Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram

Krit Charupanit; Michael D. Nunez; Danilo Bernardo; Martina Bebin; Darcy A. Krueger; Hope Northrup; Mustafa Sahin; Joyce Y. Wu; Beth A. Lopour

doi:10.1109/EMBC.2018.8513033

Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram

Krit Charupanit, Michael D. Nunez, Danilo Bernardo, Martina Bebin, Darcy A. Krueger, Hope Northrup, Mustafa Sahin, Joyce Y. Wu, Beth A. Lopour

Pediatrics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

High frequency oscillations (HFOs) > 80 Hz are a promising biomarker of epileptic tissue. Recent evidence has shown that spontaneous HFOs can be recorded from the scalp, but detection of these electrographic events remains a challenge. Here, we modified a simple automatic detector, used originally for intracranial EEG (iEEG) recordings, to detect ripples and fast ripples in scalp EEG. We analyzed scalp EEG recordings of seven subjects and validated our detector and artifact rejection algorithm via visual review. Of the candidate events marked by the detector, 40% and 60% were confirmed to be ripples and fast ripples, respectively, by human visual review, making this algorithm suitable for supervised detection. Detected HFOs occurred at a rate of <1/min in most channels, and the average duration was 47 and 24 ms for ripples and fast ripples, respectively. The simplicity of the algorithm, with only a single parameter, enables the consistent application of automatic detection across recording modalities, and it could therefore be a tool for the assessment and localization of epileptic activity.

Original language	English (US)
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	3116-3119
Number of pages	4
ISBN (Electronic)	9781538636466
DOIs	https://doi.org/10.1109/EMBC.2018.8513033
State	Published - Oct 26 2018
Event	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States Duration: Jul 18 2018 → Jul 21 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

Other

Other	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/Territory	United States
City	Honolulu
Period	7/18/18 → 7/21/18

Funding

ACKNOWLEDGMENT Research reported in this publication was supported by the National Institute of Neurological Disorders And Stroke of the National Institutes of Health under Award Number U01NS082320. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We are sincerely indebted to the generosity of the families and patients in TSC clinics across the United States who contributed their time and effort to this study. We would like to thank the Tuberous Sclerosis Alliance for their continued support in TSC research. We also thank Tian Lan for starting this study.

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC.2018.8513033

Cite this

Charupanit, K., Nunez, M. D., Bernardo, D., Bebin, M., Krueger, D. A., Northrup, H., Sahin, M., Wu, J. Y., & Lopour, B. A. (2018). Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 3116-3119). Article 8513033 (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.2018.8513033

Charupanit, Krit ; Nunez, Michael D. ; Bernardo, Danilo et al. / Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3116-3119 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{3f31994c69044d3c96a5f2444f54db24,

title = "Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram",

abstract = "High frequency oscillations (HFOs) > 80 Hz are a promising biomarker of epileptic tissue. Recent evidence has shown that spontaneous HFOs can be recorded from the scalp, but detection of these electrographic events remains a challenge. Here, we modified a simple automatic detector, used originally for intracranial EEG (iEEG) recordings, to detect ripples and fast ripples in scalp EEG. We analyzed scalp EEG recordings of seven subjects and validated our detector and artifact rejection algorithm via visual review. Of the candidate events marked by the detector, 40% and 60% were confirmed to be ripples and fast ripples, respectively, by human visual review, making this algorithm suitable for supervised detection. Detected HFOs occurred at a rate of <1/min in most channels, and the average duration was 47 and 24 ms for ripples and fast ripples, respectively. The simplicity of the algorithm, with only a single parameter, enables the consistent application of automatic detection across recording modalities, and it could therefore be a tool for the assessment and localization of epileptic activity.",

author = "Krit Charupanit and Nunez, {Michael D.} and Danilo Bernardo and Martina Bebin and Krueger, {Darcy A.} and Hope Northrup and Mustafa Sahin and Wu, {Joyce Y.} and Lopour, {Beth A.}",

note = "Funding Information: ACKNOWLEDGMENT Research reported in this publication was supported by the National Institute of Neurological Disorders And Stroke of the National Institutes of Health under Award Number U01NS082320. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We are sincerely indebted to the generosity of the families and patients in TSC clinics across the United States who contributed their time and effort to this study. We would like to thank the Tuberous Sclerosis Alliance for their continued support in TSC research. We also thank Tian Lan for starting this study. 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",

month = oct,

day = "26",

doi = "10.1109/EMBC.2018.8513033",

language = "English (US)",

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

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3116--3119",

booktitle = "40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018",

address = "United States",

}

Charupanit, K, Nunez, MD, Bernardo, D, Bebin, M, Krueger, DA, Northrup, H, Sahin, M, Wu, JY & Lopour, BA 2018, Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018., 8513033, 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. 3116-3119, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, United States, 7/18/18. https://doi.org/10.1109/EMBC.2018.8513033

Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. / Charupanit, Krit; Nunez, Michael D.; Bernardo, Danilo 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. 3116-3119 8513033 (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 proceeding › Conference contribution

TY - GEN

T1 - Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram

AU - Charupanit, Krit

AU - Nunez, Michael D.

AU - Bernardo, Danilo

AU - Bebin, Martina

AU - Krueger, Darcy A.

AU - Northrup, Hope

AU - Sahin, Mustafa

AU - Wu, Joyce Y.

AU - Lopour, Beth A.

N1 - Funding Information: ACKNOWLEDGMENT Research reported in this publication was supported by the National Institute of Neurological Disorders And Stroke of the National Institutes of Health under Award Number U01NS082320. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We are sincerely indebted to the generosity of the families and patients in TSC clinics across the United States who contributed their time and effort to this study. We would like to thank the Tuberous Sclerosis Alliance for their continued support in TSC research. We also thank Tian Lan for starting this study. Publisher Copyright: © 2018 IEEE.

PY - 2018/10/26

Y1 - 2018/10/26

N2 - High frequency oscillations (HFOs) > 80 Hz are a promising biomarker of epileptic tissue. Recent evidence has shown that spontaneous HFOs can be recorded from the scalp, but detection of these electrographic events remains a challenge. Here, we modified a simple automatic detector, used originally for intracranial EEG (iEEG) recordings, to detect ripples and fast ripples in scalp EEG. We analyzed scalp EEG recordings of seven subjects and validated our detector and artifact rejection algorithm via visual review. Of the candidate events marked by the detector, 40% and 60% were confirmed to be ripples and fast ripples, respectively, by human visual review, making this algorithm suitable for supervised detection. Detected HFOs occurred at a rate of <1/min in most channels, and the average duration was 47 and 24 ms for ripples and fast ripples, respectively. The simplicity of the algorithm, with only a single parameter, enables the consistent application of automatic detection across recording modalities, and it could therefore be a tool for the assessment and localization of epileptic activity.

AB - High frequency oscillations (HFOs) > 80 Hz are a promising biomarker of epileptic tissue. Recent evidence has shown that spontaneous HFOs can be recorded from the scalp, but detection of these electrographic events remains a challenge. Here, we modified a simple automatic detector, used originally for intracranial EEG (iEEG) recordings, to detect ripples and fast ripples in scalp EEG. We analyzed scalp EEG recordings of seven subjects and validated our detector and artifact rejection algorithm via visual review. Of the candidate events marked by the detector, 40% and 60% were confirmed to be ripples and fast ripples, respectively, by human visual review, making this algorithm suitable for supervised detection. Detected HFOs occurred at a rate of <1/min in most channels, and the average duration was 47 and 24 ms for ripples and fast ripples, respectively. The simplicity of the algorithm, with only a single parameter, enables the consistent application of automatic detection across recording modalities, and it could therefore be a tool for the assessment and localization of epileptic activity.

UR - http://www.scopus.com/inward/record.url?scp=85056566216&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056566216&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2018.8513033

DO - 10.1109/EMBC.2018.8513033

M3 - Conference contribution

C2 - 30441054

AN - SCOPUS:85056566216

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 3116

EP - 3119

BT - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018

Y2 - 18 July 2018 through 21 July 2018

ER -

Charupanit K, Nunez MD, Bernardo D, Bebin M, Krueger DA, Northrup H et al. Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. 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. 3116-3119. 8513033. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2018.8513033

Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram

Abstract

Publication series

Other

Funding

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this