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IIsc-aiims Algorithm To Help Detect Seizures, Health News, ET HealthWorld

Bengaluru: Researchers at IIScin collaboration with AIIMS-Rishikesh, have developed an algorithm that can help decode brain scans to identify the occurrence and type of Epilepsy, Epilepsy is a neurological disease where the brain emits sudden bursts of electrical signals in a short amount of time, resulting in seizuresfits, and in extreme cases, death.

Based on the point of origin of the brain’s erratic signals, epilepsy is classified as either focal or generalized epilepsy, IISc said, adding that focal epilepsy occurs when the erratic signals are confined to a specific region in the brain. If the signals are at random locations, then it is termed as generalized epilepsy. To identify whether a patient is epileptic, neurophysiologists need to manually inspect electroencephalograms (EEGs), which can capture such erratic signals. Visual EEG inspection can become tiring after prolonged periods, and may occasionally lead to errors, says Hardik J Pandya, assistant professor at the department of electronic systems engineering (DESE) and the corresponding author of the study published in Biomedical Signal Processing and Control.

“The research aims to differentiate EEG of normal subjects from epileptic EEGs. Additionally, the developed algorithm attempts to identify the types of seizures. Our work is to help the neurologists make an efficient and quick automated screening and diagnosis,” Pandya adds.

In their study, the team reports a novel algorithm that can sift through EEG data and identify signatures of epilepsy from the electrical signal patterns. After initial training, the algorithm was able to detect whether a human subject could have epilepsy or not — based on these patterns in their respective analyses — with a high degree of accuracy, the researchers say.

To develop and train the algorithm, the researchers first examined EEG data from 88 human subjects acquired at AIIMS Rishikesh, Each subject underwent a 45-minute EEG test, divided into two parts: An initial 10-minute test when the subject was awake, which included photic stimulation and hyperventilation, followed by a 35-minute sleep period when the subject was asked to sleep.

“Next, the team analyzed this data and classified different wave patterns into sharp signals, spikes, and slow waves. Spikes are patterns where a signal rises and falls within a very short duration of time (around 70 milliseconds), while sharps are those with rises and falls spread over a slightly longer duration (around 250 milliseconds), and slow waves have a much longer duration (around 400 milliseconds),” IISc said.

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