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      Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy

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          Abstract

          A wearable electroencephalogram (EEG) device for continuous monitoring of patients suffering from epilepsy would provide valuable information for the management of the disease. Currently no EEG setup is small and unobtrusive enough to be used in daily life. Recording behind the ear could prove to be a solution to a wearable EEG setup. This article examines the feasibility of recording epileptic EEG from behind the ear. It is achieved by comparison with scalp EEG recordings. Traditional scalp EEG and behind-the-ear EEG were simultaneously acquired from 12 patients with temporal, parietal, or occipital lobe epilepsy. Behind-the-ear EEG consisted of cross-head channels and unilateral channels. The analysis on Electrooculography (EOG) artifacts resulting from eye blinking showed that EOG artifacts were absent on cross-head channels and had significantly small amplitudes on unilateral channels. Temporal waveform and frequency content during seizures from behind-the-ear EEG visually resembled that from scalp EEG. Further, coherence analysis confirmed that behind-the-ear EEG acquired meaningful epileptic discharges similarly to scalp EEG. Moreover, automatic seizure detection based on support vector machine (SVM) showed that comparable seizure detection performance can be achieved using these two recordings. With scalp EEG, detection had a median sensitivity of 100% and a false detection rate of 1.14 per hour, while, with behind-the-ear EEG, it had a median sensitivity of 94.5% and a false detection rate of 0.52 per hour. These findings demonstrate the feasibility of detecting seizures from EEG recordings behind the ear for patients with focal epilepsy.

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          Most cited references32

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          How about taking a low-cost, small, and wireless EEG for a walk?

          To build a low-cost, small, and wireless electroencephalogram (EEG) system suitable for field recordings, we merged consumer EEG hardware with an EEG electrode cap. Auditory oddball data were obtained while participants walked outdoors on university campus. Single-trial P300 classification with linear discriminant analysis revealed high classification accuracies for both indoor (77%) and outdoor (69%) recording conditions. We conclude that good quality, single-trial EEG data suitable for mobile brain-computer interfaces can be obtained with affordable hardware. Copyright © 2012 Society for Psychophysiological Research.
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            The epidemiology of epilepsy in Europe - a systematic review.

            Population-based epidemiological studies on epilepsy are available mainly from the UK and the Nordic, Baltic and western Mediterranean countries. No studies were identified from large areas of Europe, especially from the former eastern Europe (except the Baltic countries) and the eastern Mediterranean countries. Based on the prevalence of epilepsy in different studies and accounting for incomplete case identification the estimated number of children and adolescents in Europe with active epilepsy is 0.9 million (prevalence 4.5-5.0 per 1000), 1.9 million in ages 20-64 years (prevalence six per 1000) and 0.6 million in ages 65 years and older (prevalence seven per 1000). Approximately 20-30% of the epilepsy population have more than one seizure per month. Based on the age-specific incidence rates in European studies, the estimated number of new cases per year amongst European children and adolescents is 130,000 (incidence rate 70 per 100,000), 96,000 in adults 20-64 years (incidence rate 30 per 100,000) and 85,000 in the elderly 65 years and older (incidence 100 per 100,000). The proportion of both new and established cases with epilepsy in the young, adults and elderly in individual countries may differ substantially from total European distribution because of differences in age structure.
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              Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear

              This study presents first evidence that reliable EEG data can be recorded with a new cEEGrid electrode array, which consists of ten electrodes printed on flexible sheet and arranged in a c-shape to fit around the ear. Ten participants wore two cEEGrid systems for at least seven hours. Using a smartphone for stimulus delivery and signal acquisition, resting EEG and auditory oddball data were collected in the morning and in the afternoon six to seven hours apart. Analysis of resting EEG data confirmed well-known spectral differences between eyes open and eyes closed conditions. The ERP results confirmed the predicted condition effects with significantly larger P300 amplitudes for target compared to standard tones, and a high test-retest reliability of the P300 amplitude (r > = .74). Moreover, a linear classifier trained on data from the morning session revealed similar performance in classification accuracy for the morning and the afternoon sessions (both > 70%). These findings demonstrate the feasibility of concealed and comfortable brain activity acquisition over many hours.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                23 December 2017
                January 2018
                : 18
                : 1
                : 29
                Affiliations
                [1 ]Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven 3001, Belgium; sabine.vanhuffel@ 123456esat.kuleuven.be (S.V.H.); bori.hunyadi@ 123456esat.kuleuven.be (B.H.)
                [2 ]Imec, Leuven 3001, Belgium
                [3 ]Laboratory for Epilepsy Research, University Hospital Leuven, Leuven 3000, Belgium; evy.cleeren@ 123456uzleuven.be (E.C.); wim.vanpaesschen@ 123456uzleuven.be (W.V.P.)
                [4 ]Byteflies, Antwerp 2600, Belgium; jonathan.dan@ 123456byteflies.com
                [5 ]UCB, Brussels 1070, Belgium; kasper.claes@ 123456ucb.com
                Author notes
                [* ]Correspondence: ying.gu@ 123456kuleuven.be ; Tel.: +32-16-373-374
                Author information
                https://orcid.org/0000-0002-8535-1699
                https://orcid.org/0000-0001-5939-0996
                Article
                sensors-18-00029
                10.3390/s18010029
                5795884
                29295522
                a29e69bf-3c6a-4491-ad28-151cf4a5a54e
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 01 November 2017
                : 21 December 2017
                Categories
                Article

                Biomedical engineering
                seizure detection,epilepsy,eeg,eog,wearable sensor,svm
                Biomedical engineering
                seizure detection, epilepsy, eeg, eog, wearable sensor, svm

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