurosurg. Psychiatry, vol. 36, no. 2, pp. 174–182, 1973.


via Electromyographic indices of muscle fatigue of a severely paralyzed chronic stroke patient undergoing upper limb motor rehabilitation – IEEE Conference Publication

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