arXiv subjects

Clara Becker

Publications and source records attributed to Clara Becker.

4 recordsLinked to original sources

arXiv2026

Inter-Electrode Pulse Wave Velocity: A Direct Method for Maternal Arterial Stiffness Assessment During Pregnancy Using Multi-Channel ECG

Objective: To validate a novel inter-electrode pulse wave velocity (PWV) method that measures pulse propagation between ECG electrodes without left ventricular ejection time (LVET) estimation. Methods: We analyzed 43 three-channel ECG recordings (1000 Hz) from the FELICITy 2 cohort (approximately 19 and 35 weeks gestation). R-peaks were independently detected per channel using an ensemble approach. Time lags (Delta t) between matched R-peaks across electrode pairs were used to compute PWV as PWV = L / Delta t, where L is effective inter-electrode distance. Three channel pairs yielded independent PWV estimates. Temporal stability was assessed using sliding windows (1-15 minutes). To test whether Delta t reflects morphology or vascular propagation, we evaluated three QRS fiducials (R-peak, QRS onset, maximum dV/dt) and two bandpass filters (0.5-40 and 0.5-100 Hz). Longitudinal changes were compared between control (n=24) and yoga (n=20) groups. Results: PWV values were physiologically plausible and consistent with aortic PWV (5-10 m/s): control 7.40 +/- 1.51 vs 6.98 +/- 1.63 m/s; yoga 7.10 +/- 2.15 vs 8.16 +/- 0.91 m/s (early vs late pregnancy). PWV stabilized at 5 minutes (coefficient of variation 12.3 percent), with 2.6- to 5.2-fold lower variability than heart rate and heart rate variability. Inter-electrode delays (15-27 ms) persisted across fiducials and were minimally affected by filter settings (change -8.5 percent, not significant), arguing against purely morphological distortion; PWV remained within 6.8-9.1 m/s. Preliminary group trends differed (control -5.7 percent, yoga +14.9 percent; interaction p=0.07). Conclusions: Inter-electrode PWV enables direct spatial assessment of pulse propagation with physiologically valid values, is robust to fiducial and filtering choices, and shows promise for pregnancy-related arterial stiffness assessment with standard multi-channel ECG.

physics.med-ph↗

arXiv2026

Prenatal Stress Detection from Electrocardiography Using Self-Supervised Deep Learning: Development and External Validation

Prenatal psychological stress affects 15-25% of pregnancies and increases risks of preterm birth, low birth weight, and adverse neurodevelopmental outcomes. Current screening relies on subjective questionnaires (PSS-10), limiting continuous monitoring. We developed deep learning models for stress detection from electrocardiography (ECG) using the FELICITy 1 cohort (151 pregnant women, 32-38 weeks gestation). A ResNet-34 encoder was pretrained via SimCLR contrastive learning on 40,692 ECG segments per subject. Multi-layer feature extraction enabled binary classification and continuous PSS prediction across maternal (mECG), fetal (fECG), and abdominal ECG (aECG). External validation used the FELICITy 2 RCT (28 subjects, different ECG device, yoga intervention vs. control). On FELICITy 1 (5-fold CV): mECG 98.6% accuracy (R2=0.88, MAE=1.90), fECG 99.8% (R2=0.95, MAE=1.19), aECG 95.5% (R2=0.75, MAE=2.80). External validation on FELICITy 2: mECG 77.3% accuracy (R2=0.62, MAE=3.54, AUC=0.826), aECG 63.6% (R2=0.29, AUC=0.705). Signal quality-based channel selection outperformed all-channel averaging (+12% R2 improvement). Mixed-effects models detected a significant intervention response (p=0.041). Self-supervised deep learning on pregnancy ECG enables accurate, objective stress assessment, with multi-layer feature extraction substantially outperforming single embedding approaches.

q-bio.QM↗

arXiv2025

Heart Rate Variability Patterns Reflect Yoga Intervention in Chronically Stressed Pregnant Women: A Quasi-Randomized Controlled Trial

Prenatal maternal stress (PS) is a risk factor for adverse offspring neurodevelopment. Heart rate variability (HRV) complexity provides a non-invasive marker of maternal autonomic regulation and may be influenced by mind--body interventions such as Yoga. In this quasi-randomized controlled trial, 28 chronically stressed pregnant women were followed from the second trimester until birth: 14 participated in weekly Hatha Yoga with electrocardiogram (ECG) recordings, and 14 received standard obstetric care with monthly ECGs. Group allocation was based on availability, with participants unaware of their assignment at enrollment. HRV complexity was assessed first with Sample Entropy and Entropy Rate and then expanded to 94 HRV metrics spanning temporal, frequency, nonlinear, and information-theoretical domains. All metrics were covariate-adjusted (maternal age, BMI, gestational age), standardized, and analyzed using timepoint-specific principal component analysis (PCA). From this, a unified HRV index was derived. Analyses revealed that HRV metric relationships changed dynamically across pregnancy, with PCA loadings shifting from frequency toward complexity measures in late gestation. The mixed effects model identified a significant time x group interaction effect (p = 0.041). These findings suggest a restructuring of HRV signal-analytical domains with advancing pregnancy attributable to Yoga and highlight the utility of advanced HRV analysis frameworks for future, larger trials.

q-bio.QM↗

arXiv2023

Pulsed RF Knock-Out Extraction: A Potential Enabler for FLASH Hadrontherapy in the Bragg Peak

One challenge on the path to delivering FLASH-compatible beams with a synchrotron is facilitating an accurate dose-control for the required ultra-high dose rates. We propose the use of pulsed RFKO extraction instead of continuous beam delivery as a way to control the dose delivered per Voxel. In a first feasibility test dose rates in pulses of up to 600 Gy/s were observed, while the granularity at which the dose was delivered is expected to be well below 0.5 Gy.

physics.med-ph↗