Local Pattern Transformation-Based convolutional neural network for sleep stage scoring
Yükleniyor...
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ScienceDirect
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Sleep stage scoring is essential for the diagnosis and treatment of sleep disorders. However, manual sleep scoring
is a tedious, time-consuming, and subjective task. Therefore, this paper proposes a novel framework based on
local pattern transformation (LPT) methods and convolutional neural networks for automatic sleep stage scoring.
Unlike in previous works in other fields, these methods were not employed for manual feature extraction, which
requires expert knowledge and the pipeline behind it might bias results. The transformed signals were directly
fed into a CNN model (called EpochNet) that can accept multiple successive epochs. The model learns features
from multiple input epochs and considers inter-epoch context during classification. To evaluate and validate the
effectiveness of the proposed approach, we conducted several experiments on the Sleep-EDF dataset. Four LPT
methods, including One-dimensional Local Binary Pattern (1D-LBP), Local Neighbor Descriptive Pattern (LNDP),
Local Gradient Pattern (LGP), and Local Neighbor Gradient Pattern (LNGP), and different polysomnography
(PSG) signals were analyzed as sequence length (number of input epochs) increased from one to five. 1D-LBP and
LNDP achieved similar performances, outperforming other LPT methods that are less sensitive to local variations.
The best performance was achieved when an input sequence containing five epochs of PSG signals transformed
by 1D-LBP was employed. The best accuracy, F1 score, and Kohen’s kappa coefficient were 0.848, 0.782, and
0.790, respectively. The results showed that our approach can achieve comparable performance to other state-ofthe-art methods while occupying fewer computing resources because of the compact size of EpochNet.
Açıklama
Anahtar Kelimeler
Sleep stage scoringLocal pattern TransformationLPTOne-dimensional Local Binary Pattern1D-LBPLocal Neighbor Descriptive PatternLNDPLocal Gradient PatternLGPLocal Neighbor Gradient PatternLNGPConvolutional neural networkCNN
Kaynak
Biomedical Signal Processing and Control
WoS Q Değeri
Q2
Scopus Q Değeri
N/A
Cilt
80
Sayı
1
Künye
Zan, H., & Yildiz, A. (2023). Local Pattern Transformation-Based convolutional neural network for sleep stage scoring. Biomedical Signal Processing and Control, 80, 104275.
