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Saeid Sanei

8 accepted papers

2022

Online Detection of Scalp-Invisible Mesial-Temporal Brain Interictal Epileptiform Discharges from EEG

ICASSP 2022accepted

Brain interictal epileptiform discharges (IEDs) are transient events occurring between two or before seizure onsets. The IEDs are captured mainly by the intracranial EEG (iEEG) and only 4.7% of them are visible in our scalp EEG (sEEG) dataset. Here, we propose a method namely temporal components ana…

Cited by 0SourceScholar
2021

Incorporating Uncertainty In Data Labeling Into Detection of Brain Interictal Epileptiform Discharges From EEG Using Weighted optimization

ICASSP 2021accepted

Interictal epileptiform discharges (IEDs) can have various morphologies as well as spatial distributions and sometimes are associated with other brain activities, resulting in uncertainty in their labeling. Such an uncertainty corresponds to the probability of a waveform being an IED. Here, we incor…

Cited by 0SourceScholar
2020

Eeg Connectivity - Informed Cooperative Adaptive Line Enhancer for Recognition of Brain State

ICASSP 2020accepted

Bursts of sleep spindles and paroxysmal fast brain activity waveforms have frequency overlap whilst generally, paroxysmal waveforms have shorter duration than spindles. Both resemble bursts of normal alpha activity during short rests while awake with closed eyes. In this paper, it is shown that for…

Cited by 0SourceScholar
2019

Detection of Sleep Apnea/hypopnea Events Using Synchrosqueezed Wavelet Transform

ICASSP 2019accepted

In this article, detection of sleep apnea or hypopnea events is addressed using a single channel electrocardiography (ECG) signal by analysis of respiratory extracted modulation. First, R peaks are detected from ECG signal. Then, a time-series with the amplitude (height) and timing of R peaks repres…

Cited by 0SourceScholar
2018

Quaternion Adaptive Line Enhancer based on Singular Spectrum Analysis

ICASSP 2018accepted

Quaternion adaptive line enhancer (QALE) has been proposed recently for the recovery of two- (2-D) or three-dimensional (3-D) periodic signals from their noisy mixtures [1] with the help of quaternion-valued adaptive filtering theory. Similar to the traditionall-D [2] version, QALE, relies mainly on…

Cited by 0SourceScholar
2016

Coupled dictionary learning for multimodal data: An application to concurrent intracranial and scalp EEG

ICASSP 2016accepted

This paper focuses on learning a coupled dictionary between multimodal datasets where the data of different modes can be described as a function of each other. Our method is able to reconstruct the data of one mode by using the data of another mode. This provides the advantage on applications that l…

Cited by 0SourceScholar