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This article presents the development of a power loss emulation (PLE) system device to study and find ways of mitigating skin tissue heating effects in transcutaneous energy transmission systems (TETS) for existing and next generation left ventricular assist devices (LVADs). Skin thermal profile measurements were made using the PLE system prototype and also separately with a TETS in a porcine model. Subsequent data analysis and separate computer modelling studies permit understanding of the contribution of tissue blood perfusion towards cooling of the subcutaneous tissue around the electromagnetic coupling area. A 2-channel PLE system prototype and a 2-channel TETS prototype were implemented for this study. The heating effects resulting from power transmission inefficiency were investigated under varying conditions of power delivery levels for an implanted device. In the part of the study using the PLE setup, the implanted heating element was placed subcutaneously 6–8 mm below the body surface of in vivo porcine model skin. Two operating modes of transmission coupling power losses were emulated: (a) conventional continuous transmission, and (b) using our proposed pulsed transmission waveform protocols. Experimental skin tissue thermal profiles were studied for various levels of LVAD power. The heating coefficient was estimated from the porcine model measurements (an in vivo living model and a euthanised cadaver model without blood circulation at the end of the experiment). An in silico model to support data interpretation provided reliable experimental and numerical methods for effective wireless transdermal LVAD energization advanced solutions. In the separate second part of the study conducted with a separate set of pigs, a two-channel inductively coupled RF driving system implemented wireless power transfer (WPT) to a resistive LVAD model (50 Ω) to explore continuous versus pulsed RF transmission modes. The RF-transmission pulse duration ranged from 30 ms to 480 ms, and the idle time (no-transmission) from 5 s to 120 s. The results revealed that blood perfusion plays an important cooling role in reducing thermal tissue damage from TETS applications. In addition, the results analysis of the in vivo, cadaver (R1Sp2) model, and in silico studies confirmed that the tissue heating effect was significantly lower in the living model versus the cadaver model due to the presence of blood perfusion cooling effects.

Sudden cardiac death (SCD) risk can be reduced by early detection of short-lived and transient cardiac arrhythmias using long-term electrocardiographic (ECG) monitoring. Early detection of ventricular arrhythmias can reduce the risk of SCD by allowing appropriate interventions. Long-term continuous ECG monitoring, using a non-invasive armband-based wearable device is an appealing solution for detecting early heart rhythm abnormalities. However, there is a paucity of understanding on the number and best bipolar ECG electrode pairs axial orientation around the left mid-upper arm circumference (MUAC) for such devices. This study addresses the question on the best axial orientation of ECG bipolar electrode pairs around the left MUAC in non-invasive armband-based wearable devices, for the early detection of heart rhythm abnormalities. A total of 18 subjects with almost same BMI values in the WASTCArD arm-ECG database were selected to assess arm-ECG bipolar leads quality using proposed metrics of relative (normalized) signal strength measurement, arm-ECG detection performance of the main ECG waveform event component (QRS) and heart-rate variability (HRV) in six derived bipolar arm ECG-lead sensor pairs around the armband circumference, having regularly spaced axis angles (at 30° steps) orientation. The analysis revealed that the angular range from −30° to +30°of arm-lead sensors pair axis orientation around the arm, including the 0° axis (which is co-planar to chest plane), provided the best orientation on the arm for reasonably good QRS detection; presenting the highest sensitivity (Se) median value of 93.3%, precision PPV median value at 99.6%; HRV RMS correlation (p) of 0.97 and coefficient of determination (R2) of 0.95 with HRV gold standard values measured in the standard Lead-I ECG.

This study aimed to develop a novel Transdermal Energy Transmission System (TETS) device that addresses the driveline complications faced by patients with advanced heart failure (HF). Our TETS device utilizes a two-channel configuration with a very-low duty cycle and a pulsed RF power transmission technique, along with elliptically shaped flexible coil inductive coupling elements. We integrated a battery charging controller module into the TETS, enabling it to recharge an implanted Lithium-Ion (Li-Ion) battery that powers low-power-rated Circulatory Assist Devices, or left ventricular assist devices (LVADs). Benchtop measurements demonstrated that the TETS delivered energy from the implanted coils to the battery charging module, at a charging rate of up to 2900 J/h, presented an average temperature increase (ΔT) of 3 °C. We conducted in vivo measurements using four porcine models followed by histopathological analysis of the skin tissue in the implanted coils areas. The thermal profile analysis from the in vivo measurements and the calculated charging rates from the current and voltage waveforms, in porcine models, indicated that the charging rate and temperature varied for each model. The maximum energy charging rate observed was 2200 J/h, with an average ΔT of 3 °C. The exposed skin tissue histopathological analysis results showed no evidence of tissue thermal damage in the in vivo measurements. These results demonstrate the feasibility of our developed TETS device for wireless driving implanted low-power-rated LVADs and Li-Ion charging.

Impedance cardiography (ICG) is a low-cost, non-invasive technique that enables the clinical assessment of haemodynamic parameters, such as cardiac output and stroke volume (SV). Conventional ICG recordings are taken from the patient’s thorax. However, access to ICG vital signs from the upper-arm brachial artery (as an associated surrogate) can enable user-convenient wearable armband sensor devices to provide an attractive option for gathering ICG trend-based indicators of general health, which offers particular advantages in ambulatory long-term monitoring settings. This study considered the upper arm ICG and control Thorax-ICG recordings data from 15 healthy subject cases. A prefiltering stage included a third-order Savitzky–Golay finite impulse response (FIR) filter, which was applied to the raw ICG signals. Then, a multi-stage wavelet-based denoising strategy on a beat-by-beat (BbyB) basis, which was supported by a recursive signal-averaging optimal thresholding adaptation algorithm for Arm-ICG signals, was investigated for robust signal quality enhancement. The performance of the BbyB ICG denoising was evaluated for each case using a 700 ms frame centred on the heartbeat ICG pulse. This frame was extracted from a 600-beat ensemble signal-averaged ICG and was used as the noiseless signal reference vector (gold standard frame). Furthermore, in each subject case, enhanced Arm-ICG and Thorax-ICG above a threshold of correlation of 0.95 with the noiseless vector enabled the analysis of beat inclusion rate (BIR%), yielding an average of 80.9% for Arm-ICG and 100% for Thorax-ICG, and BbyB values of the ICG waveform feature metrics A, B, C and VET accuracy and precision, yielding respective error rates (ER%) of 0.83%, 11.1%, 3.99% and 5.2% for Arm-IG, and 0.41%, 3.82%, 1.66% and 1.25% for Thorax-ICG, respectively. Hence, the functional relationship between ICG metrics within and between the arm and thorax recording modes could be characterised and the linear regression (Arm-ICG vs. Thorax-ICG) trends could be analysed. Overall, it was found in this study that recursive averaging, set with a 36 ICG beats buffer size, was the best Arm-ICG BbyB denoising process, with an average of less than 3.3% in the Arm-ICG time metrics error rate. It was also found that the arm SV versus thorax SV had a linear regression coefficient of determination (R2) of 0.84.

Global trade and globalization have driven growth and diversification in the horticultural industry. Fresh grapes, a key product, face challenges of market volatility, trade barriers, and logistics. Market diversification is essential for stability and competitiveness in international trade. This research focused on analyzing market diversification in Peru’s fresh grape exports during the 2013–2022 period, exploring its implications for international trade. A quantitative methodology was used, along with the analysis of publicly recorded data on the website of the National Superintendence of Customs and Tax Administration, specifically exports from companies shipping under the national subheading for Grapes (0806.10.00.00). Diversification was analyzed using the Herfindahl–Hirschman concentration index (HHI), and competitiveness through the Balassa index. The main findings were that between 2013 and 2022, Peruvian grape exports grew in value (CAGR of 12.02%) and volume (CAGR of 12.13%). The sector expanded with an average of 151.2 companies and 59.1 destination markets. Diversification varied: the USA (12.4%), the Netherlands (1.6%), Hong Kong (4.2%), and Mexico (63.2%). The Herfindahl–Hirschman index showed concentration in the USA (4533 in 2020, 4519 in 2022) and stability in companies (2318 in 2014, 2450 in 2022). Finally, it is recommended to strengthen the Peruvian viticultural sector by maintaining geographic diversification through policies seeking new markets, monitoring global trends, constantly analyzing market concentration, and promoting fair competition among participating companies, allowing new ones to enter this sector.

Abnormal heart rhythms (arrhythmias) are a major cause of cardiovascular disease and death in Europe. Sudden cardiac death accounts for 50% of cardiac mortality in developed countries; ventricular tachycardia or ventricular fibrillation is the most common underlying arrhythmia. In the ambulatory population, atrial fibrillation is the most common arrhythmia and is associated with an increased risk of stroke and heart failure, particularly in an aging population. Early detection of arrhythmias allows appropriate intervention, reducing disability and death. However, in the early stages of disease arrhythmias may be transient, lasting only a few seconds, and are thus difficult to detect. This work addresses the problem of extracting the far-field heart electrogram signal from noise components, as recorded in bipolar leads along the left arm, using a data driven ECG (electrocardiogram) denoising algorithm based on ensemble empirical mode decomposition (EEMD) methods to enable continuous non-invasive monitoring of heart rhythm for long periods of time using a wrist or arm wearable device with advanced biopotential sensors. Performance assessment against a control denoising method of signal averaging (SA) was implemented in a pilot study with 34 clinical cases. EEMD was found to be a reliable, low latency, data-driven denoising technique with respect to the control SA method, achieving signal-to-noise ratio (SNR) enhancement to a standard closer to the SA control method, particularly on the upper arm-ECG bipolar leads. Furthermore, the SNR performance of the EEMD was improved when assisted with an FFT (fast Fourier transform ) thresholding algorithm (EEMD-fft).

A wireless powered implantable atrial defibrillator consisting of a battery driven hand-held radio frequency (RF) power transmitter (ex vivo) and a passive (battery free) implantable power receiver (in vivo) that enables measurement of the intracardiac impedance (ICI) during internal atrial defibrillation is reported. The architecture is designed to operate in two modes: Cardiac sense mode (power-up, measure the impedance of the cardiac substrate and communicate data to the ex vivo power transmitter) and cardiac shock mode (delivery of a synchronised very low tilt rectilinear electrical shock waveform). An initial prototype was implemented and tested. In low-power (sense) mode, >5 W was delivered across a 2.5 cm air-skin gap to facilitate measurement of the impedance of the cardiac substrate. In high-power (shock) mode, >180 W (delivered as a 12 ms monophasic very-low-tilt-rectilinear (M-VLTR) or as a 12 ms biphasic very-low-tilt-rectilinear (B-VLTR) chronosymmetric (6ms/6ms) amplitude asymmetric (negative phase at 50% magnitude) shock was reliably and repeatedly delivered across the same interface; with >47% DC-to-DC (direct current to direct current) power transfer efficiency at a switching frequency of 185 kHz achieved. In an initial trial of the RF architecture developed, 30 patients with AF were randomised to therapy with an RF generated M-VLTR or B-VLTR shock using a step-up voltage protocol (50–300 V). Mean energy for successful cardioversion was 8.51 J ± 3.16 J. Subsequent analysis revealed that all patients who cardioverted exhibited a significant decrease in ICI between the first and third shocks (5.00 Ω (SD(σ) = 1.62 Ω), p < 0.01) while spectral analysis across frequency also revealed a significant variation in the impedance-amplitude-spectrum-area (IAMSA) within the same patient group (|∆(IAMSAS1-IAMSAS3)[1 Hz − 20 kHz] = 20.82 Ω-Hz (SD(σ) = 10.77 Ω-Hz), p < 0.01); both trends being absent in all patients that failed to cardiovert. Efficient transcutaneous power transfer and sensing of ICI during cardioversion are evidenced as key to the advancement of low-energy atrial defibrillation.

This article presents the devising, development, prototyping and assessment of a wearable arm-ECG sensor system (WAMECG1) for long-term non-invasive heart rhythm monitoring, and functionalities for acquiring, storing, visualizing and transmitting high-quality far-field electrocardiographic signals. The system integrates the main building blocks present in a typical ECG monitoring device such as the skin surface electrodes, front-end amplifiers, analog and digital signal conditioning filters, flash memory and wireless communication capability. These are integrated into a comfortable, easy to wear, and ergonomically designed arm-band ECG sensor system which can acquire a bipolar ECG signal from the upper arm of the user over a period of 72 h. The small-amplitude bipolar arm-ECG signal is sensed by a reusable, long-lasting, Ag–AgCl based dry electrode pair, then digitized using a programmable sampling rate in the range of 125 to 500 Hz and transmitted via Wi-Fi. The prototype comparative performance assessment results showed a cross-correlation value of 99.7% and an error of less than 0.75% when compared to a reference high-resolution medical-grade ECG system. Also, the quality of the recorded far-field bipolar arm-ECG signal was validated in a pilot trial with volunteer subjects from within the research team, by wearing the prototype device while: (a) resting in a chair; and (b) doing minor physical activities. The R-peak detection average sensibilities were 99.66% and 94.64%, while the positive predictive values achieved 99.1% and 92.68%, respectively. Without using any additional algorithm for signal enhancement, the average signal-to-noise ratio (SNR) values were 21.71 and 18.25 for physical activity conditions (a) and (b) respectively. Therefore, the performance assessment results suggest that the wearable arm-band prototype device is a suitable, self-contained, unobtrusive platform for comfortable cardiac electrical activity and heart rhythm logging and monitoring.

Empirical mode decomposition is used as a low latency method of recovering the cardiac ventricular activity QRS biopotential signals recorded from the upper arm. The recovery technique is tested and compared with the industry accepted technique of signal averaging using a database of “normal” rhythm traces from bipolar ECG leads along the left arm, recorded from patient volunteers at a cardiology day procedure clinic. The same partial recomposition technique is applied to recordings taken using an innovative dry electrode technology supplied by Plessey Semiconductors. In each case, signal to noise ratio (SNR) is used as a metric for comparison.

Today’s economical cycles challenge the test program generation process for semiconductors with regard to productivity, time-to-market, increasing quality requirements and manufacturing robustness, while, at the same time, the complexity of the system-on-a-chip mixed-signal integrated circuits to be tested increases significantly. Furthermore, commercial challenges in combination with competitive advantage become an important factor, not only within semiconductor manufacturing, but also within test program development. This paper provides a review of these challenges, and how they might be addressed. We first give a short introduction and background on semiconductor testing and test development with the focus on mixed-signal and systems-on-chip. This is followed by current roadmaps and considerations for test program software development. Based on the highlighted strength and weaknesses of the reviewed approaches, the authors conclude with some recommendations to address these challenges by adopting software engineering methods for the test program development process.