NDLI: Early detection of human epileptic seizures based on intracortical local field potentials

Content Provider	IEEE Xplore Digital Library
Author	Park, Y.S. Hochberg, L.R. Eskandar, E.N. Cash, S.S. Truccolo, W.
Copyright Year	2013
Description	Author affiliation: Dept. of Neurosci., Brown Univ., Providence, RI, USA (Truccolo, W.) \|\| Brown Inst. for Brain Sci., Brown Univ., Providence, RI, USA (Park, Y.S.) \|\| Dept. of Veterans Affairs, Center for Neurorestoration & Neurotechnology, Providence, RI, USA (Hochberg, L.R.) \|\| Dept. of Neurosurg., Massachusetts Gen. Hosp., Boston, MA, USA (Eskandar, E.N.) \|\| Dept. of Neurology, Massachusetts Gen. Hosp., Boston, MA, USA (Cash, S.S.)
Abstract	The unpredictability of re-occurring seizures dramatically impacts the quality of life and autonomy of people with epilepsy. Reliable early seizure detection could open new therapeutic possibilities and thus substantially improve quality of life and autonomy. Though many seizure detection studies have shown the potential of scalp electroencephalogram (EEG) and intracranial EEG (iEEG) signals, reliable early detection of human seizures remains elusive in practice. Here, we examined the use of intracortical local field potentials (LFPs) recorded from $4×4-mm^{2}$ 96-microelectrode arrays (MEA) for early detection of human epileptic seizures. We adopted a framework consisting of (1) sampling of intracortical LFPs; (2) denoising of LFPs with the Kalman filter; (3) spectral power estimation in specific frequency bands using 1-sec moving time windows; (4) extraction of statistical features, such as the mean, variance, and Fano factor (calculated across channels) of the power in each frequency band; and (5) cost-sensitive support vector machine (SVM) classification of ictal and interictal samples. We tested the framework in one-participant dataset, including 4 seizures and corresponding interictal recordings preceding each seizure. The participant was a 52-year-old woman suffering from complex partial seizures. LFPs were recorded from an MEA implanted in the participant's left middle temporal gyrus. In this participant, spectral power in 0.3-10 Hz, 20-55 Hz, and 125-250 Hz changed significantly between ictal and interictal epochs. The examined seizure detection framework provided an event-wise sensitivity of 100% (4/4) and only one 20-sec-long false positive event in interictal recordings (likely an undetected subclinical event under further visual inspection), and a detection latency of 4.35 ± 2.21 sec (mean ± std) with respect to iEEG-identified seizure onsets. These preliminary results indicate that intracortical MEA recordings may provide key signals to quickly and reliably detect human seizures.
Starting Page	323
Ending Page	326
File Size	1228241
Page Count	4
File Format	PDF
ISBN	9781467319690
ISSN	19483554
DOI	10.1109/NER.2013.6695937
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Noise reduction Epilepsy Feature extraction Educational institutions Electroencephalography Reliability
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	ndl-support@iitkgp.ac.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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