Automated epileptic seizure waveform detection method based on the feature of the mean slope of wavelet coefficient counts using a hidden Markov model and EEG signals-Reference-Cited by-同舟云学术

Automated epileptic seizure waveform detection method based on the feature of the mean slope of wavelet coefficient counts using a hidden Markov model and EEG signals

Published:2020-04 Issue:2 Volume:42 Page:217-229
ISSN:1225-6463
Container-title:ETRI Journal
language:en
Short-container-title:ETRI Journal

Author:

Lee Miran¹^ORCID,Ryu Jaehwan²,Kim Deok‐Hwan³^ORCID

Affiliation:

1. Graduate School of Information Science and Engineering Ritsumeikan University Shiga Japan

2. Technical Research Institute Sammi Information System Seoul Rep. of Korea

3. Department of Electronic Engineering Inha University Incheon Rep. of Korea

Funder

Industrial Technology Innovation Program funded by the Ministry of Trade, Industry & Energy

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education

Institute for Information & communications Technology Promotio

Publisher

Wiley

Subject

Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.4218/etrij.2018-0118

Reference47 articles.

1. Seizure prediction: the long and winding road

2. Seizure prediction and the preseizure period

3. Classification of ictal and seizure-free EEG signals using fractional linear prediction

4. Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks

5. EEG signal classification using PCA, ICA, LDA and support vector machines

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Early detection of stroke disease using patients previous medical data instil with deep learning;Multimedia Tools and Applications;2024-07-01

2. Hybrid deep learning and metaheuristic model based stroke diagnosis system using electroencephalogram (EEG);Biomedical Signal Processing and Control;2024-01

3. Machine Learning-Based Stroke Disease Detection System Using Biosignals (ECG and PPG);Lecture Notes in Networks and Systems;2024

4. Cerebral infraction prediction system using ECG and PPG bio-signal;i-manager's Journal on Digital Signal Processing;2024

5. Multiple Explainable Approaches to Predict the Risk of Stroke Using Artificial Intelligence;Information;2023-08-01