The sections of pipe bends are hot spots for wall thinning due to accelerated corrosion by fluid flow. Conventionally, the thickness of a bend wall is evaluated by local point-by-point ultrasonic measurement, which is slow and costly. Guided wave tomography is an attractive method that enables the monitoring of a whole bend area by processing the waves excited and received by transducer arrays. The main challenge associated with the tomography of the bend is the development of an appropriate forward model, which should simply and efficiently handle the wave propagation in a complex bend model. In this study, we developed a two-dimensional (2D) acoustic forward model to replace the complex three-dimensional (3D) bend domain with a rectangular domain that is made artificially anisotropic by using Thomsen parameters. Thomsen parameters allow the consideration of the directional dependence of the velocity of the wave in the model. Good agreement was found between predictions and experiments performed on a 220 mm diameter (d) pipe with 1.5d bend radius, including the wave-field focusing effect and the steering effect of scattered wave-fields from defects.

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.

Extracting relevant information from impedance spectra is a big challenge if we consider different mechanisms, including cable and contacting effects, material properties and system instability. A particularly important prerequisite is that these effects depend differently on the frequency and that some measures can be taken to eliminate effects of irrelevant mechanisms. The common way in signal processing is to model the impedance spectrum by means of equivalent circuits and to extract the quantity of interest using optimization techniques. The more effects and mechanisms are represented in an impedance spectrum, the more unknown parameters are needed for accurate modelling. The parameter extraction process becomes thereby difficult to solve and needs a lot of trials and a priori knowledge. It is therefore important that mechanisms with minor influence are eliminated or neglected. Other possibilities for signal processing provide mathematical data fusion methods. Statistical methods like principal component analysis can be used for extracting specific information from the measured data. The paper considers different applications (electrochemical, biomedical, moisture analysis, battery diagnosing) of electrical impedance spectroscopy.

Background. Today, central aortic pressure (CAP) is measured through the invasive procedure of angiography. The only feasible alternative is applanation tonometry, requiring experienced staff to perform reliable measurements. The method of measuring the electrical bioimpedance (EBI) from the wrist gives promising results in estimating the CAP. However, the origin of the EBI data, its quality, and approaches to acquiring the signal are still vague. This study is aimed at determining the dependency of EBI of blood on the diameter, branching, and hindering the blood flow by squeezing the vessel. Methods. An on‐desk hydraulic and mechanical pipe system that imitates the arterial tree in the forearm with the modulated flow of saline solution to imitate the pulsating blood was constructed. The setup was verified in the simulation model. The flexible and rigid pipes were squeezed at selected locations of radial and ulnar arteries, and the superficial palmar arc and the pressure with impedance were measured. Results. The multifaceted effect of squeezing the selected locations of arteries in the forearm on the measured EBI and pressure was verified. The effect of arterial stiffening was verified, revealing a very strong inverse correlation of the time‐varying impedance (ΔZ(t)) of rigid pipe compared to the measured data of the wrist. Conclusion. To gain the highest magnitude of ΔZ(t), our research suggests applying pressure on the radial artery and measuring the EBI of the ulnar artery. Our results propose physiology‐based suggestions to increase the sensitivity of measured EBI of the pulse wave, constituting a base for designing novel wearable monitoring devices and algorithms for CAP estimation.

The monitoring of peripheral electrical bioimpedance (EBI) variations is a promising method that has the potential to replace invasive or burdensome techniques for cardiovascular measurements. Segmental or continuous recording of peripheral pulse waves can serve as a basis for calculating prognostic markers like pulse wave velocity (PWV) or include parameters such as pulse transit time (PTT) or pulse arrival time (PAT) for noninvasive blood pressure (BP) estimation, as well as potentially novel cardiovascular risk indicators. However, several technical, analytical, and interpretative aspects need to be resolved before the EBI method can be adopted in clinical practice. Our goal was to investigate and improve the application of EBI, executing its comparison with other cardiovascular assessment methods in patients hospitalized for coronary catheterization procedures. Methods: We analyzed data from 44 non-acute patients aged 45–74 years who were hospitalized for coronary catheterization at East Tallinn Central Hospital between 2020 and 2021. The radial EBI and electrocardiogram (ECG) were measured simultaneously with central and contralateral pressure curves. The Savitzky–Golay filter was used for signal smoothing. The Hankel matrix decomposer was applied for the extraction of cardiac waveforms from multi-component signals. After extracting the cardiac component, a period detection algorithm was applied to EBI and blood pressure curves. Results: Seven points of interest were detected on the pressure and EBI curves, and four with good representativeness were selected for further analysis. The Spearman correlation coefficient was low for all but the central and distal pressure curve systolic upstroke time points. A high positive correlation was found between PWV measured both invasively and with EBI. The median value of complimentary pulse wave velocity (CPWV), a parameter proposed in the paper, was significantly lower in patients with normal coronaries compared to patients with any stage of coronary disease. Conclusions: With regard to wearable devices, the EBI-derived PAT can serve as a substrate for PWV calculations and cardiovascular risk assessment, although these data require further confirmation.