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Sleep stage scoring on MASS (subject-wise)

87.5AccuracyTinySleepNet
77.51680.10882.785.292Mar 12, 2017Jan 31, 2018Dec 22, 2018Nov 12, 2019Oct 2, 2020Aug 23, 2021Jul 15, 2022

Evaluation results

MethodLinks
TinySleepNetYear=2020, Technique=CNN & RNN, LP=LFS, Signals=EEG2022.0787.583.20.82—————
Classical ML PipelineYear=2022, Technique=Catboost, LP=LFS, Signals=EEG + EOG + EMG2022.0786.781.70.803—————
IITNetArchitecture=CNN + RNN, Channel=F4-EOG (left), Input=Raw Signal, Approach=Many-to-One, Sequence Length=10 (9 past), Subjects=622019.0286.380.50.7985.454.191.386.884.8
Classical ML PipelineYear=2022, Technique=Catboost, LP=LFS, Signals=EEG + EOG2022.0786.380.90.797—————
IITNetYear=2019, Technique=CNN & RNN, LP=LFS, Signals=EEG2022.0786.380.50.79—————
DeepSleepNetEEG Channel=F4-EOG (Left), Test Epochs=586002017.0386.281.70.887.359.890.381.589.3
IITNetArchitecture=CNN + RNN, Channel=F4-EOG (left), Input=Raw Signal, Approach=Many-to-One, Sequence Length=4 (3 past), Subjects=622019.0286.2800.7985.251.891.486.984.5
SupratakArchitecture=CNN + RNN, Channel=F4-EOG (left), Input=Raw Signal, Approach=Many-to-One, Sequence Length=Whole previous night epochs, Subjects=622019.0286.281.70.887.359.890.381.589.3
DeepSleepNetYear=2017, Technique=CNN & RNN, LP=FT, Signals=EEG2022.0786.281.70.8—————
Ref. [13]EEG Channel=F4-EOG (Left), Test Epochs=590662017.0385.980.5—84.656.390.784.886.1
DongArchitecture=Mixed RNN, Channel=F4-EOG (left), Input=Handcrafted Features, Approach=Many-to-One, Sequence Length=5 (4 past), Subjects=622019.0285.980.50.7984.656.390.784.886.1
Classical ML PipelineYear=2022, Technique=Logistic regr., LP=LFS, Signals=EEG + EOG + EMG2022.0785.380.70.786—————
IITNetArchitecture=CNN + RNN, Channel=F4-EOG (left), Input=Raw Signal, Approach=One-to-One, Sequence Length=1, Subjects=622019.0284.576.60.7786.936.890.588.181
Classical ML PipelineYear=2022, Technique=Logistic regr., LP=LFS, Signals=EEG + EOG2022.0784.579.40.775—————
Multitask 1-max CNNInput channel=C4-A1 + ROC-LOC + CHIN1-CHIN2, Feature type=learned, Subjects=200, Independent testing=yes2018.0583.6———————
Multitask 1-max CNNInput channel=C4-A1 + ROC-LOC, Feature type=learned, Subjects=200, Independent testing=yes2018.0582.5———————
DeepSleepNet (Deep CNN)Input channel=C4-A1 + ROC-LOC + CHIN1-CHIN2, Feature type=learned, Subjects=200, Independent testing=yes2018.0580.7———————
Deep CNNInput channel=C4-A1 + ROC-LOC + CHIN1-CHIN2, Feature type=learned, Subjects=200, Independent testing=yes2018.0579.9———————
ResNetInput channel=C4-A1 + ROC-LOC + CHIN1-CHIN2, Feature type=learned, Subjects=200, Independent testing=yes2018.0579.4———————
Multitask 1-max CNNInput channel=C4-A1, Feature type=learned, Subjects=200, Independent testing=yes2018.0578.6———————
PhanArchitecture=Multitask 1-max CNN, Channel=C4-A1, Input=Spectrogram, Approach=One-to-Many, Sequence Length=1, Subjects=2002019.0278.670.60.7—————
Deep CNN (Tsinalis et al.)Input channel=C4-A1 + ROC-LOC + CHIN1-CHIN2, Feature type=learned, Subjects=200, Independent testing=yes2018.0577.9———————
RobustSleepNetYear=2021, Technique=RNN, LP=FT, Signals=EEG + EOG2022.07—84——————
RobustSleepNetYear=2021, Technique=RNN, LP=LFS, Signals=EEG + EOG2022.07—82.2——————
RobustSleepNetYear=2021, Technique=RNN, LP=DT, Signals=EEG + EOG2022.07—80.8——————
SimpleSleepNetYear=2020, Technique=RNN, LP=LFS, Signals=EEG + EOG2022.07—84.7——————
U-SleepYear=2021, Technique=CNN, LP=DT, Signals=EEG + EOG2022.07—80——————