Papers with Code · CC BY-SA 4.0

Sleep Stage Detection

59 평가 기록 18 datasets

Human Sleep Staging into W-N1-N2-N3-REM classes from multiple or single polysomnography signals

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

벤치마크

Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.

Dataset기록된 모델 예시MetricPaperCode

SHHS

SynthSleepNet (EEG2+EOG2+EMG1)

Accuracy: 89.89%Cohen's Kappa: 0.860Macro-F1: 0.845

논문 코드

Sleep-EDF

SleePyCo (Fpz-Cz only)

Accuracy: 86.8%Macro-F1: 0.812Cohen's kappa: 0.820

논문 코드

MASS SS3

Deep Sleep Net

Accuracy: 89.1%

논문 코드

SHHS (single-channel)

MC2SleepNet 50% Masking (C4-A1 only)

Accuracy: 88.6%Cohen's Kappa: 0.841Macro-F1: 0.821

논문 코드

DODO

SimpleSleepNet

Accuracy: 88.7Kappa: 82.3

논문 코드

Sleep-EDFx

NeuroNet (Fpz-Cz only)

Accuracy: 85.24%Macro-F1: 0.798

논문 코드

Sleep-EDFx (single-channel)

NeuroNet (Fpz-Cz only)

Accuracy: 85.24%Macro-F1: 0.798

논문 코드

DODH

SimpleSleepNet

Accuracy: 89.9Kappa: 84.6

논문 코드

ISRUC-Sleep

SLEEPER-DT

Accuracy: 78.5AUROC: 84.7Kappa: 0.72

논문 -

MASS (single-channel)

SleePyCo (C4-A1 only)

Accuracy: 86.8%Cohen's Kappa: 0.811Macro-F1: 0.825

논문 코드

MASS SS2

IITNet (F4-EOG [Left] only)

Accuracy: 84.5%

논문 코드

Montreal Archive of Sleep Studies

SleePyCo (C4-A1 only)

Accuracy: 86.8%Cohen's kappa: 0.811Macro-F1: 0.825

논문 코드

데이터셋

18개

SHHS Sleep-EDF MASS SS3 SHHS (single-channel)DODO Sleep-EDFx Sleep-EDFx (single-channel)DODH ISRUC-Sleep MASS (single-channel)MASS SS2 Montreal Archive of Sleep Studies

논문

Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging

1911.03221 2019-10-31 이 페이지의 평가 4건

Accuracy: 89.9Kappa: 84.6

Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep Scoring

2207.07753 2022-07-15 이 페이지의 평가 2건

Accuracy: 86.6%Macro-F1: 0.810Cohen's kappa: 0.816

Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring

1710.00633 2017-10-02 이 페이지의 평가 1건

Accuracy: 81.3%

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

1703.04046 2017-03-12 이 페이지의 평가 1건

Accuracy: 82%Macro-F1: 0.769Cohen's kappa: 0.76

Intra- and Inter-epoch Temporal Context Network (IITNet) Using Sub-epoch Features for Automatic Sleep Scoring on Raw Single-channel EEG

1902.06562 2019-02-18 이 페이지의 평가 1건

Accuracy: 84.0%

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

1805.06546 2018-05-16 이 페이지의 평가 1건

Accuracy: 81.9%

SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning

2209.09452 2022-09-20 이 페이지의 평가 1건

Accuracy: 86.8%Macro-F1: 0.812Cohen's kappa: 0.820

XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging

2007.05492 2020-07-08 이 페이지의 평가 1건

Accuracy: 86.4%Macro-F1: 0.809Cohen's kappa: 0.813

라이브러리

Papers with Code 리더보드 row에 연결된 구현 저장소입니다.

github.com/Dreem-Organization/dreem-learning-evaluation 1 논문

github.com/Dreem-Organization/dreem-learning-open 1 논문

github.com/predict-idlab/sleep-linear 1 논문

github.com/akaraspt/deepsleepnet 1 논문

github.com/CVxTz/EEG_classification 1 논문

github.com/emadeldeen24/eval_ssl_ssc 1 논문

github.com/famousgrouse/AccSleepNet 1 논문

github.com/gist-ailab/IITNet-official 1 논문

하위 태스크

SS Sleep Staging 2 데이터셋 · 4 rows