According to WHO, epilepsy is the fourth most common neurological disease globally. CDC statistics show that 1 in 26 individuals in the U.S. will be diagnosed with epilepsy over a lifetime. While there are 36 epilepsy drugs available on the market, 1 in 3 adult patients and 20 to 25% of child patients have drug-resistant epilepsy.
When having a seizure, patients with epilepsy (PWE) may suffer from temporary loss of consciousness, sensation, and motor control. The notorious nature of generalized tonic-clonic seizure (GTCS) has been known for a long time, especially the correlation between high-frequency GTCS and sudden unexpected death in epilepsy (SUDEP). Based on patient surveys, the seemingly random timing of seizures is one of the worst aspects of epilepsy. Unexpected episodes are disruptive, significantly hindering their daily routines. Sometimes, there may be severe secondary damage, such as having an attack while driving or sporting.
We study sleep-wake cycles, circadian and multi-day rhythms in physiological signals, the risk of generalized tonic-clonic seizure (GTCS), and the potential modulation between them. We envision these rhythms captured by wearable devices to empower personalized and unobtrusive GTCS forecasting technologies. Specifically, we focus on sleep-wake behaviors, electrodermal activity (EDA), and GTCS events detected by wrist-worn smart wristbands in ambulatory settings. Data from over 1,000 to 2,000 patients diagnosed with GTCS are analyzed, depending on the availability in specific analyses.