3,237 research outputs found

    Development and preliminary evaluation of a novel low cost VR-based upper limb stroke rehabilitation platform using Wii technology.

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    Abstract Purpose: This paper proposes a novel system (using the Nintendo Wii remote) that offers customised, non-immersive, virtual reality-based, upper-limb stroke rehabilitation and reports on promising preliminary findings with stroke survivors. Method: The system novelty lies in the high accuracy of the full kinematic tracking of the upper limb movement in real-time, offering strong personal connection between the stroke survivor and a virtual character when executing therapist prescribed adjustable exercises/games. It allows the therapist to monitor patient performance and to individually calibrate the system in terms of range of movement, speed and duration. Results: The system was tested for acceptability with three stroke survivors with differing levels of disability. Participants reported an overwhelming connection with the system and avatar. A two-week, single case study with a long-term stroke survivor showed positive changes in all four outcome measures employed, with the participant reporting better wrist control and greater functional use. Activities, which were deemed too challenging or too easy were associated with lower scores of enjoyment/motivation, highlighting the need for activities to be individually calibrated. Conclusions: Given the preliminary findings, it would be beneficial to extend the case study in terms of duration and participants and to conduct an acceptability and feasibility study with community dwelling survivors. Implications for Rehabilitation Low-cost, off-the-shelf game sensors, such as the Nintendo Wii remote, are acceptable by stroke survivors as an add-on to upper limb stroke rehabilitation but have to be bespoked to provide high-fidelity and real-time kinematic tracking of the arm movement. Providing therapists with real-time and remote monitoring of the quality of the movement and not just the amount of practice, is imperative and most critical for getting a better understanding of each patient and administering the right amount and type of exercise. The ability to translate therapeutic arm movement into individually calibrated exercises and games, allows accommodation of the wide range of movement difficulties seen after stroke and the ability to adjust these activities (in terms of speed, range of movement and duration) will aid motivation and adherence - key issues in rehabilitation. With increasing pressures on resources and the move to more community-based rehabilitation, the proposed system has the potential for promoting the intensity of practice necessary for recovery in both community and acute settings.The National Health Service (NHS) London Regional Innovation Fund

    Robot-Aided Systems for Improving the Assessment of Upper Limb Spasticity: A Systematic Review

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    This article belongs to the Special Issue Sensors Technology for Medical Robotics.Spasticity is a motor disorder that causes stiffness or tightness of the muscles and can interfere with normal movement, speech, and gait. Traditionally, the spasticity assessment is carried out by clinicians using standardized procedures for objective evaluation. However, these procedures are manually performed and, thereby, they could be influenced by the clinician’s subjectivity or expertise. The automation of such traditional methods for spasticity evaluation is an interesting and emerging field in neurorehabilitation. One of the most promising approaches is the use of robot-aided systems. In this paper, a systematic review of systems focused on the assessment of upper limb (UL) spasticity using robotic technology is presented. A systematic search and review of related articles in the literature were conducted. The chosen works were analyzed according to the morphology of devices, the data acquisition systems, the outcome generation method, and the focus of intervention (assessment and/or training). Finally, a series of guidelines and challenges that must be considered when designing and implementing fully-automated robot-aided systems for the assessment of UL spasticity are summarized

    Training modalities in robot-mediated upper limb rehabilitation in stroke : A framework for classification based on a systematic review

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    © 2014 Basteris et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The work described in this manuscript was partially funded by the European project ‘SCRIPT’ Grant agreement no: 288698 (http://scriptproject.eu). SN has been hosted at University of Hertfordshire in a short-term scientific mission funded by the COST Action TD1006 European Network on Robotics for NeuroRehabilitationRobot-mediated post-stroke therapy for the upper-extremity dates back to the 1990s. Since then, a number of robotic devices have become commercially available. There is clear evidence that robotic interventions improve upper limb motor scores and strength, but these improvements are often not transferred to performance of activities of daily living. We wish to better understand why. Our systematic review of 74 papers focuses on the targeted stage of recovery, the part of the limb trained, the different modalities used, and the effectiveness of each. The review shows that most of the studies so far focus on training of the proximal arm for chronic stroke patients. About the training modalities, studies typically refer to active, active-assisted and passive interaction. Robot-therapy in active assisted mode was associated with consistent improvements in arm function. More specifically, the use of HRI features stressing active contribution by the patient, such as EMG-modulated forces or a pushing force in combination with spring-damper guidance, may be beneficial.Our work also highlights that current literature frequently lacks information regarding the mechanism about the physical human-robot interaction (HRI). It is often unclear how the different modalities are implemented by different research groups (using different robots and platforms). In order to have a better and more reliable evidence of usefulness for these technologies, it is recommended that the HRI is better described and documented so that work of various teams can be considered in the same group and categories, allowing to infer for more suitable approaches. We propose a framework for categorisation of HRI modalities and features that will allow comparing their therapeutic benefits.Peer reviewedFinal Published versio

    Interventions for improving upper limb function after stroke

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    Background: Improving upper limb function is a core element of stroke rehabilitation needed to maximise patient outcomes and reduce disability. Evidence about effects of individual treatment techniques and modalities is synthesised within many reviews. For selection of effective rehabilitation treatment, the relative effectiveness of interventions must be known. However, a comprehensive overview of systematic reviews in this area is currently lacking. Objectives: To carry out a Cochrane overview by synthesising systematic reviews of interventions provided to improve upper limb function after stroke. Methods: Search methods: We comprehensively searched the Cochrane Database of Systematic Reviews; the Database of Reviews of Effects; and PROSPERO (an international prospective register of systematic reviews) (June 2013). We also contacted review authors in an effort to identify further relevant reviews. Selection criteria: We included Cochrane and non‐Cochrane reviews of randomised controlled trials (RCTs) of patients with stroke comparing upper limb interventions with no treatment, usual care or alternative treatments. Our primary outcome of interest was upper limb function; secondary outcomes included motor impairment and performance of activities of daily living. When we identified overlapping reviews, we systematically identified the most up‐to‐date and comprehensive review and excluded reviews that overlapped with this. Data collection and analysis: Two overview authors independently applied the selection criteria, excluding reviews that were superseded by more up‐to‐date reviews including the same (or similar) studies. Two overview authors independently assessed the methodological quality of reviews (using a modified version of the AMSTAR tool) and extracted data. Quality of evidence within each comparison in each review was determined using objective criteria (based on numbers of participants, risk of bias, heterogeneity and review quality) to apply GRADE (Grades of Recommendation, Assessment, Development and Evaluation) levels of evidence. We resolved disagreements through discussion. We systematically tabulated the effects of interventions and used quality of evidence to determine implications for clinical practice and to make recommendations for future research. Main results: Our searches identified 1840 records, from which we included 40 completed reviews (19 Cochrane; 21 non‐Cochrane), covering 18 individual interventions and dose and setting of interventions. The 40 reviews contain 503 studies (18,078 participants). We extracted pooled data from 31 reviews related to 127 comparisons. We judged the quality of evidence to be high for 1/127 comparisons (transcranial direct current stimulation (tDCS) demonstrating no benefit for outcomes of activities of daily living (ADLs)); moderate for 49/127 comparisons (covering seven individual interventions) and low or very low for 77/127 comparisons. Moderate‐quality evidence showed a beneficial effect of constraint‐induced movement therapy (CIMT), mental practice, mirror therapy, interventions for sensory impairment, virtual reality and a relatively high dose of repetitive task practice, suggesting that these may be effective interventions; moderate‐quality evidence also indicated that unilateral arm training may be more effective than bilateral arm training. Information was insufficient to reveal the relative effectiveness of different interventions. Moderate‐quality evidence from subgroup analyses comparing greater and lesser doses of mental practice, repetitive task training and virtual reality demonstrates a beneficial effect for the group given the greater dose, although not for the group given the smaller dose; however tests for subgroup differences do not suggest a statistically significant difference between these groups. Future research related to dose is essential. Specific recommendations for future research are derived from current evidence. These recommendations include but are not limited to adequately powered, high‐quality RCTs to confirm the benefit of CIMT, mental practice, mirror therapy, virtual reality and a relatively high dose of repetitive task practice; high‐quality RCTs to explore the effects of repetitive transcranial magnetic stimulation (rTMS), tDCS, hands‐on therapy, music therapy, pharmacological interventions and interventions for sensory impairment; and up‐to‐date reviews related to biofeedback, Bobath therapy, electrical stimulation, reach‐to‐grasp exercise, repetitive task training, strength training and stretching and positioning. Authors' conclusions: Large numbers of overlapping reviews related to interventions to improve upper limb function following stroke have been identified, and this overview serves to signpost clinicians and policy makers toward relevant systematic reviews to support clinical decisions, providing one accessible, comprehensive document, which should support clinicians and policy makers in clinical decision making for stroke rehabilitation. Currently, no high‐quality evidence can be found for any interventions that are currently used as part of routine practice, and evidence is insufficient to enable comparison of the relative effectiveness of interventions. Effective collaboration is urgently needed to support large, robust RCTs of interventions currently used routinely within clinical practice. Evidence related to dose of interventions is particularly needed, as this information has widespread clinical and research implications

    How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

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    Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

    Computational neurorehabilitation: modeling plasticity and learning to predict recovery

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    Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity

    Effects of Robot-assisted Upper Extremity Rehabilitation on Change in Functioning and Disability in Patients With Neurologic Impairment: A Pilot Study

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    Introduction: The aim is to evaluate the effect of robot-assisted training on the most important aspects of functioning and disability in patients with upper extremity neurologic impairment. Materials and Methods: A prospective six-week pilot study included robot-assisted training of the upper extremity and conventional neurorehabilitation in 12 participants after a stroke or traumatic brain injury. Outcome measurements were range of motion (ROM), the International Classification of Functioning, Disability and Health (ICF) Core Set for Hand and the Visual Analog Scale (VAS) for pain sensation. A Wilcoxon test was used for the analysis of pre- and post-test differences and Spearman’s correlation was used for connecting the data collected. Results: A statistically significant difference was found for ROM (shoulder abduction/adduction, shoulder flexion/extension, shoulder internal/external rotation and forearm pronation/supination) and a number of ICF categories (Body Function: b280, b710, b715, b730, b760; Activities and Participation: d230, d430, d440, d445, d5). A significant positive correlation of medium intensity (r=0.589) was found between the duration of movement coordination training and the ICF category b760. We did not find a statistically significant difference in pain sensation (VAS) with regard to the direct use of the device. For all analyses, p<0.05 and CI was 95%. Conclusion: Robot-assisted training and conventional neurorehabilitation improved motor and functional recovery. There was a correlation between training a specific goal on the device and one of the ICF Body Function categories

    Robot-aided therapy for upper limbs in patients with stroke-related lesions. Brief report of a clinical experience

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    This study was aimed at verifying the improvement on the motor impairment and functionality in 19 patients with chronic hemiparesis after stroke treated with a robot-aided rehabilitation protocol using the ReoGoℱ system (Motorika Medical Ltd, Israel), and at evaluating the persistence of the effects after 1 month. The study also focused on the actual possibility of administering the robot-aided therapy with the ReoGoℱ for the upper limbs and on the patients' degree of acceptance and compliance with the treatment. Subjects underwent an assessment prior to the start of the rehabilitation project (T-1), one at the start (T0), one at the end of the treatment (T1) and one after one month from the end of the treatment (T2). The following tests were administered: (i) Fugl-Meyer (FM) upper limb; Ashworth scale (AS); Functional Independence Measure (FIMℱ) (T-1 - T2); (ii) strength evaluation; Visual Analogue Scale (VAS) for pain; Frenchay Arm test (FAT); Box and Block test (BBT); Timed Up and Go (TUG) test (T0 - T2). Additionally, the Euro-QoL questionnaire and a VAS for the treatment satisfaction were administered to the subjects. Non-statistical difference of scores at T-1 and T0 on almost the entire battery of tasks suggested a stable patients' performance prior to the start of the rehabilitation. With the exception of the Medical Research Council (MRC) and the AS sub-scales measuring -as appropriate- strength and spasticity of the shoulder, triceps and wrist, all scores showed a significant increase between T0 and T1. The improvement on the pain could not be proved significant (p = 0.10). A significant increase between T0 and T2 was found for all assessment scores, with the exception of the MRC for external shoulder rotators (p = 0.05) and of the AS for shoulder (p = 0.32) and wrist (p = 0.08). Substantial stability was observed between T1 and T2. Patients were capable of completing the treatment and showed good participant satisfaction. This pilot study led to the finding of a clinical improvement and excellent patients compliance. It is possible that the learning process experienced by the patients was robot-dependent, especially in consideration of the general maintenance of the achievements observed on all activities
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