ArticleBiomedical engineering online2018
Augmented reality-based electrode guidance system for reliable electroencephalography.
Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Quantifying the impact of hair and skin characteristics on fNIRS signal quality for enhanced inclusivity.Nature human behaviour · 2025Article
- Virtual reality vs. Manikin based training on emergency life saving basic rescue skills: a summative evaluation.BMC medical education · 2025Article
- Improving neuroimaging headgear placement robustness using facial-landmark-guided augmented reality.Neurophotonics · 2025Article
- Improving neuroimaging headgear placement robustness using facial-landmark guided augmented reality.bioRxiv : the preprint server for biology · 2025Article
- High-density multidistance fNIRS enhances detection of brain activity during a word-color Stroop task.Neurophotonics · 2025Article
- Scalp electrode placement accuracy for the canine electroencephalography array.Frontiers in veterinary science · 2025Article
- Quantifying the Impact of Hair and Skin Characteristics on Signal Quality with Practical Recommendations for Improvement.bioRxiv : the preprint server for biology · 2024Article
- Canine Electroencephalography Electrode Positioning Using a Neuronavigation System.Animals : an open access journal from MDPI · 2024Article
- Using the MoBI motion capture system to rapidly and accurately localize EEG electrodes in anatomic space.The European journal of neuroscience · 2021Article
- The importance of modeling the human cerebral vasculature in blunt trauma.Biomedical engineering online · 2021Article
- More Reliable EEG Electrode Digitizing Methods Can Reduce Source Estimation Uncertainty, but Current Methods Already Accurately Identify Brodmann Areas.Frontiers in neuroscience · 2019Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundIn longitudinal electroencephalography (EEG) studies, repeatable electrode positioning is essential for reliable EEG assessment. Conventional methods use anatomical landmarks as fiducial locations for the electrode placement. Since the landmarks are manually identified, the EEG assessment is inevitably unreliable because of individual variations among the subjects and the examiners. To overcome this unreliability, an augmented reality (AR) visualization-based electrode guidance system was proposed.
methodsThe proposed electrode guidance system is based on AR visualization to replace the manual electrode positioning. After scanning and registration of the facial surface of a subject by an RGB-D camera, the AR of the initial electrode positions as reference positions is overlapped with the current electrode positions in real time. Thus, it can guide the position of the subsequently placed electrodes with high repeatability.
resultsThe experimental results with the phantom show that the repeatability of the electrode positioning was improved compared to that of the conventional 10-20 positioning system.
conclusionThe proposed AR guidance system improves the electrode positioning performance with a cost-effective system, which uses only RGB-D camera. This system can be used as an alternative to the international 10-20 system.
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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.