ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
BrainFusion: a Low-Code, Reproducible, and Deployable Software Framework for Multimodal Brain‒Computer Interface and Brain‒Body Interaction Research.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Dataset Fragmentation, Cognitive Variability, and Reproducibility Challenges in EEG-Based Brain-Computer Interfaces: A PRISMA-Based Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- From Signal Stacking to Dynamic Coupling: A Critical Review of Wearable EEG-EMG Fusion Brain-Computer Interfaces for Stroke Rehabilitation.Micromachines · 2026Review
- Non-Invasive Brain-Computer Interfaces: Converging Frontiers in Neural Signal Decoding and Flexible Bioelectronics Integration.Nano-micro letters · 2026Review
- Article
- AI-Driven Multimodal Brain-State Decoding for Personalized Closed-Loop TENS: A Comprehensive Review.Brain sciences · 2025Review
- BrainFusion: a Low-Code, Reproducible, and Deployable Software Framework for Multimodal Brain‒Computer Interface and Brain‒Body Interaction Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
This study presents BrainFusion, a unified software framework designed to improve reproducibility and support translational applications in multimodal brain-computer interface (BCI) and brain-body interaction research. While electroencephalography (EEG)-based BCIs have advanced considerably, integrating multimodal physiological signals remains hindered by analytical complexity, limited standardization, and challenges in real-world deployment. BrainFusion addresses these gaps through standardized data structures, automated preprocessing pipelines, cross-modal feature engineering, and integrated machine learning modules. Its application generator further enables streamlined deployment of workflows as standalone executables. Demonstrated in two case studies, BrainFusion achieves 95.5% accuracy in within-subject EEG-functional near-infrared spectroscopy (fNIRS) motor imagery classification using ensemble modeling and 80.2% accuracy in EEG-electrocardiography (ECG) sleep staging using deep learning, with the latter successfully deployed as an executable tool. Supporting EEG, fNIRS, electromyography (EMG), and ECG, BrainFusion provides a low-code, visually guided environment, facilitating accessibility and bridging the gap between multimodal research and application in real world.
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.