Capacitive electrocardiogram (cECG), a tried and tested technique for more than 50 years, can replace the gold standard ECG only in certain applications where unobtrusiveness is aimed for at the expense of reduced signal quality. This inferiority is due, among other reasons, to the fragility of the capacitive coupling between the body and the electrode, observed as motion artifacts in the presence of time-variant coupling capacitance. Attempts were made to remove these artifacts in earlier studies using adaptive noise cancellation by assuming statistical independence between motion and ECG signals. This paper considers the mechanical vibrations of the human body itself as the source of time-variant coupling capacitances which can cause motion artifacts. Ballistocardiography (BCG) measurements on cECG electrodes were recorded and analyzed to investigate how these mechanical vibrations influence the coupling impedance of the clothing between the body and the electrode. A novel sensor has been proposed and tested in a test bench for four different nominal pressure values (15, 20, 25, and 30 mmHg) with minute increasing steps for the measurement of the coupling capacitance. Subsequently, simultaneous measurements of BCG and the coupling capacitance were conducted on three healthy subjects for two different electrode positions. A significant correlation between the coupling capacitance and ballistocardiograms measured was found both in time domain shapes and timefrequency distributions in all measurements.

The capacitive electrocardiograph (cECG) has been tested for several measurement scenarios, including hospital beds, car seats and chairs since it was first proposed. The inferior signal quality of the cECG compared to the gold standard ECG guides the ongoing research in the direction of out-of-hospital applications, where unobtrusiveness is sought and high-level diagnostic signal quality is not essential. This study aims to expand the application range of cECG not in terms of the measurement scenario but in the profile of the subjects by including subjects with implanted cardiac pacemakers. Within this study, 20 patients with cardiac pacemakers were recruited during their clinical device follow-up and cECG measurements were conducted using a seat equipped with integrated cECG electrodes. The multichannel cECG recordings of active unipolar and bipolar pacemaker stimulation were analyzed offline and evaluated in terms of $F_{\beta }$ scores using a pacemaker spike detection algorithm. $F_{\beta }$ scores from 3652 pacing events, varying from 0.62 to 0.78, are presented with influencing parameters in the algorithm and the comparison of cECG channels. By tuning the parameters of the algorithm, different ranges of $F_{\beta }$ scores were found as 0.32 to 0.49 and 0.78 to 0.88 for bipolar and unipolar stimulations, respectively. For the first time, this study shows the feasibility of a cECG system allowing health monitoring in daily use on subjects wearing cardiac pacemakers.

With higher levels of automation in vehicles, the need for robust driver monitoring systems increases, since it must be ensured that the driver can intervene at any moment. Drowsiness, stress and alcohol are still the main sources of driver distraction. However, physiological problems such as heart attacks and strokes also exhibit a significant risk for driver safety, especially with respect to the ageing population. In this paper, a portable cushion with four sensor units with multiple measurement modalities is presented. Capacitive electrocardiography, reflective photophlethysmography, magnetic induction measurement and seismocardiography are performed with the embedded sensors. The device can monitor the heart and respiratory rates of a vehicle driver. The promising results of the first proof-of-concept study with twenty participants in a driving simulator not only demonstrate the accuracy of the heart (above 70% of medical-grade heart rate estimations according to IEC 60601-2-27) and respiratory rate measurements (around 30% with errors below 2 BPM), but also that the cushion might be useful to monitor morphological changes in the capacitive electrocardiogram in some cases. The measurements can potentially be used to detect drowsiness and stress and thus the fitness of the driver, since heart rate variability and breathing rate variability can be captured. They are also useful for the early prediction of cardiovascular diseases, one of the main reasons for premature death. The data are publicly available in the UnoVis dataset.

Capacitive electrocardiogram (cECG) has been proposed for various applications to extend cardiac monitoring to everyday life. While offering unobtrusive measurement of an electrocardiogram, cECG measurements experience severe motion artifacts with higher amplitudes and longer durations, which results in gaps in the signal availability and deterioration in the signal quality. Time-variant coupling impedance of the cECG results from the variations in the contact pressure of through-clothing cECG measurements and is often used to model the nature of motion artifacts. This paper offers a new perspective to utilize the sensitive nature of the coupling impedance by introducing high-frequency sinusoidal variations in the contact pressure. The multiplicative interaction between the source signal and the coupling impedance modulates the amplitude of this sinusoidal with the ECG signal. This new technique is named Modulated ECG (mECG), as the ECG signal is merged to the envelope of the resulting carrier wave. The proposed idea of a contact pressure modulated with a high-frequency sinusoidal is investigated analytically in a cECG electrode model. The numerical simulations based on the electrode model are supported by the physical simulations conducted in a test bench using an electrode prototype proposed for mECG measurements. Among the factors influencing mECG measurements, the type of textile, contact pressure, and modulation frequency are investigated. Moreover, the electrode model with a parallel capacitor and resistor as the coupling impedance is evaluated by impedance measurements of textiles. mECG amplitudes are found lower than those of cECG with a factor greater than 398, yet cECG measurements are not affected by the parallel mECG measurements in the tests. Therefore, the mECG technique can supplement the cECG by being measured simultaneously using the same electrode.

Neonatal intensive care units provide vital medical support for premature infants. The key aspect in neonatal care is the continuous monitoring of vital signs measured using adhesive skin sensors. Since sensors can cause irritation of the skin and lead to infections, research focuses on contact-free, camera-based methods such as infrared thermography and photoplethysmography imaging. The development of image processing algorithms requires large datasets, but recording the necessary data from studies brings tremendous effort and costs. Therefore, realistic patient phantoms would be feasible to create a comprehensive dataset and validate image-based algorithms. This work describes the realization of a neonatal phantom which can simulate physiological vital parameters such as pulse rate and thermoregulation. It mimics the outer appearance of premature infants using a 3D printed base structure coated with several layers of modified, skin-colored silicone. A distribution of red and infrared LEDs in the scaffold enables the simulation of a PPG signal by mimicking pulsative light intensity changes on the skin. Additionally, the body temperature of the phantom is individually adjustable in several regions using heating elements. In the validation process for PPG simulation, the feasibility of setting different pulse frequencies and the variation of oxygen saturation levels was obtained. Furthermore, heating tests showed region-dependent temperature variations between 0.19C and 0.81C around the setpoint. In conclusion, the proposed neonatal phantom can be used to simulate a variety of vital parameters of preterm infants and, therefore, enables the implementation of image processing algorithms for the analysis of the medical state.