Method for Monitoring Patterns in the Behavior of Brain Activity Prior to an Episode of Epilepsy, Applied to Young People in Times of the Covid-19 Pandemic, using Low-Cost BCI Devices

Abstract

Epilepsy is one of the characteristic diseases of brain activity. People with this disease live with the symptoms and try to control the events to mitigate the effects that they may cause, such as a fall, blow, or any other consequence. In these times of pandemic caused by COVID-19, many of the people who have this disease present many events in a row, which can be caused by many factors, such as being at home most of the day, without being able to go out to get distracted. In this research work, a practical method is presented to monitor and predict an epilepsy event, based on the measurement of stress and meditation levels by using low-cost devices. For the evaluation of the method, measurements were made on a patient who constantly presents epilepsy events. The evaluation was carried out when she took her classes online, where the students present greater pressure. The method uses smartwatches to evaluate the stress level and BCI devices to measure the level of meditation. The results found in the data analysis present grouped values for the positive and negative cases of happening of epilepsy events. In the evaluation, possible threshold values that can be used to classify epilepsy events were determined. The determined threshold value can be used independently if only one device can be counted on. The reference threshold value is determined between values of 41 and 79, on a scale of 1 to 100. It is concluded that the device that can be counted on in the market at a low cost is the smartwatch that measures the stress level, compared to the best-known brain signal analysis device. As for the BCI device, the presented method is easy to implement; it can be easily used by the patients themselves or their relatives.