Researchers at the Indian Institute of Science (IISc), Bengaluru in collaboration with the All India Institute of Medical Science (AIIMS), Rishikesh, have developed an algorithm that can help decode brain scans to identify the occurrence and type of epilepsy. The announcement regarding the collaboration was made Wednesday. “Epilepsy is a neurological disease where the brain emits sudden bursts of electrical signals in a short amount of time, resulting in seizures, fits, and in extreme cases, death. Based on the point of origin of the brain’s erratic signals, epilepsy is classified as either focal or generalised epilepsy. 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 generalised epilepsy,” the IISc said in a statement. Hardik J Pandya, assistant professor at the Department of Electronic Systems Engineering (DESE), IISc, and the corresponding author of the study, said: “To identify whether a patient is epileptic, neurophysiologists need to manually inspect EEGs (electroencephalograms), which can capture such erratic signals. Visual inspection of EEG can become tiring after prolonged periods, and may occasionally lead to errors. The research aims to differentiate EEGs 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.” In its study, the team reported 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 (a living individual about whom an investigation is carried) could have epilepsy or not – based on these patterns in their respective analyses – with a high degree of accuracy,” the IISc said. Explaining further, the researchers in a statement said: “An epileptic subject shows a different set of patterns compared to a healthy individual. The researchers developed an algorithm to calculate the total number of sharp waves – the Cumulative Sharp Count – and use this as a parameter to detect if the subject is epileptic or not (a higher value indicates a greater chance that the subject is epileptic). The team then ran their algorithm on a new set of EEG data from subjects for whom the classification (whether they had epilepsy, and if so, what type of epilepsy they had) was already known to the doctors. This blind validation study successfully classified the subjects accurately in nearly 91% of the cases.” “We hope to refine this further by testing on more data to consider more variabilities of human EEGs until we reach the point where this becomes completely translational and robust,” said Rathin K Joshi, a PhD student in DESE. Currently, a patent has been filed for the work and the algorithm is being tested for its reliability by physicians at AIIMS Rishikesh.
