Monitoring and alerting system for epilepsy patients - Yeo, Ryan Wee En (Nanyang Technological University, 2022)
In recent years, there has been a rapid emergence of innovative approaches to healthcare. Data are constantly collected by wearable devices such as smartwatches, opening new possibilities for continuous monitoring of parameters related to an individual’s health status. We can inform the relevant parties of their health conditions by utilising this information. This Monitoring and Alerting System for Epilepsy patients (MAASFEP) deploys a non invasive method that incorporates the Electromyograph (EMG) Sensor, Light Dependent Resistor (LDR), Temperature Sensor, Galvanic Skin Response (GSR) Sensor and the Pulse Sensor on the ESP32 microcontroller to perform seizure classification and display the classified results on Telegram to alert relevant parties. Additionally, MAASFEP provides a function that explains the steps to perform during a seizure and a log that stores the data of the patients’ seizure attacks, which the healthcare professionals can access through Telegram, allowing medical professionals to provide optimal care treatment and prescribe the proper doses of medication. Overall, MAASFEP will serve as a valuable aid for patients living at home and healthcare professionals monitoring patients’ conditions.