New portable electrocardiogram (ECG) measurement systems are emerging into market. Some use nonstandard bipolar electrode montage and sometimes very small interelectrode distances to improve the usability of the system. Modeling could provide a straightforward method to test new electrode systems. The aim of this study was to assess whether modeling the electrodes' measuring sensitivity with lead field method can provide a simple tool for testing a number of new electrode locations. We evaluated whether the actual ECG signal strength can be estimated by lead fields with two realistic 3D finite difference method (FDM) thorax models. We compared the modeling results to clinical body surface potential map (BSPM) data from 236 normal patients and studied 117 unipolar and 42 bipolar leads. In the case of unipolar electrodes the modeled measuring sensitivities correlated well with the clinical data (r=0.86, N=117, p<0.05). In the case of bipolar electrodes the correlation was moderate (r=0.62 between Model 1 and clinical data, r=0.71 between Model 2 and clinical data, N=42 and p<0.05 for both). Based on this we can conclude that lead field analysis based on realistic thorax models provides a good initial prediction for designing new electrode montages and measurement systems.
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http://dx.doi.org/10.1016/j.cmpb.2008.12.005 | DOI Listing |
Glob Ment Health (Camb)
November 2024
Global Health Section, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
Evidence on the effectiveness and implementation of mental health and psychosocial support (MHPSS) interventions for men in humanitarian settings is limited. Moreover, engagement and retention of men in such interventions has been challenging. Adaptations may therefore be required to improve the appropriateness and acceptability of these interventions for men.
View Article and Find Full Text PDFEur Heart J Imaging Methods Pract
October 2024
Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Lund 221 00, Sweden.
Aims: 4D blood flow measurements by cardiac magnetic resonance imaging (CMR) can be used to simplify blood flow assessment. Compressed sensing (CS) can provide better flow measurements than conventional parallel imaging (PI), but clinical validation is needed. This study aimed to validate stroke volume (SV) measurements by 4D-CS in healthy volunteers and patients while also investigating the influence of the CS image reconstruction parameter on haemodynamic parameters.
View Article and Find Full Text PDFCureus
December 2024
Department of Critical Care Medicine, Citizens Specialty Hospital, Hyderabad, IND.
Background: Sepsis is a life-threatening condition arising from a dysregulated host response to infection leading to organ dysfunction. Traditional clinical signs are often unreliable for detecting sepsis, necessitating the exploration of more accurate biomarkers. Furthermore, currently, recommended screening scores perform poorly, necessitating more effective biomarkers to identify sepsis.
View Article and Find Full Text PDFCureus
December 2024
Biostatistics, The Oxford Center, Brighton, USA.
Using simulated data with duplicate observational data points, this research aims to highlight the notable efficiency of repeated measures analysis of variance (ANOVA) compared to one-way ANOVA as a more powerful statistical model. One of the principal advantages of repeated measures ANOVA is its design, in which each subject acts as their own control. This methodology allows for the statistical mitigation of individual differences among subjects, thereby reducing extraneous variability (noise) that can obscure the effects of the experimental conditions under investigation.
View Article and Find Full Text PDFJAMIA Open
February 2025
Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN 46202, United States.
Objective: Measurement of health-related social needs (HRSNs) is complex. We sought to develop and validate computable phenotypes (CPs) using structured electronic health record (EHR) data for food insecurity, housing instability, financial insecurity, transportation barriers, and a composite-type measure of these, using human-defined rule-based and machine learning (ML) classifier approaches.
Materials And Methods: We collected HRSN surveys as the reference standard and obtained EHR data from 1550 patients in 3 health systems from 2 states.
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