Advancements in Wearable Health Monitoring - Analyzing the Developments of Wearable Sensors and Machine Learning for Epileptic Seizure Detection to improve Athletic Performance

Abstract

Wearable technology (WT) is a revolution in real-time data analytics and sports performance tracking. Both new and professional athletes depend on wearable technology to improve their competitive outcomes and training efficiency. However, further studies are needed to gain complete understanding to optimize their full potential in sports. A warning before the onset of seizure is important to improve quality of life (QoL) of athletes who have epilepsy. There is a need to evaluate the feasibility of wearable sensors to predict seizures with machine learning (ML). Epilepsy poses different challenges to manage and monitor because of unpredictable seizures. Wearable devices provide real-time data collection and constant monitoring to provide insights to trends and patterns related to seizure. Wearable technology is helpful to manage seizure as it allows early prediction, detection, and personalized intervention to empower healthcare providers and patients. This study explores latest advancements in wearable sensors designed for managing epilepsy. The findings of this study has highlighted the importance of wearable devices to improve accuracy in seizure detection, improve patient health with real-time monitoring, and promote data-based decision-making. However, this study recommends further research to validate reliability and accuracy of those devices in different clinical settings and populations. Combined efforts are needed among clinicians, researchers, patients, and technology developers to drive advancements and innovation in wearable technology for managing epilepsy, ultimately improving quality of life and outcomes for people with this neurological disorder.