A Survey on Deep Learning-based Non-Invasive Brain Signals:Recent Advances and New Frontiers
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Abstract (arXiv)
Brain-Computer Interface (BCI) bridges the human's neural world and the outer physical world by decoding individuals' brain signals into commands recognizable by computer devices. Deep learning has lifted the performance of brain-computer interface systems significantly in recent years. In this article, we systematically investigate brain signal types for BCI and related deep learning concepts for brain signal analysis. We then present a comprehensive survey of deep learning techniques used for BCI, by summarizing over 230 contributions most published in the past five years. Finally, we discuss the applied areas, opening challenges, and future directions for deep learning-based BCI.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 May 2019.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 2; 2025: 1; 2026: 1.
10 papers.
- 2023A survey and taxonomy of loss functions in machine learningcited by 15
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- 2022Embedding Temporal Convolutional Networks for Energy-Efficient PPG-Based Heart Rate Monitoringcited by 8
- 2024Riemannian Geometry-Based EEG Approaches: A Literature Reviewcited by 3
- 2024A Survey of Spatio-Temporal EEG data Analysis: from Models to Applicationscited by 3
- 2021Towards Interactive Reinforcement Learning with Intrinsic Feedbackcited by 2
- 2022DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selectioncited by 1
- 2023A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfacescited by 1
- 2025EEG-Based Acute Pain Classification: Machine Learning Model Comparison and Real-Time Clinical Feasibilitycited by 0
- 2026Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Netscited by 0
- 2026Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Nets5 May 2026
- 2025EEG-Based Acute Pain Classification: Machine Learning Model Comparison and Real-Time Clinical Feasibility7 Oct 2025
- 2024A Survey of Spatio-Temporal EEG data Analysis: from Models to Applications26 Sep 2024
- 2024Riemannian Geometry-Based EEG Approaches: A Literature Review19 Jul 2024
- 2023A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces21 Apr 2023
- 2023A survey and taxonomy of loss functions in machine learning13 Jan 2023
- 2022Q-PPG: Energy-Efficient PPG-based Heart Rate Monitoring on Wearable Devices24 Mar 2022
- 2022Embedding Temporal Convolutional Networks for Energy-Efficient PPG-Based Heart Rate Monitoring1 Mar 2022
- 2022DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection21 Feb 2022
- 2021Towards Interactive Reinforcement Learning with Intrinsic Feedback2 Dec 2021