Source localization of an epileptic seizure is becoming an important diagnostic tool in pre-surgical evaluation of epileptic patients. However, for localizing the epileptogenic zone precisely, the epileptic activity needs to be isolated from other activities that are not related to the epileptic source. In this study, we aim at an investigation of the effect of muscle artifact suppression by using a low-pass filter (LPF), independent component analysis (ICA), and a combination of ICA-LPF prior to source localization in focal epilepsy. These techniques were applied on the EEG data obtained from a left-temporal lobe epileptic patient by artificially contaminating the isolated spike interval, present in the four left-temporal electrodes, with a muscle artifact. The results show that the muscle artifact was fully suppressed. Applying the dipole and current-density reconstruction (CDR) source-analysis algorithms on the filtered data, we were able to identify the location of the epileptogenic zone similar to that of the original undistorted data.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/EMBC.2014.6944461 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Improving localization and measurements of M-waves using high-density surface electromyography.
J Neurophysiol
December 2024
Center for Neural Basis of Cognition, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA, USA.
Surface electromyography () is useful for studying muscle function and controlling prosthetics, but crosstalk from nearby muscles often limits its effectiveness. High-density surface EMG () improves spatial resolution, allowing for the isolation of in the densely packed forearm muscles. This study assessed for localizing and evaluated the impact of spatial filters on crosstalk reduction.
View Article and Find Full Text PDFAn Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model.
Sensors (Basel)
November 2024
Humanitarian Technology (HuT) Labs, Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri 690525, India.
Article Synopsis
- EEG is a non-invasive, portable technique widely used in brain-computer interfaces (BCIs) to help individuals with severe mobility issues control devices like wheelchairs through motor imagery signals.
- The study introduces a new approach for enhancing the quality of EEG recordings by addressing motion artifacts, which traditional methods struggle with, especially for users in motion.
- Utilizing a modified CNN deep learning algorithm and considering real-world variables, the research achieved a high classification accuracy of 94.04% in distinguishing movements, showcasing its effectiveness for practical BCI applications.
An Artifact in Concentric Needle EMG Recordings.
Muscle Nerve
December 2024
Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Introduction/aims: In healthy subjects, we observed high amplitude motor unit potential (MUP) waveforms that resembled the cannula potential (CP) with a positive sharp wave (PSW)-like waveform. We analyzed the source of this signal, its prevalence, and its effects on the analysis of electromyographic waveforms.
Methods: Three channel recordings were performed to explore the contribution of the needle core and cannula to the MUP.
Post-correctional improvement of T2-weighted fast spin echo magnetic resonance imaging pulse sequence for detecting high intensity focused ultrasound thermal lesions.
Heliyon
November 2024
Department of Physics, Toronto Metropolitan University, 350 Victoria Street, Toronto, ON, Canada.
Article Synopsis
- * The T2-weighted fast spin echo (T2W-FSE) MRI technique is commonly used to visualize HIFU-induced thermal lesions but suffers from issues like ringing artifacts and reduced spatial resolution due to T2 decay effects.
- * By applying an inverse Fourier transform (IFT) multiplication scheme with specially designed filters, researchers improved MRI image quality, resulting in significantly better spatial resolutions and enhanced signal-to-noise ratio in detecting thermal lesions.
Optimal transport assisted full waveform inversion for multiparameter imaging of soft tissues in ultrasound computed tomography.
Ultrasonics
March 2025
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:
Ultrasound computed tomography (USCT) has emerged as a promising platform for imaging tissue properties, offering non-ionizing and operator-independent capabilities. In this work, we demonstrate the feasibility of obtaining quantitative images of multiple acoustic parameters (sound speed and impedance) for soft tissues using full waveform inversion (FWI), which are justified with both numerical and experimental cases. A 3D reconstruction based on a series of 2D slice images is presented for the experimental case of ex vivo soft tissues.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!