Detail publikace

Sleep Scoring using Artificial Neural Networks

RONZHINA, M. JANOUŠEK, O. KOLÁŘOVÁ, J. NOVÁKOVÁ, M. HONZÍK, P. PROVAZNÍK, I.

Originální název

Sleep Scoring using Artificial Neural Networks

Český název

Sleep Scoring using Artificial Neural Networks

Anglický název

Sleep Scoring using Artificial Neural Networks

Typ

článek v časopise

Jazyk

en

Originální abstrakt

Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved e next to other classification methods e by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of nonlinear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.

Český abstrakt

Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved e next to other classification methods e by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of nonlinear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.

Anglický abstrakt

Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved e next to other classification methods e by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of nonlinear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.

Klíčová slova

Polysomnographic data, Sleep scoring, Features extraction, Artificial neural networks

Rok RIV

2012

Vydáno

01.06.2012

Nakladatel

Elsevier

Strany od

251

Strany do

263

Strany počet

13

BibTex


@article{BUT73020,
  author="Marina {Ronzhina} and Oto {Janoušek} and Jana {Kolářová} and Marie {Nováková} and Petr {Honzík} and Ivo {Provazník}",
  title="Sleep Scoring using Artificial Neural Networks",
  annote="Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved e next to other classification methods e by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of nonlinear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.",
  address="Elsevier",
  chapter="73020",
  howpublished="online",
  institution="Elsevier",
  number="16",
  volume="2012",
  year="2012",
  month="june",
  pages="251--263",
  publisher="Elsevier",
  type="journal article"
}