Purpose: An approach to the problem of seizure prediction aimed to provide a computationally effective method for real-time application with standard scalp EEG recordings is presented. Methods: One control record performed during steady interictal interval and 10 preseizure records lasting 15-20 minutes with standard scalp EEG 32 channels from 3 subjects suffering from pharmacoresistant medial temporal lobe epilepsy have been used. A disharmony index based on multiple abrupt changes of EEG spectral features is introduced to characterise the pre-ictal phase. The amount of changes into the time unit is considered as a predictor. A new computationally effective on-line algorithm to solve the basic problem of single change detection is proposed...
A seizure prediction method is proposed by extracting global features using phase correlation betwee...
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. ...
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. ...
The present study introduces the method for solving the problem on early prediction of epilepsy seiz...
Human epilepsy is a disease characterized by sudden, unprovoked, recurrent seizures accompanied by p...
Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, ...
Current epileptic seizure prediction algorithms are generally based on the knowledge of seizure oc...
Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's populati...
Epileptic seizures of mesial temporal origin are preceded by changes in signal properties detectable...
Epilepsy is the second most common neurological disorder, affecting 0.6–0.8 % of the world’s populat...
Epileptic seizures occur due to disorder in brain functionality which can affect patient’s health. P...
The cause of seizures in epileptic patients is still poorly understood. Ongoing debat...
As a chronic neurological disorder, epilepsy is associated with recurrent, unprovoked epileptic seiz...
During prolonged EEG monitoring of epileptic patients, the continuous recording may be marked where ...
Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming majority of peopl...
A seizure prediction method is proposed by extracting global features using phase correlation betwee...
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. ...
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. ...
The present study introduces the method for solving the problem on early prediction of epilepsy seiz...
Human epilepsy is a disease characterized by sudden, unprovoked, recurrent seizures accompanied by p...
Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, ...
Current epileptic seizure prediction algorithms are generally based on the knowledge of seizure oc...
Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's populati...
Epileptic seizures of mesial temporal origin are preceded by changes in signal properties detectable...
Epilepsy is the second most common neurological disorder, affecting 0.6–0.8 % of the world’s populat...
Epileptic seizures occur due to disorder in brain functionality which can affect patient’s health. P...
The cause of seizures in epileptic patients is still poorly understood. Ongoing debat...
As a chronic neurological disorder, epilepsy is associated with recurrent, unprovoked epileptic seiz...
During prolonged EEG monitoring of epileptic patients, the continuous recording may be marked where ...
Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming majority of peopl...
A seizure prediction method is proposed by extracting global features using phase correlation betwee...
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. ...
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. ...