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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) Journal of Applied Data Sciences International Journal of Robotics and Control Systems Sewagati Jurnal Penyakit Dalam Indonesia Journal of Medicine and Health Technology Bioma : Jurnal Biologi dan Pembelajaran Biologi
Yuri Pamungkas
Institut Teknologi Sepuluh Nopember
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Neuroscience Public Health Social Sciences Other

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Trends and Gaps in Transformer-Based EEG Modeling: A Review of Recent Developments Yuri Pamungkas; Abdul Karim; Myo Min Aung; Muhammad Nur Afnan Uda; Uda Hashim
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.14933

Abstract

In recent years, Transformer-based deep learning architectures have emerged as a powerful paradigm for modeling EEG signals, offering superior capability in capturing spatial–temporal dependencies compared to traditional convolutional or recurrent networks. However, the diversity of model designs, limited dataset generalization, and lack of standardization have created challenges in evaluating their true potential for real-world applications. This review addresses these issues by systematically examining the evolution, performance, and methodological trends of Transformer-based EEG models published between 2022 and 2024, highlighting both achievements and research gaps. The main contribution of this study is to provide a comprehensive mapping and critical analysis of Transformer architectures applied to EEG classification, feature extraction, and signal decoding tasks. Using the Scopus database, a structured search was conducted following specific inclusion criteria (English, peer-reviewed, open-access journal papers from 2022–2024) and a well-defined query combining EEG and Transformer-related keywords. Data from 63 eligible studies were extracted and categorized according to authorship, dataset, architecture type, EEG application, and evaluation metrics. Results show that hybrid Transformer models dominate recent research, achieving accuracies above 90% in tasks such as motor imagery, emotion recognition, seizure detection, and sleep staging. Pure Transformers like ViT and BERT-like models also demonstrate competitive performance but face scalability and interpretability challenges. In conclusion, Transformer-based EEG modeling is advancing rapidly, yet future efforts must focus on model efficiency, explainability, and benchmark standardization to enable broader clinical and real-world adoption.
Co-Authors Abdul Karim Abdul Karim Abdurahman Abdurrahman Achmad Syaifudin Adhi Dharma Wibawa Adhi Dharma Wibawa, Adhi Dharma Adrian Jaleco Forca Alfonsus Haryo Sangaji Aung, Myo Min Balqis, Dayana Satira Cahya, Meiliana Dwi Derek, Natan Dian Puspita Hapsari Djaputra, Edith Maria Dwinka Syafira Eljatin Elfrida Ratnawati Evi Triandini Fadli, Sonny Faiqoh, Elok Nur Fitriani, Fatimah Nur Forca, Adrian Jaleco Gao Yulan Ginting, Tsamarah Amelia Putri Hashim, Uda Haykal, Muhammad Nazhif Haykal, Muhammad. Najib Hedianto, Tri Hidayah, Rizka Nurul Imam Susilo Indriani, Ratri Dwi Indriastuti, Endah Indriastuti, Endah Karimah, Rumman Kendenan, Valentino Kuswanto, Djoko Larasati, Alya Puti Made Krisnanda Meiliana Dwi Cahya Meiliana Dwi Cahya Muhammad Faizi Muhammad Nur Afnan Uda Muhammad Rifqi Nur Ramadani Myo Min Aung Nakkliang, Kanittha Njoto, Edwin Nugroho Nugroho Njoto, Edwin Nur Rochmah, Nur Nur, Rossa Alfi Padma Nyoman Crisnapati Padma Nyoman Crisnapati Parlindungan, Putra Gelar Perwitasari, Rayi Kurnia Pratasik, Stralen Putra, Gumilar Fardhani Ami Putri Alief Siswanto Putri, Atina I.W. Putri, Atina Irani Wira Putri, Ziyan Nadia Putu Adi Guna Permana Rachmadiana, Josephine Larissa Radiansyah, Riva Satya Ramadani, Muhammad Rifqi Nur Rangkuti, Rahmah Yasinta Ridhoi, Ahmad Risald, Randi Achtiar Riva Satya Radiansyah Sain, Anabela Aulia Sakina Sangsawang, Thosporn Shofwan Hanief Supeno Mardi Susiki Nugroho, Supeno Mardi Syafira Eljatin, Dwinka Syulthoni, Zain Budi Thwe, Yamin Uda Hashim Uda, Muhammad Nur Afnan Wawan Yunanto Yamin Thwe Yulan, Gao Yuni Hisbiyah