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Automated real-time detection of tonic-clonic seizures using a wearable EMG device

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DOI

  • Sándor Beniczky
  • Isa Conradsen, From the Department of Clinical Neurophysiology (S.B.), Danish Epilepsy Centre Dianalund and Aarhus University Hospital; FORCE Technology (I.C.), Hørsholm, Denmark; Department of Clinical Neurophysiology (O.H.), National Centre for Epilepsy, Oslo University Hospital, Norway; Department of Clinical Neurophysiology (M.F.), Copenhagen University Hospital Rigshospitalet; Department of Neurology (P.W.), Danish Epilepsy Centre, Dianalund, Denmark; and Postgraduate Programme in Clinical Medicine (P.W.), Federal University of Santa Catarina, Florianópolis, Brazil.
  • ,
  • Oliver Henning, From the Department of Clinical Neurophysiology (S.B.), Danish Epilepsy Centre Dianalund and Aarhus University Hospital; FORCE Technology (I.C.), Hørsholm, Denmark; Department of Clinical Neurophysiology (O.H.), National Centre for Epilepsy, Oslo University Hospital, Norway; Department of Clinical Neurophysiology (M.F.), Copenhagen University Hospital Rigshospitalet; Department of Neurology (P.W.), Danish Epilepsy Centre, Dianalund, Denmark; and Postgraduate Programme in Clinical Medicine (P.W.), Federal University of Santa Catarina, Florianópolis, Brazil.
  • ,
  • Martin Fabricius, From the Department of Clinical Neurophysiology (S.B.), Danish Epilepsy Centre Dianalund and Aarhus University Hospital; FORCE Technology (I.C.), Hørsholm, Denmark; Department of Clinical Neurophysiology (O.H.), National Centre for Epilepsy, Oslo University Hospital, Norway; Department of Clinical Neurophysiology (M.F.), Copenhagen University Hospital Rigshospitalet; Department of Neurology (P.W.), Danish Epilepsy Centre, Dianalund, Denmark; and Postgraduate Programme in Clinical Medicine (P.W.), Federal University of Santa Catarina, Florianópolis, Brazil.
  • ,
  • Peter Wolf, From the Department of Clinical Neurophysiology (S.B.), Danish Epilepsy Centre Dianalund and Aarhus University Hospital; FORCE Technology (I.C.), Hørsholm, Denmark; Department of Clinical Neurophysiology (O.H.), National Centre for Epilepsy, Oslo University Hospital, Norway; Department of Clinical Neurophysiology (M.F.), Copenhagen University Hospital Rigshospitalet; Department of Neurology (P.W.), Danish Epilepsy Centre, Dianalund, Denmark; and Postgraduate Programme in Clinical Medicine (P.W.), Federal University of Santa Catarina, Florianópolis, Brazil.

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).

Original languageEnglish
JournalNeurology
Volume90
Issue5
Pages (from-to)e428-e434
Number of pages8
ISSN0028-3878
DOIs
Publication statusPublished - 30 Jan 2018

    Research areas

  • BIOMARKERS, EPILEPSY, NONEPILEPTIC CONVULSIVE SEIZURES, PATIENT, PREVENTION, QUANTITATIVE-ANALYSIS, SAFETY, SUDDEN UNEXPECTED DEATH, SURFACE ELECTROMYOGRAPHY, WRIST ACCELEROMETER

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