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Seizure prediction—ready for a new era
Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming
majority of people with epilepsy regard the unpredictability of seizures as a major issue …
majority of people with epilepsy regard the unpredictability of seizures as a major issue …
EEG seizure detection and prediction algorithms: a survey
Epilepsy patients experience challenges in daily life due to precautions they have to take in
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …
A long short-term memory deep learning network for the prediction of epileptic seizures using EEG signals
The electroencephalogram (EEG) is the most prominent means to study epilepsy and
capture changes in electrical brain activity that could declare an imminent seizure. In this …
capture changes in electrical brain activity that could declare an imminent seizure. In this …
Seizure forecasting and cyclic control of seizures
Epilepsy is a unique neurologic condition characterized by recurrent seizures, where
causes, underlying biomarkers, triggers, and patterns differ across individuals. The …
causes, underlying biomarkers, triggers, and patterns differ across individuals. The …
Classification of epilepsy EEG signals using DWT-based envelope analysis and neural network ensemble
M Li, W Chen, T Zhang - Biomedical Signal Processing and Control, 2017 - Elsevier
Epilepsy is a neurological disorder of brain which is characterized by recurrent disorders.
And people with epilepsy and their families frequently suffer from stigma and discrimination …
And people with epilepsy and their families frequently suffer from stigma and discrimination …
Epileptic seizure prediction using CSP and LDA for scalp EEG signals
TN Alotaiby, SA Alshebeili, FM Alotaibi… - Computational …, 2017 - Wiley Online Library
This paper presents a patient‐specific epileptic seizure predication method relying on the
common spatial pattern‐(CSP‐) based feature extraction of scalp electroencephalogram …
common spatial pattern‐(CSP‐) based feature extraction of scalp electroencephalogram …
Seizure prediction based on transformer using scalp electroencephalogram
J Yan, J Li, H Xu, Y Yu, T Xu - Applied Sciences, 2022 - mdpi.com
Epilepsy is a chronic and recurrent brain dysfunction disease. An acute epileptic attack will
interfere with a patient's normal behavior and consciousness, having a great impact on their …
interfere with a patient's normal behavior and consciousness, having a great impact on their …
Closed-loop neural prostheses with on-chip intelligence: A review and a low-latency machine learning model for brain state detection
The application of closed-loop approaches in systems neuroscience and therapeutic
stimulation holds great promise for revolutionizing our understanding of the brain and for …
stimulation holds great promise for revolutionizing our understanding of the brain and for …
Reinforcement learning for intelligent healthcare systems: A review of challenges, applications, and open research issues
The rise of chronic disease patients and the pandemic pose immediate threats to healthcare
expenditure and mortality rates. This calls for transforming healthcare systems away from …
expenditure and mortality rates. This calls for transforming healthcare systems away from …
An ultra-low power reconfigurable biomedical ai processor with adaptive learning for versatile wearable intelligent health monitoring
Wearable intelligent health monitoring devices with on-device biomedical AI processor can
be used to detect the abnormity in users' biomedical signals (eg, ECG arrythmia …
be used to detect the abnormity in users' biomedical signals (eg, ECG arrythmia …