Biosensors & Bioelectronics

Machine Learning and Wearable Technology for Monitoring Biomedical Signal Pattern Changes during Pre-Migraine Nights

Abstract

Braswell Massimo*

The integration of machine learning and wearable technology has opened new possibilities for the continuous monitoring of biomedical signals, offering profound implications for personalized healthcare. One particularly promising application lies in detecting early indicators of migraines by monitoring physiological changes during pre-migraine nights. Migraines are a debilitating neurological condition that affects millions worldwide, characterized by recurring headaches often accompanied by other symptoms such as nausea, sensitivity to light, and aura. Understanding the subtle biomedical signal pattern changes that precede a migraine could provide an opportunity for early intervention, potentially mitigating the severity of symptoms or preventing the onset entirely. Wearable devices have become increasingly sophisticated, capable of monitoring a range of physiological parameters such as heart rate, skin temperature, blood oxygen saturation, electro dermal activity, and sleep patterns. When paired with machine learning algorithms, these devices can analyze complex, multidimensional data streams to identify patterns indicative of an impending migraine. The ability to collect longitudinal data from wearable technology provides a unique advantage for detecting subtle changes in physiology, which might be challenging to observe in clinical settings or through self-reporting alone