Model
Digital Document
Publisher
Florida Atlantic University
Description
This paper evaluates the effectiveness of a wearable device, developed by the
author, to detect different types of epileptic seizures and monitor epileptic patients. The
device uses GSR, Pulse, EMG, body temperature and 3-axis accelerometer sensors to
detect epilepsy. The device first learns the signal patterns of the epileptic patient in ideal
condition. The signal pattern generated during the epileptic seizure, which are distinct from
other signal patterns, are detected and analyzed by the algorithms developed by the author.
Based on an analysis, the device successfully detected different types of epileptic seizures.
The author conducted an experiment on himself to determine the effectiveness of the device
and the algorithms. Based on the simulation results, the algorithms are 100 percent accurate
in detecting different types of epileptic seizures.
author, to detect different types of epileptic seizures and monitor epileptic patients. The
device uses GSR, Pulse, EMG, body temperature and 3-axis accelerometer sensors to
detect epilepsy. The device first learns the signal patterns of the epileptic patient in ideal
condition. The signal pattern generated during the epileptic seizure, which are distinct from
other signal patterns, are detected and analyzed by the algorithms developed by the author.
Based on an analysis, the device successfully detected different types of epileptic seizures.
The author conducted an experiment on himself to determine the effectiveness of the device
and the algorithms. Based on the simulation results, the algorithms are 100 percent accurate
in detecting different types of epileptic seizures.
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