Trial reportJournal of neuroengineering and rehabilitation2016
Counteracting learned non-use in chronic stroke patients with reinforcement-induced movement therapy.
Trial report in Journal of neuroengineering and rehabilitation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 36 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Desaprendiendo la parálisis Aprendida Con RGS en Pacientes Afectos de Ictus
Personalised Health Motor and Cognitive Assistance System for RehAbilitation (PHRASE): A Randomized Clinical Trial
Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effect of virtual reality-based upper limb training on activity of daily living and quality of life among stroke survivors: a systematic review and meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Pragmatic Solutions for Stroke Recovery and Improved Quality of Life in Low- and Middle-Income Countries-A Systematic Review.Frontiers in neurology · 2020Pooled it
- Immersive virtual reality with synchronous neurostimulation for upper-limb recovery after stroke: a randomized feasibility trial.Nature medicine · 2026Trial
- Preventing slowing down of alpha rhythms in stroke patients through modulation of cortical excitatory-inhibitory balance: a randomized controlled trial.Journal of neuroengineering and rehabilitation · 2026Trial
- Systematic Review and Meta-analysis of the Efficacy of Shorter Duration Modified Constraint-Induced Movement Therapy (mCIMT) Programs.Archives of rehabilitation research and clinical translation · 2026Review
- Machine learning-based adaptive personalization in virtual reality stroke rehabilitation: a systematic review.Frontiers in rehabilitation sciences · 2026Review
- Robotic Ankle Assessment Post-Stroke: Reliability, Comparison to Therapists, and Benchmark Dataset Development.Sensors (Basel, Switzerland) · 2025Article
- Gravity support from a robotic exoskeleton increases spontaneous use of the nondominant upper extremity during a choice reaching task.Journal of neurophysiology · 2024Article
- Volitional Control of the Paretic Hand Post-Stroke Increases Finger Stiffness and Resistance to Robot-Assisted Movement.Proceedings of the ... IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics · 2024Article
- The use of accelerometer bracelets to evaluate arm motor function over a stroke rehabilitation period - an explorative observational study.Journal of neuroengineering and rehabilitation · 2024Observational
- Behavior Change Approaches in Digital Technology-Based Physical Rehabilitation Interventions Following Stroke: Scoping Review.Journal of medical Internet research · 2024Article
- Wearable Technology to Capture Arm Use of People With Stroke in Home and Community Settings: Feasibility and Early Insights on Motor Performance.Physical therapy · 2024Article
- Responsiveness and construct validity of two outcome measures of bilateral upper limb function in patients with chronic stroke.Frontiers in neurology · 2024Article
- Autonomy support encourages use of more-affected arm post-stroke.Journal of neuroengineering and rehabilitation · 2023Article
- Upper limb practice with a dynamic hand orthosis to improve arm and hand function in people after stroke: a feasibility study.Pilot and feasibility studies · 2023Article
- Review
- Interaction of network and rehabilitation therapy parameters in defining recovery after stroke in a Bilateral Neural Network.Journal of neuroengineering and rehabilitation · 2022Article
- ROBOCOP (ROBOtic Care of Poststroke Pain): Study Protocol for a Randomized Trial to Assess Robot-Assisted Functional and Motor Recovery and Impact on Poststroke Pain Development.Frontiers in neurology · 2022Article
- Effort, success, and side of lesion determine arm choice in individuals with chronic stroke.Journal of neurophysiology · 2022Article
- Estimating upper-extremity function from kinematics in stroke patients following goal-oriented computer-based training.Journal of neuroengineering and rehabilitation · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAfter stroke, patients who suffer from hemiparesis tend to suppress the use of the affected extremity, a condition called learned non-use. Consequently, the lack of training may lead to the progressive deterioration of motor function. Although Constraint-Induced Movement Therapies (CIMT) have shown to be effective in treating this condition, the method presents several limitations, and the high intensity of its protocols severely compromises its adherence. We propose a novel rehabilitation approach called Reinforcement-Induced Movement Therapy (RIMT), which proposes to restore motor function through maximizing arm use. This is achieved by exposing the patient to amplified goal-oriented movements in VR that match the intended actions of the patient. We hypothesize that through this method we can increase the patients self-efficacy, reverse learned non-use, and induce long-term motor improvements.
methodsWe conducted a randomized, double-blind, longitudinal clinical study with 18 chronic stroke patients. Patients performed 30 minutes of daily VR-based training during six weeks. During training, the experimental group experienced goal-oriented movement amplification in VR. The control group followed the same training protocol but without movement amplification. Evaluators blinded to group designation performed clinical measurements at the beginning, at the end of the training and at 12-weeks follow-up. We used the Fugl-Meyer Assessment for the upper extremities (UE-FM) (Sanford et al., Phys Ther 73:447-454, 1993) as a primary outcome measurement of motor recovery. Secondary outcome measurements included the Chedoke Arm and Hand Activity Inventory (CAHAI-7) (Barreca et al., Arch Phys Med Rehabil 6:1616-1622, 2005) for measuring functional motor gains in the performance of Activities of Daily Living (ADLs), the Barthel Index (BI) for the evaluation of the patient's perceived independence (Collin et al., Int Disabil Stud 10:61-63, 1988), and the Hamilton scale (Knesevich et al., Br J Psychiatr J Mental Sci 131:49-52, 1977) for the identification of improvements in mood disorders that could be induced by the reinforcement-based intervention. In order to study and predict the effects of this intervention we implemented a computational model of recovery after stroke.
resultsWhile both groups showed significant motor gains at 6-weeks post-treatment, only the experimental group continued to exhibit further gains in UE-FM at 12-weeks follow-up (p<.05). This improvement was accompanied by a significant increase in arm-use during training in the experimental group.
conclusionsImplicitly reinforcing arm-use by augmenting visuomotor feedback as proposed by RIMT seems beneficial for inducing significant improvement in chronic stroke patients. By challenging the patients' self-limiting believe system and perceived low self-efficacy this approach might counteract learned non-use.
trial registrationClinical Trials NCT02657070 .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.