Electrical and Electronic Engineering - Research Publications

Permanent URI for this collection

http://hdl.handle.net/11343/362

Filters

2016 1
Reset filters

Settings
Statistics
Citations
Author: GUBBI LAKSHMINARASIMHA, JAYAVARDHANA × Author: Palaniswami, Marimuthu × Author: Yan, Bernard × End date: 2019 × Start date: 2016 × Type: Journal Article ×

Search Results

Now showing 1 - 1 of 1
  • Item
    Thumbnail Image
    Automatic Detection and Classification of Convulsive Psychogenic Nonepileptic Seizures Using a Wearable Device
    Gubbi, J ; Kusmakar, S ; Rao, AS ; Yan, B ; O'Brien, T ; Palaniswami, M (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2016-07)
    Epilepsy is one of the most common neurological disorders and patients suffer from unprovoked seizures. In contrast, psychogenic nonepileptic seizures (PNES) are another class of seizures that are involuntary events not caused by abnormal electrical discharges but are a manifestation of psychological distress. The similarity of these two types of seizures poses diagnostic challenges that often leads in delayed diagnosis of PNES. Further, the diagnosis of PNES involves high-cost hospital admission and monitoring using video-electroencephalogram machines. A wearable device that can monitor the patient in natural setting is a desired solution for diagnosis of convulsive PNES. A wearable device with an accelerometer sensor is proposed as a new solution in the detection and diagnosis of PNES. The seizure detection algorithm and PNES classification algorithm are developed. The developed algorithms are tested on data collected from convulsive epileptic patients. A very high seizure detection rate is achieved with 100% sensitivity and few false alarms. A leave-one-out error of 6.67% is achieved in PNES classification, demonstrating the usefulness of wearable device in the diagnosis of PNES.