Difference between revisions of "Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database"
(Created page with "''Velez M, Fisher RS, Bartlett V, Le S (2016) Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure. 2016 Jul;39:13-18.''...") |
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| − | + | Velez M, Fisher RS, Bartlett V, Le S (2016) Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure. 2016 Jul;39:13-18. | |
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| − | == | + | https://ac.els-cdn.com/S1059131116300255/1-s2.0-S1059131116300255-main.pdf?_tid=80be6336-8697-4461-8efa-442c933f54cf&acdnat=1530209986_aea0236fbe84976d89d44b3d8f39c794 |
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| + | PURPOSE: Clinical management of epilepsy and current epilepsy therapy trials rely on paper or electronic diaries often with inaccurate self-reported seizure frequency as the primary outcome. This is the first study addressing the feasibility of detecting and recording generalized tonic-clonic seizures (GTCS) through a biosensor linked to an online seizure database. METHOD: A prospective trial was conducted with video-EEG (vEEG) in an epilepsy monitoring unit. Patients wore a wristwatch accelerometer that detected shaking and transmitted events via Bluetooth® to a bedside electronic tablet and then via Wi-Fi to an online portal. The watch recorded the date, time, audio, duration, frequency and amplitude of events. Events logged by the watch and recorded in a bedside paper diary were measured against vEEG, the "gold standard." RESULTS: Thirty patients were enrolled and 62 seizures were recorded on vEEG: 31 convulsive and 31 non-convulsive. Twelve patients had a total of 31 convulsive seizures, and of those, 10 patients had 13 GTCS. The watch captured 12/13 (92.3%) GTCS. Watch audio recordings were consistent with seizures in 11/12 (91.6%). Data were successfully transferred to the bedside tablet in 11/12 (91.6%), and to the online database in 10/12 (83.3%) GTCS. The watch recorded 81 false positives, of which 42/81 (51%) were cancelled by the patients. Patients and caregivers verbally reported 15/62 seizures (24.2% sensitivity) but no seizures were recorded on paper logs. CONCLUSION: Automatic detection and recording of GTCS to an online database is feasible and may be more informative than seizure logging in a paper diary. | ||
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| + | Epilepsy, Automatic detection, Online interface, Seizure diary | ||
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Latest revision as of 14:11, 17 June 2019
Velez M, Fisher RS, Bartlett V, Le S (2016) Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database. Seizure. 2016 Jul;39:13-18.
Abstract: PURPOSE: Clinical management of epilepsy and current epilepsy therapy trials rely on paper or electronic diaries often with inaccurate self-reported seizure frequency as the primary outcome. This is the first study addressing the feasibility of detecting and recording generalized tonic-clonic seizures (GTCS) through a biosensor linked to an online seizure database. METHOD: A prospective trial was conducted with video-EEG (vEEG) in an epilepsy monitoring unit. Patients wore a wristwatch accelerometer that detected shaking and transmitted events via Bluetooth® to a bedside electronic tablet and then via Wi-Fi to an online portal. The watch recorded the date, time, audio, duration, frequency and amplitude of events. Events logged by the watch and recorded in a bedside paper diary were measured against vEEG, the "gold standard." RESULTS: Thirty patients were enrolled and 62 seizures were recorded on vEEG: 31 convulsive and 31 non-convulsive. Twelve patients had a total of 31 convulsive seizures, and of those, 10 patients had 13 GTCS. The watch captured 12/13 (92.3%) GTCS. Watch audio recordings were consistent with seizures in 11/12 (91.6%). Data were successfully transferred to the bedside tablet in 11/12 (91.6%), and to the online database in 10/12 (83.3%) GTCS. The watch recorded 81 false positives, of which 42/81 (51%) were cancelled by the patients. Patients and caregivers verbally reported 15/62 seizures (24.2% sensitivity) but no seizures were recorded on paper logs. CONCLUSION: Automatic detection and recording of GTCS to an online database is feasible and may be more informative than seizure logging in a paper diary.
Keywords: Epilepsy, Automatic detection, Online interface, Seizure diary