Artifact removal from EEG signals using regenerative multi-dimensional singular value decomposition and independent component analysis
AM Judith, SB Priya, RK Mahendran - Biomedical Signal Processing and …, 2022 - Elsevier
The EEG signals are regularly blended with sources like Electrooculogram, Electromyogram
and few other artifacts caused by physical or signal interferences. The presence of artifacts …
and few other artifacts caused by physical or signal interferences. The presence of artifacts …
Epilepsy-Net: attention-based 1D-inception network model for epilepsy detection using one-channel and multi-channel EEG signals
In this paper, we propose and evaluate Epilepsy-Net, a collection of deep learning EEG
signal processing tools to detect epileptic seizures against non-epileptic seizures without …
signal processing tools to detect epileptic seizures against non-epileptic seizures without …
Source localization of EEG brainwaves activities via mother wavelets families for SWT decomposition
A Brain‐Computer Interface (BCI) is a system used to communicate with an external world
through the brain activity. The brain activity is measured by electroencephalography (EEG) …
through the brain activity. The brain activity is measured by electroencephalography (EEG) …
Hybrid approach: combining ecca and sscor for enhancing ssvep decoding
Currently, steady-state visual evoked potentials (SSVEPs) are applied in a variety of fields.
In these applications, spatial filtering is the most commonly used method for decoding …
In these applications, spatial filtering is the most commonly used method for decoding …
Design of active noise control system using hybrid functional link artificial neural network and finite impulse response filters
The active noise control is the best approach to limit the low-frequency noise present in any
applications and also to estimate the signals, which are corrupted by interference or additive …
applications and also to estimate the signals, which are corrupted by interference or additive …
Biomedical engineering fundamentals
RB Pachori, V Gupta - Intelligent Internet of Things: From Device to Fog …, 2020 - Springer
This chapter introduces the concept of bioelectricity and biomechanics. The descriptions of
several specific biosensors are also included in this chapter. The main aim of this chapter is …
several specific biosensors are also included in this chapter. The main aim of this chapter is …
Denoising-Aware Contrastive Learning for Noisy Time Series
Time series self-supervised learning (SSL) aims to exploit unlabeled data for pre-training to
mitigate the reliance on labels. Despite the great success in recent years, there is limited …
mitigate the reliance on labels. Despite the great success in recent years, there is limited …
Extraction and localization of non-contaminated alpha and gamma oscillations from EEG signal using finite impulse response, stationary wavelet transform, and …
The alpha and gamma oscillations derived from EEG signal are useful tools in recognizing a
cognitive state and several cerebral disorders. However, there are undesirable artifacts that …
cognitive state and several cerebral disorders. However, there are undesirable artifacts that …
An Adaptive Filter for Subdivision of Circular Grating Signal of Angle Measurement
Y Huang, S Che, G Zheng, W Zhu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Angle is an important physical quantity in International Systems of Units (SI). The precise
measurement of an angle is of great significance for scientific research and production. The …
measurement of an angle is of great significance for scientific research and production. The …
Identification of brain electrical activity related to head yaw rotations
Automatizing the identification of human brain stimuli during head movements could lead
towards a significant step forward for human computer interaction (HCI), with important …
towards a significant step forward for human computer interaction (HCI), with important …