A shallow autoencoder framework for epileptic seizure detection in EEG signals
This paper presents a trainable hybrid approach involving a shallow autoencoder (AE) and
a conventional classifier for epileptic seizure detection. The signal segments of a channel of …
a conventional classifier for epileptic seizure detection. The signal segments of a channel of …
A Hybrid Compressive Sensing and Classification Approach for Dynamic Storage Management of Vital Biomedical Signals
The efficient compression and classification of medical signals, particularly
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …
A 2.7 μJ/classification Machine-Learning based Approximate Computing Seizure Detection SoC
An electroencephalogram (EEG) based non-invasive 2-channel System on Chip (SoC) is
presented to detect and report the seizure event of the epileptic patient. The SoC …
presented to detect and report the seizure event of the epileptic patient. The SoC …
Shallow sparse autoencoder based epileptic seizure prediction
Epileptic patients' quality of life can be significantly improved by epileptic seizure prediction
based on scalp electroencephalogram (EEG). With the advancement of brain e-health …
based on scalp electroencephalogram (EEG). With the advancement of brain e-health …
Classifying Single Channel Epileptic EEG data based on Sparse Representation using Shallow Autoencoder
Patient independent epileptic seizure detection algorithm for scalp electroencephalogram
(EEG) data is pro-posed in this paper. Principal motivation of this work is to integrate neural …
(EEG) data is pro-posed in this paper. Principal motivation of this work is to integrate neural …
Single-channel EEG completion using Cascade Transformer
C Zhang, S Han, M Zhang - 2022 IEEE Biomedical Circuits and …, 2022 - ieeexplore.ieee.org
It is easy for the electroencephalogram (EEG) signal to be incomplete due to packet loss,
electrode falling off, etc. This paper proposed a Cascade Transformer architecture and a …
electrode falling off, etc. This paper proposed a Cascade Transformer architecture and a …
[PDF][PDF] A Hybrid Compressive Sensing and Classification Approach for Dynamic Storage Management of Vital Biomedical Signals
AD ALGARNI, NF SOLIMAN, FE ABD EL-SAMIE - 2023 - researchgate.net
The efficient compression and classification of medical signals, particularly
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …