mlsanityData to 7 Oct 2026

REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates

arXiv 2406.16906 ↗First posted 3 Jun 2024eess.SP cs.AI cs.LGcited by 11

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Abstract (arXiv)

EEG-based seizure detection models face challenges in terms of inference speed and memory efficiency, limiting their real-time implementation in clinical devices. This paper introduces a novel graph-based residual state update mechanism (REST) for real-time EEG signal analysis in applications such as epileptic seizure detection. By leveraging a combination of graph neural networks and recurrent structures, REST efficiently captures both non-Euclidean geometry and temporal dependencies within EEG data. Our model demonstrates high accuracy in both seizure detection and classification tasks. Notably, REST achieves a remarkable 9-fold acceleration in inference speed compared to state-of-the-art models, while simultaneously demanding substantially less memory than the smallest model employed for this task. These attributes position REST as a promising candidate for real-time implementation in clinical devices, such as Responsive Neurostimulation or seizure alert systems.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 18 of its 47 references that are in the map. First posted on arXiv 3 Jun 2024.

Builds on

18 of 47 references.

References · 18

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
  4. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  5. 2019Deep Double Descent: Where Bigger Models and More Data Hurtcited by 667
  6. 2018The Temple University Hospital Seizure Detection Corpuscited by 80
  7. 2021Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysiscited by 75
  8. 2017Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecastingcited by 36
  9. 2019Temporal Graph Convolutional Networks for Automatic Seizure Detectioncited by 20
  10. 2019Neural Memory Networks for Seizure Type Classificationcited by 19
  11. 2022DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automatacited by 18
  12. 2016Learning Robust Features using Deep Learning for Automatic Seizure Detectioncited by 16
6 more
  1. 2020ResOT: Resource-Efficient Oblique Trees for Neural Signal Classificationcited by 12
  2. 2021Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecturecited by 12
  3. 2019Convolutional neural network for detection and classification of seizures in clinical datacited by 8
  4. 2022Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Settingcited by 8
  5. 2022NeuralTree: A 256-Channel 0.227-μJ/Class Versatile Neural Activity Classification and Closed-Loop Neuromodulation SoCcited by 8
  6. 2021Closed-Loop Neural Prostheses with On-Chip Intelligence: A Review and A Low-Latency Machine Learning Model for Brain State Detectioncited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 5.

11 papers.

  1. 2024TimeLDM: Latent Diffusion Model for Unconditional Time Series Generationcited by 10
  2. 2025BioMamba: Leveraging Spectro-Temporal Embedding in Bidirectional Mamba for Enhanced Biosignal Classificationcited by 3
  3. 2025MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detectioncited by 0
  4. 2025Machine-Learning-Powered Neural Interfaces for Smart Prosthetics and Diagnosticscited by 0
  5. 2025Personalization on a Budget: Minimally-Labeled Continual Learning for Resource-Efficient Seizure Detectioncited by 0
  6. 2025Neurocircuitry-Inspired Hierarchical Graph Causal Attention Networks for Explainable Depression Identificationcited by 0
  7. 2026The Powers of Precision: Structure-Informed Detection in Complex Systems -- From Customer Churn to Seizure Onsetcited by 0
  8. 2026NeuroCanvas: VLLM-Powered Robust Seizure Detection by Reformulating Multichannel EEG as Imagecited by 0
  9. 2026Atoms of Thought: Universal EEG Representation Learning with Microstatescited by 0
  10. 2026Revitalizing Medical Time Series with Vision-Informed Retrieval: A Vision-Language Perspectivecited by 0
  11. 2026GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modelingcited by 0