Automated real-time detection of tonic-clonic seizures using a wearable EMG device. (30th January 2018)
- Record Type:
- Journal Article
- Title:
- Automated real-time detection of tonic-clonic seizures using a wearable EMG device. (30th January 2018)
- Main Title:
- Automated real-time detection of tonic-clonic seizures using a wearable EMG device
- Authors:
- Beniczky, Sándor
Conradsen, Isa
Henning, Oliver
Fabricius, Martin
Wolf, Peter - Abstract:
- Abstract : Objective: To determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device. Methods: We prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device. The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings by trained experts, who were blinded to data from the device. Reading the seizure logs from the device was done blinded to all other data. Results: The mean recording time per patient was 53.18 hours. Total recording time was 3735.5 hours, and device deficiency time was 193 hours (4.9% of the total time the device was turned on). No adverse events occurred. The sensitivity of the wearable device was 93.8% (30 out of 32 GTCS were detected). Median seizure detection latency was 9 seconds (range −4 to 48 seconds). False alarm rate was 0.67/d. Conclusions: The performance of the wearable EMG device fulfilled the requirements of patients: it detected GTCS with a sensitivity exceeding 90% and detection latency within 30 seconds. Classification of evidence: This study provides Class II evidence that for people with a history of GTCS, a wearable EMG device accurately detects GTCSAbstract : Objective: To determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device. Methods: We prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device. The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings by trained experts, who were blinded to data from the device. Reading the seizure logs from the device was done blinded to all other data. Results: The mean recording time per patient was 53.18 hours. Total recording time was 3735.5 hours, and device deficiency time was 193 hours (4.9% of the total time the device was turned on). No adverse events occurred. The sensitivity of the wearable device was 93.8% (30 out of 32 GTCS were detected). Median seizure detection latency was 9 seconds (range −4 to 48 seconds). False alarm rate was 0.67/d. Conclusions: The performance of the wearable EMG device fulfilled the requirements of patients: it detected GTCS with a sensitivity exceeding 90% and detection latency within 30 seconds. Classification of evidence: This study provides Class II evidence that for people with a history of GTCS, a wearable EMG device accurately detects GTCS (sensitivity 93.8%, false alarm rate 0.67/d). … (more)
- Is Part Of:
- Neurology. Volume 90:Number 5(2018)
- Journal:
- Neurology
- Issue:
- Volume 90:Number 5(2018)
- Issue Display:
- Volume 90, Issue 5 (2018)
- Year:
- 2018
- Volume:
- 90
- Issue:
- 5
- Issue Sort Value:
- 2018-0090-0005-0000
- Page Start:
- Page End:
- Publication Date:
- 2018-01-30
- Subjects:
- Neurology -- Periodicals
Neurology -- Periodicals
Neurologie -- Périodiques
616.8 - Journal URLs:
- http://www.mdconsult.com/public/search?search_type=journal&j_sort=pub_date&j_issn=0028-3878 ↗
http://www.mdconsult.com/about/journallist/192093418-5/about0nz0.html ↗
http://www.neurology.org ↗
http://journals.lww.com ↗ - DOI:
- 10.1212/WNL.0000000000004893 ↗
- Languages:
- English
- ISSNs:
- 0028-3878
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.500000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 8816.xml