ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2020
Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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
23 citing papers in PubMed, 73 citations in OpenAlex.
- Functional near-infrared spectroscopy: Systematic mapping of abnormal brain function features in neurological disorders.Neural regeneration research · 2026Article
- Decoupled Bidirectional Spatio-Temporal Fusion Network for Hybrid EEG-fNIRS Cognitive Task Classification.Brain sciences · 2026Article
- Non-Invasive Brain-Computer Interfaces: Converging Frontiers in Neural Signal Decoding and Flexible Bioelectronics Integration.Nano-micro letters · 2026Review
- Cortical Representation of Auditory Selective Attention in a Dichotic Listening Task: A Functional Near-Infrared Spectroscopy Study.Brain topography · 2025Article
- Advancements in the application of brain-computer interfaces based on different paradigms in amyotrophic lateral sclerosis.Frontiers in neuroscience · 2025Review
- Review
- Compact convolutional transformer for subject-independent motor imagery EEG-based BCIs.Scientific reports · 2024Article
- A Brain Network Analysis Model for Motion Sickness in Electric Vehicles Based on EEG and fNIRS Signal Fusion.Sensors (Basel, Switzerland) · 2024Article
- Functional Near-Infrared Spectroscopy in neurodegenerative disease: a review.Frontiers in neuroscience · 2024Review
- It takes two (seconds): decreasing encoding time for two-choice functional near-infrared spectroscopy brain-computer interface communication.Neurophotonics · 2023Article
- Unlocking Hidden Awareness: Repurposing fMRI to Detect Levels of Consciousness.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2023Article
- Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference.Biosensors · 2022Article
- Multi-Task Learning-Based Deep Neural Network for Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces.Sensors (Basel, Switzerland) · 2022Article
- Applying antagonistic activation pattern to the single-trial classification of mental arithmetic.Heliyon · 2022Article
- Exploring the effects of head movements and accompanying gaze fixation switch on steady-state visual evoked potential.Frontiers in human neuroscience · 2022Article
- Improved classification performance of EEG-fNIRS multimodal brain-computer interface based on multi-domain features and multi-level progressive learning.Frontiers in human neuroscience · 2022Article
- Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach-Part II: Brain Signals.Sensors (Basel, Switzerland) · 2021Review
- Multimodal fusion of EEG-fNIRS: a mutual information-based hybrid classification framework.Biomedical optics express · 2021Article
- See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions.Frontiers in human neuroscience · 2021Article
- Motor Training Using Mental Workload (MWL) With an Assistive Soft Exoskeleton System: A Functional Near-Infrared Spectroscopy (fNIRS) Study for Brain-Machine Interface (BMI).Frontiers in neurorobotics · 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
8 authors at 1 institution in 1 country.
Funding
Abstract
objectiveBrain-computer interface (BCI) based communication remains a challenge for people with later-stage amyotrophic lateral sclerosis (ALS) who lose all voluntary muscle control. Although recent studies have demonstrated the feasibility of functional near-infrared spectroscopy (fNIRS) to successfully control BCIs primarily for healthy cohorts, these systems are yet inefficient for people with severe motor disabilities like ALS. In this study, we developed a new fNIRS-based BCI system in concert with a single-trial Visuo-Mental (VM) paradigm to investigate the feasibility of enhanced communication for ALS patients, particularly those in the later stages of the disease.
methodsIn the first part of the study, we recorded data from six ALS patients using our proposed protocol (fNIRS-VM) and compared the results with the conventional electroencephalography (EEG)-based multi-trial P3Speller (P3S). In the second part, we recorded longitudinal data from one patient in the late locked-in state (LIS) who had fully lost eye-gaze control. Using statistical parametric mapping (SPM) and correlation analysis, the optimal channels and hemodynamic features were selected and used in linear discriminant analysis (LDA).
resultsOver all the subjects, we obtained an average accuracy of 81.3%±5.7% within comparatively short times (< 4 sec) in the fNIRS-VM protocol relative to an average accuracy of 74.0%±8.9% in the P3S, though not competitive in patients with no substantial visual problems. Our longitudinal analysis showed substantially superior accuracy using the proposed fNIRS-VM protocol (73.2%±2.0%) over the P3S (61.8%±1.5%). SIGNIFICANCE: Our findings indicate the potential efficacy of our proposed system for communication and control for late-stage ALS patients.
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.