Researchers from Ciklum, Anton Popov and Ivan Kotiuchyi, in partnership with the University of Palermo have published a research paper, “Time, frequency and information domain analysis of short-term heart rate variability during pre- and post-ictal periods in epileptic children”.
Epilepsy is a neurological disorder provoked by unusual nerve cell activity in the brain, resulting in temporary motor, sensory, or mental dysfunction. Around 50 million people worldwide are diagnosed with epilepsy, making it the fourth most common neurological disease after migraines, strokes, and Alzheimer’s.
There are different manifestations of epileptic seizures such as convulsions, trembling, jerking, stiffening, loss of consciousness or a sensation of déjà vu. These seizures are often focal – meaning they generate within in one hemisphere but then rapidly become generalised and involve bilateral networks in the brain, causing a loss of consciousness.
Effective epilepsy treatments are still not applicable to all forms and causes of epilepsy. Antiseizure medications are not suitable for everyone as there are side effects, surgery sometimes is not an option as well. Before a medicine can cure all types of epilepsy as easy as antibiotics cure infections, the important thing to do is finding a way to predict uncontrolled or intractable seizures to minimize the danger for patients.Anton Popov, AI/Deep Learning Technical Lead
With a strong interest in health tech, Ciklum’s research engineers partnered with University of Palermo researchers to explore solutions in a paper. As a sufficient amount of studies have been done on heart rate viability (HRV) during seizure activity, the decision was made to examine HRV during seizure-free states, so-called pre-ictal and post-ictal activity. The HVR of 42 children diagnosed with focal or generalised epilepsy were observed 10, 300, 600 and 1800 seconds before and after repeated seizure episodes and analyzed.
The researchers found out that the early post-ictal phase is characterized by significant tachycardia, depressed HRV, shift of the sympatho-vagal balance and decreased HRV complexity, with overall results more evident in focal than in generalized epilepsy. The findings may have clinical relevance by reducing thresholds for life-threatening arrhythmias and could be a biomarker of risk for sudden unexpected death in epilepsy.
You can read the full article here.