Multi-Biosignal Analysis for Epileptic Seizure Monitoring

Diana Cogan, Javad Birjandtalab, Mehrdad Nourani, Jay Harvey, Venkatesh Nagaraddi

Research output: Contribution to journalArticle

42 Scopus citations

Abstract

Persons who suffer from intractable seizures are safer if attended when seizures strike. Consequently, there is a need for wearable devices capable of detecting both convulsive and nonconvulsive seizures in everyday life. We have developed a three-stage seizure detection methodology based on 339 h of data (26 seizures) collected from 10 patients in an epilepsy monitoring unit. Our intent is to develop a wearable system that will detect seizures, alert a caregiver and record the time of seizure in an electronic diary for the patient's physician. Stage I looks for concurrent activity in heart rate, arterial oxygenation and electrodermal activity, all of which can be monitored by a wrist-worn device and which in combination produce a very low false positive rate. Stage II looks for a specific pattern created by these three biosignals. For the patients whose seizures cannot be detected by Stage II, Stage III detects seizures using limited-channel electroencephalogram (EEG) monitoring with at most three electrodes. Out of 10 patients, Stage I recognized all 11 seizures from seven patients, Stage II detected all 10 seizures from six patients and Stage III detected all of the seizures of two out of the three patients it analyzed.

Original languageEnglish (US)
Article number1650031
JournalInternational Journal of Neural Systems
Volume27
Issue number1
DOIs
StatePublished - Feb 1 2017

Keywords

  • Arterial oxygenation
  • electrodermal activity
  • heart rate
  • limited-channel EEG monitoring
  • seizure detection
  • wrist-worn device

ASJC Scopus subject areas

  • Computer Networks and Communications

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