{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T15:49:55Z","timestamp":1782834595017,"version":"3.54.5"},"reference-count":34,"publisher":"World Scientific Pub Co Pte Lt","issue":"11","funder":[{"name":"KU Leuven Research Council","award":["C14\/16\/057"],"award-info":[{"award-number":["C14\/16\/057"]}]},{"name":"European Union's Horizon 2020","award":["802895"],"award-info":[{"award-number":["802895"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[2020,11]]},"abstract":"<jats:p> Advances in electroencephalography (EEG) equipment now allow monitoring of people with epilepsy in their daily-life environment. The large volumes of data that can be collected from long-term out-of-clinic monitoring require novel algorithms to process the recordings on board of the device to identify and log or transmit only relevant data epochs. Existing seizure-detection algorithms are generally designed for post-processing purposes, so that memory and computing power are rarely considered as constraints. We propose a novel multi-channel EEG signal processing method for automated absence seizure detection which is specifically designed to run on a microcontroller with minimal memory and processing power. It is based on a linear multi-channel filter that is precomputed offline in a data-driven fashion based on the spatial-temporal signature of the seizure and peak interference statistics. At run-time, the algorithm requires only standard linear filtering operations, which are cheap and efficient to compute, in particular on microcontrollers with a multiply-accumulate unit (MAC). For validation, a dataset of eight patients with juvenile absence epilepsy was collected. Patients were equipped with a 20-channel mobile EEG unit and discharged for a day-long recording. The algorithm achieves a median of 0.5 false detections per day at 95% sensitivity. We compare our algorithm with state-of-the-art absence seizure detection algorithms and conclude it performs on par with these at a much lower computational cost. <\/jats:p>","DOI":"10.1142\/s0129065720500355","type":"journal-article","created":{"date-parts":[[2020,8,18]],"date-time":"2020-08-18T15:49:47Z","timestamp":1597765787000},"page":"2050035","source":"Crossref","is-referenced-by-count":35,"title":["Computationally-Efficient Algorithm for Real-Time Absence Seizure Detection in Wearable Electroencephalography"],"prefix":"10.1142","volume":"30","author":[{"given":"Jonathan","family":"Dan","sequence":"first","affiliation":[{"name":"STADIUS \u2013 ESAT KU Leuven, Leuven, Belgium"},{"name":"Byteflies, Antwerp, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin","family":"Vandendriessche","sequence":"additional","affiliation":[{"name":"Byteflies, Antwerp, Belgium"},{"name":"ECSE \u2013 Case Western Reserve University, Cleveland, Ohio, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wim Van","family":"Paesschen","sequence":"additional","affiliation":[{"name":"Neurology \u2013 UZ Leuven, Leuven, Belgium"},{"name":"Department of Neurology \u2013 KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dorien","family":"Weckhuysen","sequence":"additional","affiliation":[{"name":"Neurology \u2013 Kempenhaeghe, Heeze, Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Bertrand","sequence":"additional","affiliation":[{"name":"STADIUS \u2013 ESAT KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"219","published-online":{"date-parts":[[2020,8,18]]},"reference":[{"issue":"4","key":"S0129065720500355BIB001","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/S1474-4422(18)30454-X","volume":"18","author":"Beghi E.","year":"2019","journal-title":"Lancet Neurol."},{"issue":"12","key":"S0129065720500355BIB002","doi-asserted-by":"crossref","first-page":"2625","DOI":"10.1007\/s10072-019-04022-y","volume":"40","author":"Cho Y. 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