AUTOMATIC SLEEP SCORING VIA DEEP LEARNING: DO IT AT HOME!

被引：0
|
作者：
Fiorillo, L. [1 ]
Monachino, G. [1 ]
Bechny, M. [1 ]
Palo, G. [2 ]
Samaras-Tsakiris, K. [3 ]
du Toit, W. [3 ]
Meier, E. [3 ]
Melnykowycz, M. [3 ]
Agostini, V. [2 ]
Faraci, F. D. [1 ]
机构：
[1] Univ Appl Sci & Arts Southern Switzerland SUPSI, Dept Innovat Technol, MeDiTech, Lugano, Switzerland
[2] Polytech Univ Turin, Dept Elect & Telecommun, Turin, Italy
[3] IDUN Technol, Opfikon, Switzerland
来源：
SLEEP MEDICINE | 2024年 / 115卷
关键词：
D O I：
暂无
中图分类号：
R74 [神经病学与精神病学];
学科分类号：
摘要：
引用
收藏
页码：93 / 93
页数：1
相关论文
共 50 条
  • [1] Temporal dependency in automatic sleep scoring via deep learning based architectures: An empirical study
    Fiorillo, Luigi
    Wand, Michael
    Marino, Italo
    Favaro, Paolo
    Faraci, Francesca D.
    42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 3509 - 3512
  • [2] Do not sleep on traditional machine learning Simple and interpretable techniques are competitive to deep learning for sleep scoring
    Van Der Donckt, Jeroen
    Van Der Donckt, Jonas
    Deprost, Emiel
    Vandenbussche, Nicolas
    Rademaker, Michael
    Vandewiele, Gilles
    Van Hoecke, Sofie
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2023, 81
  • [3] Inter-database validation of a deep learning approach for automatic sleep scoring
    Alvarez-Estevez, Diego
    Rijsman, Roselyne M.
    PLOS ONE, 2021, 16 (08):
  • [4] A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series
    Yan, Rui
    Li, Fan
    Zhou, DongDong
    Ristaniemi, Tapani
    Cong, Fengyu
    28TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2020), 2021, : 1090 - 1094
  • [5] Channel Contribution in Deep Learning Based Automatic Sleep Scoring-How Many Channels Do We Need?
    Lu, Changqing
    Pathak, Shreyasi
    Englebienne, Gwenn
    Seifert, Christin
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2023, 31 : 494 - 505
  • [6] Evaluation of automatic scoring algorithm for home sleep diagnosis
    Rigau, Jordi
    Guerrero, Arnoldo
    Del Corral, Ignacio
    Pico, Antoni
    Masa, Juan F.
    Montserrat, Josep M.
    EUROPEAN RESPIRATORY JOURNAL, 2013, 42
  • [7] Automatic scoring of drug-induced sleep endoscopy for obstructive sleep apnea using deep learning
    Hanif, Umaer
    Kiaer, Eva Kirkegaard
    Capasso, Robson
    Liu, Stanley Y.
    Mignot, Emmanuel J. M.
    Sorensen, Helge B. D.
    Jennum, Poul
    SLEEP MEDICINE, 2023, 102 : 19 - 29
  • [8] Automatic sleep scoring: A deep learning architecture for multi-modality time series
    Yan, Rui
    Li, Fan
    Zhou, Dong Dong
    Ristaniemi, Tapani
    Cong, Fengyu
    JOURNAL OF NEUROSCIENCE METHODS, 2021, 348
  • [9] DEEP LEARNING FOR SCORING SLEEP BASED ON SIGNALS AVAILABLE IN HOME SLEEP APNEA TEST STUDIES: CARDIORESPIRATORY SLEEP STAGING
    Anderer, P.
    Ross, M.
    Cerny, A.
    Radha, M.
    Fonseca, P.
    SLEEP, 2020, 43 : A167 - A167
  • [10] Towards automatic home-based sleep apnea estimation using deep learning
    Retamales, Gabriela
    Gavidia, Marino E.
    Bausch, Ben
    Montanari, Arthur N.
    Husch, Andreas
    Goncalves, Jorge
    NPJ DIGITAL MEDICINE, 2024, 7 (01):
12345