@article{ref1,
title="Trends and challenges of processing measurements from wearable devices intended for epileptic seizure prediction",
journal="Journal of signal processing systems",
year="2022",
author="Xu, Yankun and Yang, Jie and Sawan, Mohamad",
volume="94",
number="6",
pages="527-542",
abstract="The rapid contemporary development of wearable devices offers non-invasive and effective approaches for monitoring the human brain. Recent studies have investigated the prediction of epileptic seizures (ESs) using wearable measurements, such as scalp electroencephalography and functional near-infrared spectroscopy. The signal processing tasks are the core component of emerging closed-loop ES prediction (ESP) systems. Various research groups have introduced many state-of-the-art signal processing techniques to improve ESP performance. Wearable measurements consider low frequency and low spatial resolution characteristics. In this paper, we provide a comprehensive review of signal processing techniques including preprocessing, feature extraction, dimensionality reduction and classification schemes for ESP systems. Trends and concerns of ESP studies at the end of the manuscript.<p /> <p>Language: en</p>",
language="en",
issn="1939-8018",
doi="10.1007/s11265-021-01659-x",
url="http://dx.doi.org/10.1007/s11265-021-01659-x"
}