Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms

Mark Orsullivan; Sergi Gomez; Alison Orshea; Eduard Salgado; Kevin Huillca; Sean Mathieson; Geraldine Boylan; Emanuel Popovici; Andriy Temko

doi:10.1109/EMBC.2018.8513231

Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms

Mark Orsullivan
, Sergi Gomez
, Alison Orshea
, Eduard Salgado
, Kevin Huillca
, Sean Mathieson
, Geraldine Boylan
, Emanuel Popovici
, Andriy Temko

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

Abstract

This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals, particularly those without EEG interpretation expertise. The system aims to increase the demographic of clinicians capable of diagnosing abnormalities in neonatal EEG. The proposed system uses a low-cost and low-power EEG acquisition system. An Android app provides single-channel EEG visualization, traffic-light indication of the presence of neonatal seizures provided by a trained, deep convolutional neural network and an algorithm for EEG sonification, designed to facilitate the perception of changes in EEG morphology specific to neonatal seizures. The multifaceted EEG interpretation framework is presented and the implemented mobile platform architecture is analyzed with respect to its power consumption and accuracy.

Original language	English
Title of host publication	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4881-4884
Number of pages	4
ISBN (Electronic)	9781538636466
DOIs	https://doi.org/10.1109/EMBC.2018.8513231
Publication status	Published - 26 Oct 2018
Event	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States Duration: 18 Jul 2018 → 21 Jul 2018

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2018-July
ISSN (Print)	1557-170X

Conference

Conference	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/Territory	United States
City	Honolulu
Period	18/07/18 → 21/07/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1109/EMBC.2018.8513231

Cite this

Orsullivan, M., Gomez, S., Orshea, A., Salgado, E., Huillca, K., Mathieson, S., Boylan, G., Popovici, E., & Temko, A. (2018). Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 4881-4884). Article 8513231 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2018.8513231

Orsullivan, Mark ; Gomez, Sergi ; Orshea, Alison et al. / Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 4881-4884 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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title = "Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms",

abstract = "This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals, particularly those without EEG interpretation expertise. The system aims to increase the demographic of clinicians capable of diagnosing abnormalities in neonatal EEG. The proposed system uses a low-cost and low-power EEG acquisition system. An Android app provides single-channel EEG visualization, traffic-light indication of the presence of neonatal seizures provided by a trained, deep convolutional neural network and an algorithm for EEG sonification, designed to facilitate the perception of changes in EEG morphology specific to neonatal seizures. The multifaceted EEG interpretation framework is presented and the implemented mobile platform architecture is analyzed with respect to its power consumption and accuracy.",

author = "Mark Orsullivan and Sergi Gomez and Alison Orshea and Eduard Salgado and Kevin Huillca and Sean Mathieson and Geraldine Boylan and Emanuel Popovici and Andriy Temko",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 ; Conference date: 18-07-2018 Through 21-07-2018",

year = "2018",

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doi = "10.1109/EMBC.2018.8513231",

language = "English",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

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Orsullivan, M, Gomez, S, Orshea, A, Salgado, E, Huillca, K, Mathieson, S , Boylan, G , Popovici, E & Temko, A 2018, Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018., 8513231, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 4881-4884, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, United States, 18/07/18. https://doi.org/10.1109/EMBC.2018.8513231

Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms. / Orsullivan, Mark; Gomez, Sergi; Orshea, Alison et al.
40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 4881-4884 8513231 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

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AU - Huillca, Kevin

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AU - Boylan, Geraldine

AU - Popovici, Emanuel

AU - Temko, Andriy

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AB - This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals, particularly those without EEG interpretation expertise. The system aims to increase the demographic of clinicians capable of diagnosing abnormalities in neonatal EEG. The proposed system uses a low-cost and low-power EEG acquisition system. An Android app provides single-channel EEG visualization, traffic-light indication of the presence of neonatal seizures provided by a trained, deep convolutional neural network and an algorithm for EEG sonification, designed to facilitate the perception of changes in EEG morphology specific to neonatal seizures. The multifaceted EEG interpretation framework is presented and the implemented mobile platform architecture is analyzed with respect to its power consumption and accuracy.

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Orsullivan M, Gomez S, Orshea A, Salgado E, Huillca K, Mathieson S et al. Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 4881-4884. 8513231. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2018.8513231

Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms

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UN SDGs

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