An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods

M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Epilepsy is one of the most common complex brain disorders which is a chronic non-
communicable disease caused by paroxysmal abnormal super-synchronous electrical …

The challenging path to developing a mobile health device for epilepsy: the current landscape and where we go from here

I Hubbard, S Beniczky, P Ryvlin - Frontiers in Neurology, 2021 - frontiersin.org
Seizure detection, and more recently seizure forecasting, represent important avenues of
clinical development in epilepsy, promoted by progress in wearable devices and mobile …

Ictal autonomic changes as a tool for seizure detection: a systematic review

A van Westrhenen, T De Cooman… - Clinical Autonomic …, 2019 - Springer
Purpose Adequate epileptic seizure detection may have the potential to minimize seizure-
related complications and improve treatment evaluation. Autonomic changes often precede …

Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network

M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2023 - Elsevier
Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons,
leading to transient brain dysfunctions. This paper proposed an EEG based real-time …

Recognising drivers' mental fatigue based on EEG multi-dimensional feature selection and fusion

Y Zhang, H Guo, Y Zhou, C Xu, Y Liao - Biomedical Signal Processing and …, 2023 - Elsevier
Detecting the mental state of a driver using electroencephalography (EEG) signals can
reduce the probability of traffic accidents. However, EEG signals are unstable and nonlinear …

The power of ECG in multimodal patient‐specific seizure monitoring: added value to an EEG‐based detector using limited channels

K Vandecasteele, T De Cooman, C Chatzichristos… - …, 2021 - Wiley Online Library
Objective Wearable seizure detection devices could provide more reliable seizure
documentation outside the hospital compared to seizure self‐reporting by patients, which is …

Resource-aware distributed epilepsy monitoring using self-awareness from edge to cloud

F Forooghifar, A Aminifar… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The integration of wearable devices in humans' daily lives has grown significantly in recent
years and still continues to affect different aspects of high-quality life. Thus, ensuring the …

Decentralized federated learning for epileptic seizures detection in low-power wearable systems

S Baghersalimi, T Teijeiro, A Aminifar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In healthcare, data privacy of patients regulations prohibits data from being moved outside
the hospital, preventing international medical datasets from being centralized for AI training …

Neural stimulation systems for the control of refractory epilepsy: a review

MD Bigelow, AZ Kouzani - Journal of NeuroEngineering and …, 2019 - Springer
Epilepsy affects nearly 1% of the world's population. A third of epilepsy patients suffer from a
kind of epilepsy that cannot be controlled by current medications. For those where surgery is …

Many-to-one knowledge distillation of real-time epileptic seizure detection for low-power wearable internet of things systems

S Baghersalimi, A Amirshahi, F Forooghifar… - arXiv preprint arXiv …, 2022 - arxiv.org
Integrating low-power wearable Internet of Things (IoT) systems into routine health
monitoring is an ongoing challenge. Recent advances in the computation capabilities of …