Continuous cardiac output is a significant matter that must be considered in monitoring the functioning of cardiovascular system. A non-invasive sensing system that is based on measuring electrical bioimpedance variations of radial artery is proposed to evaluate the physical condition of patient. To optimize the signal acquisition, different electrode placement strategies are compared with the goal of finding the most suitable ones. The finite element method (FEM) simulation of sensitivity distribution and experimental measurements on radial artery are performed for experimenting circular and distal electrode placements. Importantly, also the modified electrode placement strategies, guided by the idea of focused impedance method (FIM), are investigated. To reduce the number of electrodes in measurement setup, its novel version is proposed: a five-electrode FIM strategy. The efficiency of the proposed strategy can be seen in the reduced amount of required number of electrodes: the smaller area of electrode-skin contact interface results in smaller influence of uncertainties. Moreover, the reduced number of electrodes contributes to benefit through developing simpler instrumentation having lower energy consumption and cheaper manufacturing costs. The results show the advances of the proposed novel five-electrode FIM strategy for measuring the pulsating volume of blood in radial artery with the goal of determining the central aortic pressure (CAP) of blood.

Background: Wearable technologies for monitoring cardiovascular parameters, including electrocardiography (ECG) and impedance cardiography (ICG), propose a challenging research subject. The expectancy for wearable devices to be unobtrusive and miniaturized sets a goal to develop smarter devices and better methods for signal acquisition, processing, and decision-making. Methods: In this work, non-standard electrode placement configurations (EPC) on the thoracic area and single arm were experimented for ECG signal acquisition. The locations were selected for joint acquisition of ECG and ICG, targeted to suitability for integrating into wearable devices. The methodology for comparing the detected signals of ECG was developed, presented, and applied to determine the R, S, and T waves and RR interval. An algorithm was proposed to distinguish the R waves in the case of large T waves. Results: Results show the feasibility of using non-standard EPCs, manifesting in recognizable signal waveforms with reasonable quality for post-processing. A considerably lower median sensitivity of R wave was verified (27.3%) compared with T wave (49%) and S wave (44.9%) throughout the used data. The proposed algorithm for distinguishing R wave from large T wave shows satisfactory results. Conclusions: The most suitable non-standard locations for ECG monitoring in conjunction with ICG were determined and proposed.

In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90–94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.

Background: Pelotherapy is the traditional procedure of applying curative muds on the skin’s surface—shown to have a positive effect on the human body and cure illnesses. The effect of pelotherapy is complex, functioning through several mechanisms, and depends on the skin’s functional condition. The current research objective was to develop a methodology and electrodes to assess the passage of the chemical and biologically active compounds of curative mud through human skin by performing electrical bioimpedance (EBI) analysis. Methods: The methodology included local area mud pack and simultaneous tap water compress application on the forearms with the comparison to the measurements of the dry skin. A custom-designed small-area gold-plated electrode on a rigid printed circuit board, in a tetrapolar configuration, was designed. A pilot study experiment with ten volunteers was performed. Results: Our results indicated the presence of an effect of pelotherapy, manifested by the varying electrical properties of the skin. Distinguishable difference in the measured real part of impedance (R) emerged, showing a very strong correlation between the dry and tap-water-treated skin (r = 0.941), while a poor correlation between the dry and mud-pack-treated skin (r = 0.166) appeared. The findings emerged exclusively in the frequency interval of 10 kHz …1 MHz and only for R. Conclusions: EBI provides a promising tool for monitoring the variations in the electrical properties of the skin, including the skin barrier. We foresee developing smart devices for promoting the exploitation of spa therapies.

Background: Cardiovascular diseases (CVDs), being the culprit for one-third of deaths globally, constitute a challenge for biomedical instrumentation development, especially for early disease detection. Pulsating arterial blood flow, providing access to cardiac-related parameters, involves the whole body. Unobtrusive and continuous acquisition of electrical bioimpedance (EBI) and photoplethysmography (PPG) constitute important techniques for monitoring the peripheral arteries, requiring novel approaches and clever means. Methods: In this work, five peripheral arteries were selected for EBI and PPG signal acquisition. The acquisition sites were evaluated based on the signal morphological parameters. A small-data-based deep learning model, which increases the data by dividing them into cardiac periods, was proposed to evaluate the continuity of the signals. Results: The highest sensitivity of EBI was gained for the carotid artery (0.86%), three times higher than that for the next best, the posterior tibial artery (0.27%). The excitation signal parameters affect the measured EBI, confirming the suitability of classical 100 kHz frequency (average probability of 52.35%). The continuity evaluation of the EBI signals confirmed the advantage of the carotid artery (59.4%), while the posterior tibial artery (49.26%) surpasses the radial artery (48.17%). The PPG signal, conversely, commends the location of the posterior tibial artery (97.87%). Conclusions: The peripheral arteries are highly suitable for non-invasive EBI and PPG signal acquisition. The posterior tibial artery constitutes a candidate for the joint acquisition of EBI and PPG signals in sensor-fusion-based wearable devices—an important finding of this research.

A test and evaluation platform has been developed to research and develop solutions and algorithms for joint acquisition, processing, and reasoning from the electrical bioimpedance, electro-cardiography, and photoplethysmography (EBI, ECG, and PPG) signals. The solution is based on the low-cost Launchpad of the Texas Instrument TMS320F28379D dual core 16/32-bit DSP with 16-bit multichannel ADC and several other peripherals (PWM, ADC, timers, I2C, SPI, a lot of SRAM and flash memory). In the simplest mode, the platform is used to simultaneously acquire the EBI, ECG, and PPG signals at 1 kHz and send them to the PC by virtual COMport, for further analysis and presentation. The EBI, ECG, and PPG signals are sampled with a 16-bit ADC and have a resolution of more than four decimal digits, with an EBI error of less than 0.002%. In the next stage, various embedded and ”at the edge” measurement algorithms will be developed, tested, demonstrated, and evaluated on this platform.