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.

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.

Several approaches can be used to find defects in metal surfaces. Eddy current testing is a simple and efficient method for non-destructive testing of metals, identifying alloys, measuring coating thickness, and detecting corrosion. Impedance spectroscopy enables depth profiling and high-speed measurements in real-time manufacturing. For example, in the wood processing industry, early detection of cracks in high-speed band saws is crucial. Electromagnetic testing, particularly eddy-current-based methods, is widely used. This paper reviews existing solutions and investigates cracked saw blade specimens using planar coils in the 100 kHz–10 MHz range. Results show that higher frequencies improve crack detection. Future research should focus on high-speed detection and machine vision-based solutions.

Using the pulse-width modulation (PWM) is a very convenient and efficient way to generate the approximation of the AC, in the simplest case sinewaves in th