High Accuracy Epileptic Seizure Detection System Based on Wearable Devices Using Support Vector Machine Classifier
Author:
Funder
Zewail City of Science and Technology
Siemens
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9664825/9664893/09664898.pdf?arnumber=9664898
Reference22 articles.
1. Epilepsyecosystem.org: crowd-sourcing reproducible seizure prediction with long-term human intracranial EEG
2. Signal quality and patient experience with wearable devices for epilepsy management
3. Linear and Nonlinear Feature Extraction for Neural Seizure Detection
4. Low-Power Hardware Implementation of a Support Vector Machine Training and Classification for Neural Seizure Detection
5. Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG
Cited by 3 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. An Effective Approach for Newspaper Article Classification using Multi-Class Support Vector Machine in Comparison with Binary Classifier to improve Accuracy;2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM);2023-04-06
2. FPGA Utilized Implementation of Epileptic Seizure Detection System Based on Wearable Devices using Dynamic Partial Reconfiguration;2022 10th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC);2022-12-19
3. Advances in Biosignal Sensing and Signal Processing Methods with Wearable Devices;Analysis & Sensing;2022-11-14
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