ArticleScientific reports2022
EEG temporal-spatial transformer for person identification.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Data-Efficient EEG-Based Person Identification via Time-Interval-Based Multi-Positive Contrastive Learning.Sensors (Basel, Switzerland) · 2026Article
- Decoding multi-class motor attempt from the affected unilateral limbs in chronic stroke patients.Journal of neuroengineering and rehabilitation · 2026Article
- Efficient EEG-Based Person Identification: A Unified Framework from Automatic Electrode Selection to Intent Recognition.Sensors (Basel, Switzerland) · 2026Article
- Multi-scale EEG feature decoding with Swin Transformers for subject independent motor imagery BCIs.Scientific reports · 2026Article
- A dual-branch network with brain region-constrained attention for EEG emotion recognition.Frontiers in neuroscience · 2026Article
- Transformer-based deep learning model for predicting fNIRS short-channel signals.Neurophotonics · 2025Article
- Classification of Electroencephalography Motor Execution Signals Using a Hybrid Neural Network Based on Instantaneous Frequency and Amplitude Obtained via Empirical Wavelet Transform.Sensors (Basel, Switzerland) · 2025Article
- Transformers in EEG Analysis: A Review of Architectures and Applications in Motor Imagery, Seizure, and Emotion Classification.Sensors (Basel, Switzerland) · 2025Review
- Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data.Journal of neuroscience methods · 2024Article
- Feasibility of decoding covert speech in ECoG with a Transformer trained on overt speech.Scientific reports · 2024Article
- A fusion analytic framework for investigating functional brain connectivity differences using resting-state fMRI.Frontiers in neuroscience · 2024Article
- Deep temporal networks for EEG-based motor imagery recognition.Scientific reports · 2023Article
- Local and global convolutional transformer-based motor imagery EEG classification.Frontiers in neuroscience · 2023Article
- EEGformer: A transformer-based brain activity classification method using EEG signal.Frontiers in neuroscience · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
An increasing number of studies have been devoted to electroencephalogram (EEG) identity recognition since EEG signals are not easily stolen. Most of the existing studies on EEG person identification have only addressed brain signals in a single state, depending upon specific and repetitive sensory stimuli. However, in reality, human states are diverse and rapidly changing, which limits their practicality in realistic settings. Among many potential solutions, transformer is widely used and achieves an excellent performance in natural language processing, which demonstrates the outstanding ability of the attention mechanism to model temporal signals. In this paper, we propose a transformer-based approach for the EEG person identification task that extracts features in the temporal and spatial domains using a self-attention mechanism. We conduct an extensive study to evaluate the generalization ability of the proposed method among different states. Our method is compared with the most advanced EEG biometrics techniques and the results show that our method reaches state-of-the-art results. Notably, we do not need to extract any features manually.
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