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Item type:Publication, Access status: with files , PEPbench - Open, reproducible, and systematic benchmarking of automated pre-ejection period extraction algorithmsThe pre-ejection period (PEP) is a widely used cardiac parameter in psychophysiology that reflects the duration between the onset of ventricular depolarization and the opening of the aortic valve. PEP is often used as a marker of cardiac sympathetic nervous system (SNS) activity, particularly in within-subject comparisons under similar hemodynamic conditions. While many algorithms for automated PEP extraction from electrocardiography (ECG) and impedance cardiography (ICG) signals (more precisely, its first derivative, dZ/dt) have been proposed in literature, they have not been systematically benchmarked. This lack of standardized algorithm comparisons originates from the absence of open-source algorithms and annotated datasets for evaluating PEP extraction algorithms. To address this issue, we introduce PEPbench, an open-source Python package with different Q-peak and B-point detection algorithms from literature that can be combined to create comprehensive PEP extraction pipelines, and a standardized framework for evaluating PEP extraction algorithms. We use PEPbench to systematically compare 108 different algorithm combinations. All combinations are evaluated on two datasets with manually annotated Q-peaks and B-points, which we make publicly available as the first datasets with reference PEP annotations. Our results show that the algorithms can differ vastly in their performance and that B-point detection algorithms introduce a considerable amount of error. Thus, we suggest that automated PEP extraction algorithms should be used with caution on a beat-to-beat level as their error rates are relatively high. This highlights the need for open and reproducible benchmarking frameworks for PEP extraction algorithms to improve the quality of research findings in the field of psychophysiology. With PEPbench, we aim to take a first step toward this goal and encourage other researchers to engage in the evaluation of PEP extraction algorithms by contributing algorithms, data, and annotations. We hope to establish a community-driven platform, fostering innovation and collaboration in the field of psychophysiology and beyond.Publicationtype: Journal Article38 21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Systematic investigation of heart sound propagation using continuous wave radar(IEEE, 2025-01-16); ; ; ; Monitoring the propagation of mechanical cardiac signals throughout the body is crucial for assessing cardiovascular health. A common drawback of current gold standard methods for vital sign monitoring is the necessity for continuous skin contact. Radar-based sensing offers a promising alternative by enabling contactless measurement of cardiac activity, including heart sound signals. As previous research has primarily focused on deriving signals from proximal body regions, insights into heart sound propagation to peripheral areas are lacking. To address this, we systematically investigated whether radar-based heart sound detection and propagation measurement is feasible across the whole body. We recorded heart sounds in N=22 participants sequentially at eleven locations using a custom-built continuous-wave radar system and phonocardiogram as heart sound gold standard. Additionally, an electrocardiogram was acquired as reference for overall heart activity. After synchronization and preprocessing, we manually segmented the heart sounds and extracted temporal characteristics from ensemble-averaged signals. Our findings show that heart sounds can be detected across the entire body with the radar-based as well as the gold standard system. Furthermore, the heart sounds’ temporal characteristics vary between measurement locations. As the distance to the heart increases, we observed significantly increased propagation time intervals. This finding is consistent across both systems, exhibiting a strong agreement for the first heart sound (r = 0.73, p < 0.001) and a moderate agreement for the second heart sound (r = 0.56, p < 0.001). In conclusion, our work is the first to demonstrate that radar-based systems are feasible for contactless evaluation of heart sound propagation, offering new possibilities for research and health monitoring.Publicationtype: Journal Article59 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , EmRad: ubiquitous vital sign sensing using compact continuous-wave radars(IEEE, 2024-06-28); ; ; ; In biomedical monitoring, non-intrusive and continuous tracking of vital signs is a crucial yet challenging objective. Although accurate, traditional methods, such as electrocardiography (ECG) and photoplethysmography (PPG), necessitate direct contact with the patient, posing limitations for long-term and unobtrusive monitoring. To address this challenge, we introduce the EmRad system, an innovative solution harnessing the capabilities of continuous-wave (CW) radar technology for the contactless detection of vital signs, including heart rate and respiratory rate. EmRad discerns itself by emphasizing miniaturization, performance, scalability, and its ability to generate large-scale datasets in various environments. This article explains the system's design, focusing on signal processing strategies and motion artifact reduction to ensure precise vital sign extraction. The EmRad system's versatility is showcased through various case studies, highlighting its potential to transform vital sign monitoring in research and clinical contexts.Publicationtype: Journal Article75 48