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Swetha Lenkala, Revathi Marry, Susmitha Reddy Gopovaram, Tahir Cetin Akinci and Oguzhan Topsakal
Epilepsy is a neurological disease characterized by recurrent seizures caused by abnormal electrical activity in the brain. One of the methods used to diagnose epilepsy is through electroencephalogram (EEG) analysis. EEG is a non-invasive medical test fo...
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Navaneethakrishna Makaram, Sarvagya Gupta, Matthew Pesce, Jeffrey Bolton, Scellig Stone, Daniel Haehn, Marc Pomplun, Christos Papadelis, Phillip Pearl, Alexander Rotenberg, Patricia Ellen Grant and Eleonora Tamilia
In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images is an alternati...
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Yubo Zheng, Yingying Luo, Hengyi Shao, Lin Zhang and Lei Li
Contrastive learning, as an unsupervised technique, has emerged as a prominent method in time series representation learning tasks, serving as a viable solution to the scarcity of annotated data. However, the application of data augmentation methods duri...
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Muhammad Haseeb Aslam, Syed Muhammad Usman, Shehzad Khalid, Aamir Anwar, Roobaea Alroobaea, Saddam Hussain, Jasem Almotiri, Syed Sajid Ullah and Amanullah Yasin
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. Around 65 million people are affected by epilepsy worldwide. Patients with focal epilepsy can be treated with surgery, whereas generalized epileptic seizu...
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Hezam Albaqami, Ghulam Mubashar Hassan and Amitava Datta
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Wallace Moreira Bessa and Gabriel da Silva Lima
Memristive neuromorphic systems represent one of the most promising technologies to overcome the current challenges faced by conventional computer systems. They have recently been proposed for a wide variety of applications, such as nonvolatile computer ...
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Zhiwei Li, Jun Li, Yousheng Xia, Pingfa Feng and Feng Feng
Epileptic diseases take EEG as an important basis for clinical judgment, and fractal algorithms were often used to analyze electroencephalography (EEG) signals. However, the variation trends of fractal dimension (D) were opposite in the literature, i.e.,...
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Anis Malekzadeh, Assef Zare, Mahdi Yaghoobi and Roohallah Alizadehsani
This paper proposes a new method for epileptic seizure detection in electroencephalography (EEG) signals using nonlinear features based on fractal dimension (FD) and a deep learning (DL) model. Firstly, Bonn and Freiburg datasets were used to perform exp...
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Aníbal Romney and Vidya Manian
Epilepsy patients who do not have their seizures controlled with medication or surgery live in constant fear. The psychological burden of uncertainty surrounding the occurrence of random seizures is one of the most stressful and debilitating aspects of t...
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Amirsalar Mansouri, Sanjay P. Singh and Khalid Sayood
Epilepsy is one of the three most prevalent neurological disorders. A significant proportion of patients suffering from epilepsy can be effectively treated if their seizures are detected in a timely manner. However, detection of most seizures requires th...
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