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Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment
Electrocardiography has added value to automatically detect seizures in temporal lobe epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure detection system at home. To address this need, the performance of two wearable devices, based on electrocardiography (ECG) a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676949/ https://www.ncbi.nlm.nih.gov/pubmed/29027928 http://dx.doi.org/10.3390/s17102338 |
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author | Vandecasteele, Kaat De Cooman, Thomas Gu, Ying Cleeren, Evy Claes, Kasper Van Paesschen, Wim Van Huffel, Sabine Hunyadi, Borbála |
author_facet | Vandecasteele, Kaat De Cooman, Thomas Gu, Ying Cleeren, Evy Claes, Kasper Van Paesschen, Wim Van Huffel, Sabine Hunyadi, Borbála |
author_sort | Vandecasteele, Kaat |
collection | PubMed |
description | Electrocardiography has added value to automatically detect seizures in temporal lobe epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure detection system at home. To address this need, the performance of two wearable devices, based on electrocardiography (ECG) and photoplethysmography (PPG), are compared with hospital ECG using an existing seizure detection algorithm. This algorithm classifies the seizures on the basis of heart rate features, extracted from the heart rate increase. The algorithm was applied to recordings of 11 patients in a hospital setting with 701 h capturing 47 (fronto-)temporal lobe seizures. The sensitivities of the hospital system, the wearable ECG device and the wearable PPG device were respectively 57%, 70% and 32%, with corresponding false alarms per hour of 1.92, 2.11 and 1.80. Whereas seizure detection performance using the wrist-worn PPG device was considerably lower, the performance using the wearable ECG is proven to be similar to that of the hospital ECG. |
format | Online Article Text |
id | pubmed-5676949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-56769492017-11-17 Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment Vandecasteele, Kaat De Cooman, Thomas Gu, Ying Cleeren, Evy Claes, Kasper Van Paesschen, Wim Van Huffel, Sabine Hunyadi, Borbála Sensors (Basel) Article Electrocardiography has added value to automatically detect seizures in temporal lobe epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure detection system at home. To address this need, the performance of two wearable devices, based on electrocardiography (ECG) and photoplethysmography (PPG), are compared with hospital ECG using an existing seizure detection algorithm. This algorithm classifies the seizures on the basis of heart rate features, extracted from the heart rate increase. The algorithm was applied to recordings of 11 patients in a hospital setting with 701 h capturing 47 (fronto-)temporal lobe seizures. The sensitivities of the hospital system, the wearable ECG device and the wearable PPG device were respectively 57%, 70% and 32%, with corresponding false alarms per hour of 1.92, 2.11 and 1.80. Whereas seizure detection performance using the wrist-worn PPG device was considerably lower, the performance using the wearable ECG is proven to be similar to that of the hospital ECG. MDPI 2017-10-13 /pmc/articles/PMC5676949/ /pubmed/29027928 http://dx.doi.org/10.3390/s17102338 Text en © 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/). |
spellingShingle | Article Vandecasteele, Kaat De Cooman, Thomas Gu, Ying Cleeren, Evy Claes, Kasper Van Paesschen, Wim Van Huffel, Sabine Hunyadi, Borbála Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment |
title | Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment |
title_full | Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment |
title_fullStr | Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment |
title_full_unstemmed | Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment |
title_short | Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment |
title_sort | automated epileptic seizure detection based on wearable ecg and ppg in a hospital environment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676949/ https://www.ncbi.nlm.nih.gov/pubmed/29027928 http://dx.doi.org/10.3390/s17102338 |
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