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 …
communicable disease caused by paroxysmal abnormal super-synchronous electrical …
[HTML][HTML] One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
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 …
leading to transient brain dysfunctions. This paper proposed an EEG based real-time …
Exploring the intrinsic features of EEG signals via empirical mode decomposition for depression recognition
J Shen, Y Zhang, H Liang, Z Zhao… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Depression is a severe psychiatric illness that causes emotional and cognitive impairment
and has a considerable impact on patients' thoughts, behaviors, feelings and well-being …
and has a considerable impact on patients' thoughts, behaviors, feelings and well-being …
Automatic seizure detection by convolutional neural networks with computational complexity analysis
Abstract Background and Objectives Nowadays, an automated computer-aided diagnosis
(CAD) is an approach that plays an important role in the detection of health issues. The main …
(CAD) is an approach that plays an important role in the detection of health issues. The main …
Patient-independent seizure detection based on channel-perturbation convolutional neural network and bidirectional long short-term memory
G Liu, L Tian, W Zhou - International journal of neural systems, 2022 - World Scientific
Automatic seizure detection is of great significance for epilepsy diagnosis and alleviating the
massive burden caused by manual inspection of long-term EEG. At present, most seizure …
massive burden caused by manual inspection of long-term EEG. At present, most seizure …
Automatic epileptic seizure detection in EEG signals using sparse common spatial pattern and adaptive short-time Fourier transform-based synchrosqueezing …
Epilepsy can now be diagnosed more accurately and quickly due to computer-aided seizure
detection utilizing Electroencephalography (EEG) recordings. In this work, a novel method …
detection utilizing Electroencephalography (EEG) recordings. In this work, a novel method …
Epileptic seizure detection with deep EEG features by convolutional neural network and shallow classifiers
Introduction In the clinical setting, it becomes increasingly important to detect epileptic
seizures automatically since it could significantly reduce the burden for the care of patients …
seizures automatically since it could significantly reduce the burden for the care of patients …
[HTML][HTML] 基于脑电信号的癫痫发作预测研究进展
长明韩， 福来彭， 财陈， 文超李， 昔坤张… - Sheng Wu Yi Xue …, 2021 - ncbi.nlm.nih.gov
癫痫作为一种神经系统常见疾病， 具有发病率高、 突发性和反复性的特点。
及时预测癫痫发作并进行干预治疗， 可以显著减少患者的意外伤害。 当前 …
及时预测癫痫发作并进行干预治疗， 可以显著减少患者的意外伤害。 当前 …
Multiscale temporal self-attention and dynamical graph convolution hybrid network for EEG-based stereogram recognition
L Shen, M Sun, Q Li, B Li, Z Pan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Stereopsis is the ability of human beings to get the 3D perception on real scenarios. The
conventional stereopsis measurement is based on subjective judgment for stereograms …
conventional stereopsis measurement is based on subjective judgment for stereograms …