A5085337235- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Epilepsy research and treatment
- Neurological disorders and treatments
- Functional Brain Connectivity Studies
- Neuroscience and Neural Engineering
- Blind Source Separation Techniques
- ECG Monitoring and Analysis
- Cardiac electrophysiology and arrhythmias
- Wireless Body Area Networks
- Music and Audio Processing
- Molecular Communication and Nanonetworks
- Neonatal and fetal brain pathology
- Speech and Audio Processing
- Non-Invasive Vital Sign Monitoring
WinnMed
2024
Mayo Clinic
2024
University of Houston
2022-2024
Mayo Clinic in Arizona
2024
Abstract Neuromodulation through implantable pulse generators (IPGs) represents an important treatment approach for neurological disorders. While the field has observed success of state-of-the-art interventions, such as deep brain stimulation (DBS) or responsive neurostimulation (RNS), systems face various technical challenges, including restriction recording from a limited number sites, power management, and external access to assessed neural data in continuous fashion. To best our...
Abstract Objective. High-frequency oscillations (HFOs) are considered a biomarker of the epileptogenic zone in intracranial EEG recordings. However, automated HFO detectors confound true with spurious events caused by presence artifacts. Approach. We hypothesized that, unlike pseudo-HFOs sharp transients or arbitrary shapes, real HFOs have signal characteristic that can be represented using small number oscillatory bases. Based on this hypothesis sparse representation framework, study...
Interictal high-frequency oscillation (HFO) is considered a promising biomarker of the epileptogenic zone. The pseudo-HFOs originating from artifacts and noise might escape HFO detectors mislead seizure onset zone (SOZ) localization. purpose this study to propose new sparse representation framework fused with random forest classifier detect real HFOs eliminate pseudo-ones. In scheme, each candidate event that passed conventional amplitude threshold-based detector was represented locally in...
High-Frequency Oscillation (HFO) is a promising biomarker of the epileptogenic zone. However, sharp artifacts might easily pass conventional HFO detectors as real HFOs and reduce seizure onset zone (SOZ) localization. We hypothesize that, unlike pseudo-HFOs, which originates from with changes or arbitrary waveform characteristic, could be represented by limited number oscillatory waveforms. Accordingly, to distinguish true ones we established new classification method based on sparse...
Neural recordings frequently get contaminated by ECG or pulsation artifacts. These large amplitude components can mask the neural patterns of interest and make visual inspection process difficult. The current study describes a sparse signal representation strategy that targets to denoise artifacts in local field potentials (LFPs) recorded intraoperatively. To estimate morphology artifact, we first detect QRS-peaks from simultaneously trace as an anchor point. After LFP data has been epoched...
The wireless transmission of neural data may pose the risk packet loss (PL), potentially compromising signal quality or, in extreme cases, causing complete loss. Addressing lost packets is essential to ensure integrity and preserve vital patterns. This study investigates effect PL interference on epilepsy neuro biomarkers, focusing specifically interictal epileptiform spikes high frequency oscillations (HFOs), performance low computational cost interpolation methods. We observed that 95% 81%...
This study presents a new data acquisition Framework for synchronous dual Brain Interchange (BIC) systems recording. The setup expands the capacity recording by offering access to up 64 channels. environment utilizes our Simulink model, incorporating functionalities synchronization using master clock and email-based status updates. We evaluated framework in lab simulations, we observed 38 ms post-synchronization delay between systems. also demonstrated that this error can be minimized as low...
While high-frequency oscillations (HFOs) and their stereotyped clusters (sHFOs) have emerged as potential neuro-biomarkers for the rapid localization of seizure onset zone (SOZ) in epilepsy, clinical application is hindered by challenge automated elimination pseudo-HFOs originating from artifacts heavily corrupted intraoperative neural recordings. This limitation has led to a reliance on semi-automated detectors, coupled with manual visual artifact rejection, impeding translation findings...
High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for localizing the seizure onset zone (SOZ) patients with focal refractory epilepsy. Despite their clinical significance, HFO analysis is often compromised by high-frequency artifacts that bypass conventional detectors, resulting false-positive events dilute reliability of pool. To address this challenge, study aimed to develop an automated method accurately identify and eliminate events,...
Interictal High-frequency Oscillation (HFO) between 80-600 Hz in intracranial EEG (iEEG) is a promising biomarker of the epileptogenic zone individuals with epilepsy. Numerous studies revealed that resection channels high rate HFOs correlates favorable surgical outcomes. Early feedback to clinicians regarding distribution during iEEG recording, especially after implantation electrodes, would be helpful for clinical decisions. However, recording can easily get corrupted by various factors...
In this study, we developed and validated an online analysis framework in MATLAB Simulink for recording of intracranial electroencephalography (iEEG). This aims to detect interictal spikes patients with epilepsy as the data is being recorded. An spike detection was performed over 10-minute iEEG recorded Brain Interchange CorTec three human subjects. A pool detected then broadcasted using User Datagram Protocol (UDP) external graphical user interface further post-processing visualization. The...