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Tonic-clonic seizur...
Tonic-clonic seizure detection using accelerometry-based wearable sensors: A prospective, video-EEG controlled study
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- Johansson, Dongni, 1988 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience,University of Gothenburg, Sweden; Sahlgrenska University Hospital, Sweden
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- Ohlsson, Fredrik (author)
- RISE,Acreo
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- Krysl, David (author)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience,University of Gothenburg, Sweden; Sahlgrenska University Hospital, Sweden
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- Rydenhag, Bertil, 1954 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience,University of Gothenburg, Sweden; Sahlgrenska University Hospital, Sweden
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- Czarnecki, Madeleine (author)
- RISE,Acreo
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- Gustafsson, Niclas (author)
- RISE,Acreo
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- Wipenmyr, Jan (author)
- RISE,Acreo
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- McKelvey, Tomas, 1966 (author)
- Chalmers tekniska högskola,Chalmers University of Technology,Sahlgrenska University Hospital, Sweden
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- Malmgren, Kristina, 1952 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience,University of Gothenburg, Sweden; Sahlgrenska University Hospital, Sweden
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(creator_code:org_t)
- Elsevier BV, 2019
- 2019
- English.
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In: Seizure : the journal of the British Epilepsy Association. - : Elsevier BV. - 1059-1311 .- 1532-2688. ; 65, s. 48-54
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http://www.seizure-j...
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https://doi.org/10.1...
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Abstract
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- Purpose: The aim of this prospective, video-electroencephalography (video-EEG) controlled study was to evaluate the performance of an accelerometry-based wearable system to detect tonic-clonic seizures (TCSs) and to investigate the accuracy of different seizure detection algorithms using separate training and test data sets. Methods: Seventy-five epilepsy surgery candidates undergoing video-EEG monitoring were included. The patients wore one three-axis accelerometer on each wrist during video-EEG. The accelerometer data was band-pass filtered and reduced using a movement threshold and mapped to a time-frequency feature space representation. Algorithms based on standard binary classifiers combined with a TCS specific event detection layer were developed and trained using the training set. Their performance was evaluated in terms of sensitivity and false positive (FP) rate using the test set. Results: Thirty-seven available TCSs in 11 patients were recorded and the data was divided into disjoint training (27 TCSs, three patients) and test (10 TCSs, eight patients) data sets. The classification algorithms evaluated were K-nearest-neighbors (KNN), random forest (RF) and a linear kernel support vector machine (SVM). For the TCSs detection performance of the three algorithms in the test set, the highest sensitivity was obtained for KNN (100% sensitivity, 0.05 FP/h) and the lowest FP rate was obtained for RF (90% sensitivity, 0.01 FP/h). Conclusions: The low FP rate enhances the clinical utility of the detection system for long-term reliable seizure monitoring. It also allows a possible implementation of an automated TCS detection in free-living environment, which could contribute to ascertain seizure frequency and thereby better seizure management.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk laboratorie- och mätteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Laboratory and Measurements Technologies (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinsk bioteknologi -- Biomedicinsk laboratorievetenskap/teknologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Medical Biotechnology -- Biomedical Laboratory Science/Technology (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Neurologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Neurology (hsv//eng)
Keyword
- Seizure detection devices
- Machine learning
- Wrist-worn sensors
- Tonic-clonic seizure
- Epilepsy
- Epilepsy
- Machine learning
- Seizure detection devices
- Tonic-clonic seizure
- Wrist-worn sensors
Publication and Content Type
- art (subject category)
- ref (subject category)
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Johansson, Dongn ...
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Ohlsson, Fredrik
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Krysl, David
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Rydenhag, Bertil ...
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Czarnecki, Madel ...
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Gustafsson, Nicl ...
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Wipenmyr, Jan
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McKelvey, Tomas, ...
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Malmgren, Kristi ...
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Seizure : the jo ...
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Chalmers University of Technology
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University of Gothenburg
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RISE