ReviewFrontiers in neuroscience2020
A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback.
Review in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 4 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Vibrotactile stimulation for upper-limb neurorehabilitation and sensorimotor training: a systematic review of clinical and mechanistic evidence.Frontiers in bioengineering and biotechnology · 2026Pooled it
- Brain-machine interface-based training for improving upper extremity function after stroke: A meta-analysis of randomized controlled trials.Frontiers in neuroscience · 2022Pooled it
- Pooled it
- Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- From Signal Stacking to Dynamic Coupling: A Critical Review of Wearable EEG-EMG Fusion Brain-Computer Interfaces for Stroke Rehabilitation.Micromachines · 2026Review
- Design and Experimental Investigation of a Multi-Level Heartbeat Sound Feedback-Based Neurofeedback System: Neural Mechanisms.Sensors (Basel, Switzerland) · 2026Article
- Closed-loop EEG-based neurofeedback and brain-computer interface interventions for mental health: a review.Frontiers in neuroscience · 2026Review
- Personalized cognitive enhancement for older adults: An aging-friendly closed-loop human-machine interface framework.Ageing research reviews · 2025Review
- Recommendations for Combining Brain-Computer Interface, Motor Imagery, and Virtual Reality in Upper Limb Stroke Rehabilitation: Qualitative Participatory Design Study.JMIR rehabilitation and assistive technologies · 2025Article
- Decreased anxiety through haptic technology patch usage: A case-control comparison.Journal of family medicine and primary care · 2025Article
- NINFA: Non-commercial interface for neuro-feedback acquisitions.Neurophotonics · 2025Article
- Calibration and Modeling of the Semmes-Weinstein Monofilament for Diabetic Foot Management.Bioengineering (Basel, Switzerland) · 2024Article
- Comparison of Immediate Neuromodulatory Effects between Focal Vibratory and Electrical Sensory Stimulations after Stroke.Bioengineering (Basel, Switzerland) · 2024Article
- Interest of neurofeedback training for cognitive performance and risk of brain disorders in the military context.Frontiers in psychology · 2024Review
- An evaluation of transfer learning models in EEG-based authentication.Brain informatics · 2023Article
- Modulating Individual Alpha Frequency through Short-Term Neurofeedback for Cognitive Enhancement in Healthy Young Adults.Brain sciences · 2023Article
- Recent Developments in Haptic Devices Designed for Hearing-Impaired People: A Literature Review.Sensors (Basel, Switzerland) · 2023Review
- Continuous versus discrete robotic feedback for brain-computer interfaces aimed for neurorehabilitation.Frontiers in neurorobotics · 2023Article
- fMRI-based neurofeedback strategies and the way forward to treating phasic psychiatric symptoms.Frontiers in neuroscience · 2023Review
- Toward an Adapted Neurofeedback for Post-stroke Motor Rehabilitation: State of the Art and Perspectives.Frontiers in human neuroscience · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurofeedback (NF) and brain-computer interface (BCI) applications rely on the registration and real-time feedback of individual patterns of brain activity with the aim of achieving self-regulation of specific neural substrates or control of external devices. These approaches have historically employed visual stimuli. However, in some cases vision is unsuitable or inadequately engaging. Other sensory modalities, such as auditory or haptic feedback have been explored, and multisensory stimulation is expected to improve the quality of the interaction loop. Moreover, for motor imagery tasks, closing the sensorimotor loop through haptic feedback may be relevant for motor rehabilitation applications, as it can promote plasticity mechanisms. This survey reviews the various haptic technologies and describes their application to BCIs and NF. We identify major trends in the use of haptic interfaces for BCI and NF systems and discuss crucial aspects that could motivate further studies.
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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.