ArticleFrontiers in neuroscience2025
Tackling the possibility of extracting a brain digital fingerprint based on personal hobbies predilection.
Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- DyAMNet: dynamic adversarial and contrastive network for EEG biometrics.Frontiers in neuroscience · 2026Article
- EEG-Based Authentication Across Various Event-Related Potentials (ERPs).Sensors (Basel, Switzerland) · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In an attempt to create a more familiar brain-machine interaction for biometric authentication applications, we investigated the efficiency of using the users' personal hobbies, interests, and memory collections. This approach creates a unique and pleasant experience that can be later utilized within an authentication protocol. This paper presents a new EEG dataset recorded while subjects watch images of popular hobbies, pictures with no point of interest and images with great personal significance. In addition, we propose several applications that can be tackled with our newly collected dataset. Namely, our study showcases 4 types of applications and we obtain state-of-the-art level results for all of them. The tackled tasks are: emotion classification, category classification, authorization process, and person identification. Our experiments show great potential for using EEG response to hobby visualization for people authentication. In our study, we show preliminary results for using predilection for personal hobbies, as measured by EEG, for identifying people. Also, we propose a novel authorization process paradigm using electroencephalograms. Code and dataset are available
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.