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Postprocessing-Enhanced Machine Learning for Reliable Real-Time Sleep Staging in Closed-Loop Neuromodulation

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Detection of Change Points in Time Series with Moving Average Filters and Wavelet Transform: Application to EEG Signals
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Case studies and analysis of wind energy systems
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No Effects of Slow Oscillatory Transcranial Direct Current Stimulation (tDCS) on Sleep-Dependent Memory Consolidation in Healthy Elderly Subjects
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Slow-oscillatory Transcranial Direct Current Stimulation Modulates Memory in Temporal Lobe Epilepsy by Altering Sleep Spindle Generators: A Possible Rehabilitation Tool
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Adaptive Deep Brain Stimulation for sleep stage targeting in Parkinson’s disease
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Automatic sleep stage classification: From classical machine learning methods to deep learning
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Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field
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Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research
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Electrodiagnostic artifacts due to neurostimulation devices for drug resistant epilepsy
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Ten deep learning techniques to address small data problems with remote sensing
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A system based on machine learning for improving sleep
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Reducing power line noise in EEG and MEG data via spectrum interpolation
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Nonstationary nature of the brain activity as revealed by EEG/MEG: Methodological, practical and conceptual challenges
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Modulation of Total Sleep Time by Transcranial Direct Current Stimulation (tDCS)
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ANPHY-Sleep: an Open Sleep Database from Healthy Adults Using High-Density Scalp Electroencephalogram
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Auditory deep sleep stimulation in older adults at home: a randomized crossover trial
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A wearable EEG system for closed-loop neuromodulation of sleep-related oscillations
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Automatic sleep staging using a single-channel EEG modeling by Kalman Filter and HMM
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Automatic estimation of sleep level for nap based on conditional probability of sleep stages and an exponential smoothing method
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Sleep Stage Classification Using Bidirectional LSTM in Wearable Multi-sensor Systems
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Reluplex made more practical: Leaky ReLU
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MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG
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Automatic Stage Scoring of Single-Channel Sleep EEG by Using Multiscale Entropy and Autoregressive Models
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DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG
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The relationship between Precision-Recall and ROC curves
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REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild
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The choice of methods in determining the optimal cut-off value for quantitative diagnostic test evaluation
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Determining Best Window Size for an Improved Gabor Transform in EMG Signal Analysis
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DREAMT: Dataset for Real-time sleep stage EstimAtion using Multisensor wearable Technology
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Kalman filtering to reduce measurement noise of sample entropy: An electroencephalographic study
inferredcites →https://doi.org/10.3389/fnhum.2018.00088openalex-snapshot
Performance of an Ambulatory Dry-EEG Device for Auditory Closed-Loop Stimulation of Sleep Slow Oscillations in the Home Environment
inferredcites →https://doi.org/10.3389/fnhum.2019.00123openalex-snapshot
Short Duration Repetitive Transcranial Electrical Stimulation During Sleep Enhances Declarative Memory of Facts
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Automatic Sleep Staging Algorithm Based on Time Attention Mechanism
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On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders
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A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy
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Quantitative Evaluation of EEG-Biomarkers for Prediction of Sleep Stages
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Masseter EMG activity during sleep and sleep bruxism.
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inferred← citeshttps://doi.org/10.1007/978-981-92-3485-1_33openalex-snapshot
Online Sleep Staging via Test-Time Adaptation: An Enhanced DBConformer Approach
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