A5013037158- ECG Monitoring and Analysis
- Cardiac electrophysiology and arrhythmias
- Cardiovascular Function and Risk Factors
- Cardiac Imaging and Diagnostics
- Control Systems and Identification
- Cardiac Arrhythmias and Treatments
- EEG and Brain-Computer Interfaces
- Healthcare Technology and Patient Monitoring
- Probabilistic and Robust Engineering Design
- Cardiac Arrest and Resuscitation
- Robot Manipulation and Learning
- Cardiovascular Effects of Exercise
- Mobile Health and mHealth Applications
- Heart Rate Variability and Autonomic Control
- Delphi Technique in Research
- Electronic Health Records Systems
- Teleoperation and Haptic Systems
- Advanced Electrical Measurement Techniques
- Cardiac pacing and defibrillation studies
- Industrial Vision Systems and Defect Detection
- Advancements in Battery Materials
- Image and Signal Denoising Methods
- Advanced MRI Techniques and Applications
- Transition Metal Oxide Nanomaterials
- Advanced Battery Technologies Research
Royal HaskoningDHV (Netherlands)
2018-2021
CRV (Netherlands)
2015-2018
Université de Bordeaux
2018
University of Lucerne
2018
Electrophysiology and Heart Modeling Institute
2018
The inverse problem of electrocardiography is illposed.Errors in the model such as signal noise can impact accuracy reconstructed cardiac electrical activity.It currently not known how sensitive to processing techniques.To evaluate this, experimental data from a Langendorffperfused pig heart (n=1) suspended human-shaped torso-tank was used.Different methods were applied torso potentials recorded 128 electrodes embedded tank surface.Processing divided into three categories i) highfrequency...
Goal: To evaluate state-of-the-art signal processing methods for epicardial potential-based noninvasive electrocardiographic imaging reconstructions of single-site pacing data. Methods: Experimental data were obtained from two torso-tank setups in which Langendorff-perfused hearts (n = 4) suspended and potentials recorded simultaneously torso surfaces. 49 different applied to potentials, grouped as i) high-frequency noise removal (HFR) ii) baseline drift (BDR) iii) combined HFR+BDR. The...
The purpose of this research is to localize ECG electrodes from a 3D photo and reduce electrode misplacement related errors in the interpretation.A Kinect camera used take photo, which registered automatically model derived MRI/CT(MC).The registration algorithms use sternum marker attached skin enable an accurate fast matching MC model.The have been compared optimal manual registration.For all cases automatic performed much better than registration.The with patient specific positions will...
Longitudinal monitoring of sometimes subtle waveform changes the 12‑lead electrocardiogram (ECG) is complicated by patient-specific and technical factors, such as inaccuracy electrode repositioning. This feasibility study uses a 3D camera to reduce repositioning errors, ECG variability enable detailed longitudinal monitoring. Per subject, three clinical ECGs were obtained during routine follow-up. Additionally, two recorded guided cameras, which used capture precordial locations direct...
To overcome the ill-posed nature of inverse problem electrocardiography (ECG) and stabilize solutions, regularization is used.Despite several studies on noise, effect prefiltering ECG signals regularized solutions has not been explored.We used Bayesian estimation for solving with without applying various methods, evaluated our results using experimental data that came from a Langendorff-perfused pig heart suspended in humanshaped torso-tank.Epicardial electrograms were recorded during RV...
Studying electrocardiography is intellectually challenging since it involves a myriad of theories and complex associations. For example, the electrocardiogram (ECG) non-invasive recording electrical activity heart its interpretation requires an intricate understanding how these signals relate to cardiac mechanics (referred as electromechanical link). Furthermore, often difficult revert recorded from body surface internal health organ. To help alleviate challenges, ECGSim software application...
Abstract Objective. This study aims to assess the sensitivity of epicardial potential-based electrocardiographic imaging (ECGI) removal or interpolation bad leads. Approach. We utilized experimental data from two distinct centers. Langendorff-perfused pig ( n = 2) and dog hearts were suspended in a human torso-shaped tank paced ventricles. Six different lead configurations designed based on clinical experience. Five methods applied estimate missing data. Zero-order Tikhonov regularization...
The Consortium for ECG Imaging (CEI) has formed several collaborative projects to evaluate and improve technical aspects of Electrocardiographic (ECGI), but these efforts are not yet implemented into an integrated software framework. We developed a framework unify the multiple techniques stages ECGI one pipeline. This merges existing open source packages: SCIRun, problem solving environment; Forward/Inverse toolkit, series SCIRun modules ECGI; PFEIFER, cardiac signal pre-processing tool....
Patients with arrhythmogenic cardiomyopathy (ACM) often present ventricular arrhythmias due to local activation delay. Early detection of delay could aid in preventing sudden cardiac death. The aim this feasibility study is use a novel ECG analysis method , the mean temporal spatial isochrones (meanTSI), as marker delay.We included 16 patients symptomatic ACM, 6 asymptomatic ACM and controls.The standard 12 lead heart model were used construct meanTSI 25 ms after end QRS complex.Asymptomatic...
Accurate beat classification and alignment is fundamental to any signal averaging method. The objective of this study was investigate the accuracy different methods, impact pre-processing methods on these algorithms. Experimental data came from a human-shaped torso tank, with 256 body surface ECG recorded during sinus rhythm (SR) left ventricular pacing (LVP) (n=4). "Gold-standard" were defined cardiac electrograms. Six baseline drift removal (BDR) applied ECG. Subsequently, 3 segmentation...
The Consortium for ECG Imaging (CEI) has formed several collaborative projects to evaluate and improve technical aspects of Electrocardiographic (ECGI), but these efforts are not yet implemented into an integrated software framework. We developed a framework unify the multiple techniques stages ECGI one pipeline. This merges existing open source packages: SCIRun, problem solving environment; Forward/Inverse toolkit, series SCIRun modules ECGI; PFEIFER, cardiac signal pre-processing tool....