ArticleFrontiers in neuroscience2024
Upper extremity training followed by lower extremity training with a brain-computer interface rehabilitation system.
Article in Frontiers in neuroscience, 2024. 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 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Parkinson's Disease Rehabilitation Using Neurofeedback With Functional Electrical Stimulation and Virtual Reality Feedback for Lower Extremities
A Randomized Controlled Pilot Study of Gait Rehabilitation in Stroke Patients Using Functional Electrical Stimulation and Visual Feedback
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- The effect of rehabilitation training based on brain-computer interface on limb function in stroke patients: a systematic review and meta-analyses.Frontiers in neurologyPooled it
- A lower-limb motor imagery BCI using virtual reality and novel calibration strategy in post-stroke patients.Medical & biological engineering & computing · 2026Article
- Modern Technologies Supporting Motor Rehabilitation After Stroke: A Narrative Review.Journal of clinical medicine · 2025Review
- Classification of Electroencephalography Motor Execution Signals Using a Hybrid Neural Network Based on Instantaneous Frequency and Amplitude Obtained via Empirical Wavelet Transform.Sensors (Basel, Switzerland) · 2025Article
- Current techniques for the treatment of spasticity and their effectiveness.EFORT open reviews · 2025Article
- [Expert consensus on TZhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2025Article
- Pathophysiology and Management Strategies for Post-Stroke Spasticity: An Update Review.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Brain-computer interfaces (BCIs) based on functional electrical stimulation have been used for upper extremity motor rehabilitation after stroke. However, little is known about their efficacy for multiple BCI treatments. In this study, 19 stroke patients participated in 25 upper extremity followed by 25 lower extremity BCI training sessions. Methods: Patients' functional state was assessed using two sets of clinical scales for the two BCI treatments. The Upper Extremity Fugl-Meyer Assessment (FMA-UE) and the 10-Meter Walk Test (10MWT) were the primary outcome measures for the upper and lower extremity BCI treatments, respectively. Results: Patients' motor function as assessed by the FMA-UE improved by an average of 4.2 points ( Discussion: The results of the current study provide evidence that both upper and lower extremity BCI treatments, as well as their combination, are effective in facilitating functional improvements after stroke. In addition, and most importantly improvements did not stop after the first 25 upper extremity BCI sessions.
Indexed as
Identifiers
What OpenQuestion holds
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.