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Background Pulse wave velocity (PWV) is a marker of arterial stiffness and local measurements could facilitate its widescale clinical use. However, confluence of incident and early reflected waves leads to biased spatiotemporal PWV estimates. Objective We introduce the Double Gaussian Propagation Model (DGPM) to measure local PWV in consideration of wave confluence (PWV$_{\sf DGPM}$) and compare it against conventional spatiotemporal PWV (PWV$_{\sf ST}$), with Bramwell-Hill PWV (PWV$_{\sf BH}$) and blood pressure (BP) as reference measures. Methods Ten subjects ranging from normotension to hypertension were repeatedly measured at rest and with induced PWV changes. Carotid distension waveforms over a 19 mm wide segment were acquired from ultrasonography, simultaneously with noninvasive continuous BP. Per cardiac cycle, the 8-parameter DGPM (amplitude, centroid, width, and velocity, respectively of forward and backward propagating wave) was fitted to the distension waveforms’ systolic foot and dicrotic notch complexes. Corresponding PWV$_{\sf ST}$ was computed from linear fittings of respective feature timings and distances. Regression analyses were conducted with PWV$_{\sf DGPM}$ and PWV$_{\sf ST}$ as predictors, and various PWV and BP measures as response variables. Results Whereas PWV$_{\sf ST}$ correlations were insignificant, PWV$_{\sf DGPM}$ estimated the reference PWV$_{\sf BH}$ with a significant reduction in errors (P < 0.001), explained up to 65% PWV$_{\sf BH}$ variability at rest, demonstrated higher intra-method consistency and correlated significantly with all BP measures (P < 0.001). Conclusion The proposed DGPM measures local carotid PWV in consideration of wave confluence, showing significant correlations with Bramwell-Hill PWV and BP at two distinct waveform complexes. Thereby PWV$_{\sf DGPM}$ outperforms the conventional PWV$_{\sf ST}$ in all investigated respects, potentially enabling PWV assessment in routine clinical practice.

This paper presents a high-speed readout interface suitable for nanopore-FET (NPFET) sensor arrays, which are being explored for high-throughput DNA or protein sequencing applications. The readout interface utilises a novel architecture that can simultaneously perform recording and automatic background calibration to compensate for offset and drift of the individual NPFET threshold voltages, eliminating the need for a separate calibration step or an area-consuming DAC. A prototype readout IC has been manufactured in 0.18- $\mu \text{m}$ CMOS to validate the circuit concepts. It features 32 NPFET interface circuits multiplexed to 8 parallel analog outputs. Each individual channel achieves a bandwidth of 10 MHz. The prototype IC has been characterised experimentally, and the online calibration capability has been validated with liquid-gated FETs in a microfluidics setup.

In this paper, a computational performance analysis is presented of a wide-field time-gated fluorescence lifetime imaging microscope (FLIM) using practically realizable properties of the laser, sample, and a three-tap time-gated CMOS image sensor. The impact of these component-level properties on the accuracy and the precision of the measurement results are estimated and discussed based on Monte Carlo simulations. The correlation between the detector speed and the accuracy of the extracted fluorescence lifetime is studied, and the minimum required incident photoelectron number of each pixel is estimated for different detector speeds and different fluorescence lifetime measurements. In addition, the detection limits due to the dark current and the parasitic light sensitivity of the detector are also investigated. This work gives an overview of the required fluorescence emission condition as well as the required detector properties for a three-tap time-gated image sensor to achieve good FLIM data in biological applications.

Thin-film interference filters can be illuminated by a circular aperture at different angles. Each situation produces a different transmittance spectrum. We present an analytical model that, for small tilt angles, predicts the change in transmittance for an arbitrary position of the filter in three-dimensional space. The model is extended to take into account higher-order harmonics. We also derive a formula to predict the change in central wavelength, and we validate our results by comparison with thin-film transfer-matrix calculations. A key property of our approach is that the model can be combined with empirical data to predict the transmittance without knowing the filter design.

Spectral cameras with integrated thin-film Fabry–Perot filters enable many different applications. Some applications require the detection of spectral features that are only visible at specific wavelengths, and some need to quantify small spectral differences that are undetectable with RGB color cameras. One factor that influences the central wavelength of thin-film filters is the angle of incidence. Therefore, when light is focused from an imaging lens onto the filter array, undesirable shifts in the measured spectra are observed. These shifts limit the use of the sensor in applications that require fast lenses or lenses with large chief ray angles. To increase flexibility and enable new applications, we derive an analytical model that explains and can correct the observed shifts in measured spectra. The model includes the size of the aperture and physical position of each filter on the sensor. We experimentally validate the model with two spectral cameras: one in the visible and near-infrared region and one in the short wave infrared region.

This paper presents a low power reconfigurable IC for wearable health devices that perform bio-impedance (BioZ) spectroscopy, respiration, and ECG signals measurement. The IC consists of a broadband excitation current source (I-DAC) and a power efficient readout circuit (RO). Both are highly scalable to mitigate the tradeoff among noise, dynamic range, speed, power, and safe current limits. On circuit level, the I-DAC supports two broadband excitation modes based on maximum length sequence (MLS), a flexible selection of frequency points, bandwidth, and current magnitude. The RO employs a low noise instrumentation amplifier and a reconfigurable 8-to-12 bit ADC for flexible sensitivity, dynamic range and speed with an automatic scaling of the power consumption. On system level, calibration of the entire circuit chain, oversampling and MLS averaging further improve the bandwidth, accuracy and sensitivity of BioZ spectroscopy beyond the intrinsic circuit performance. As a result, the BioZ sensor IC achieves 2 $\text{m}\Omega $ sensitivity within 3.3 $\text{m}\Omega $ – $100~\Omega $ range and $0.6~\Omega $ sensitivity within $3.3~\Omega $ –100 $\text{k}\Omega $ range. The BioZ spectroscopy spans up to 125 kHz while consuming $155~\mu \text{W}$ . Furthermore, this IC can measure respiration and ECG simultaneously at a lower sampling rate of 20 kS/s while consuming $31~\mu \text{W}$ . Compared to prior art, to the best of our knowledge, this IC is the only work that can measure BioZ and ECG simultaneously with a single readout channel while consuming the lowest power and offering the highest flexibility in performance, application range, and power consumption.

Unobtrusive measurement of vital signs is a research topic of increasing interest, both due to the advances in different technologies and the need for a more patient-centered healthcare. A limitation of such measurements is their sensitivity to motion artifacts, which challenges their use in daily life activities. In this paper, a novel system for the simultaneous acquisition of multichannel capacitively coupled ECG (ccECG) and radar signals is presented, which allows for respiration rate and heart rate (HR) extractions. Furthermore, a combination of signal quality and confidence indicators is proposed, which serves as a first step towards sensor fusion for an increased accuracy and time coverage of HR monitoring. After applying the proposed quality estimation algorithms, sensor fusion methods were performed including quality-based ccECG channel selection, confidence-based radar HR source selection, and Bayesian fusion. Both the system and the proposed algorithms were tested in a total of 125 min of measurements obtained from five different volunteers performing normal office work. An improvement in time coverage (defined as the time in which the HR error is lower than 3 bpm) from 2% to 32.5% was obtained for radar signals with the proposed confidence-based algorithm; the same metric for ccECG increased from 52.2% to 82.1% when automatically selecting the periods with the availability of good quality ccECG signals, while achieving 35.7% coverage in the remaining periods, by using one of the proposed Bayesian fusion methods; errors in each case were reduced accordingly, and a clear division of two sets of signals with different (increased) coverage levels was achieved.

Active electrodes (AEs), i.e., electrodes with built-in readout circuitry, are increasingly being implemented in wearable healthcare and lifestyle applications due to AEs' robustness to environmental interference. An AE locally amplifies and buffers μV-level EEG signals before driving any cabling. The low output impedance of an AE mitigates cable motion artifacts, thus enabling the use of high-impedance dry electrodes for greater user comfort. However, developing a wearable EEG system, with medical grade signal quality on noise, electrode offset tolerance, common-mode rejection ratio, input impedance, and power dissipation, remains a challenging task. This paper reviews state-of-the-art bio-amplifier architectures and low-power analog circuits design techniques intended for wearable EEG acquisition, with a special focus on an AE system interfaced with dry electrodes.

As known, wireless sensing applications can be enabled by using ultra-low-power electronics for sensing, processing and transmitting information, in order to extend the battery lifetime. Battery size is also a limiting factor constrained by the application requirements. In this scenario, energy harvesting is a fascinating solution, which can attenuate the trade-off between battery size, power consumption of the load circuits and battery lifetime. In some particular applications, characterized by long times in which no energy is available in any form, the battery could completely deplete because of the standby current of the load circuits. For that reason, battery-less applications become more and more relevant. In this paper the available circuit techniques for interfacing vibrational energy harvesters are presented and compared.

Wet gel electrodes are widely used for ECG/EEG monitoring, their low impedance results in high-quality signals. But they have important drawbacks too, such as time-consuming electrode set-up for EEG followed by a painful removal, skin irritation by the gel and signal degradation due to gel drying. Hence various dry electrode types are investigated, such as hard metal electrodes with low impedance but limited patient comfort/safety. We focus on flexible conductive polymer-based electrodes to combine low impedance, user comfort and safety. The composition of the conductive polymers is optimized to improve various properties such as conductivity, which directly affects signal quality and sensitivity to motion artifacts, and mechanical properties of the electrodes, important with respect to patient comfort. Electrode impedance and ECG/EEG signal recordings are evaluated using various polymer compositions and compared to wet gel electrode results. Additive optimization to improve processability of the conductive formulations is performed by dedicated flow studies, and will result in a high electrode fabrication yield. Very promising results are obtained regarding impedance, EEG/ECG signal quality and user comfort.

We present a new approach for the fabrication and integration of vertically aligned forests of amorphous carbon nanowires (CNWs), using only standard lithography, oxygen plasma treatment, and thermal processing. The simplicity and scalability of this process, as well as the hierarchical organization of CNWs, provides a potential alternative to the use of carbon nanotubes and graphene for applications in microsystems and high surface area materials. The CNWs are highly branched at the nanoscale, and novel hierarchical microstructures with CNWs connected to a solid amorphous core are made by controlling the plasma treatment time. By multilayer processing we demonstrate deterministic joining of CNW micropillars into 3D sensing networks. Finally we show that these networks can be chemically functionalized and used for measurement of DNA binding with increased sensitivity.

As known, wireless sensing applications can be enabled by using ultra-low-power electronics for sensing, processing and transmitting information, in order to extend the battery lifetime. Battery size is also a limiting factor constrained by the application requirements. In this scenario, energy harvesting is a fascinating solution, which can attenuate the trade-off between battery size, power consumption of the load circuits and battery lifetime. In some particular applications, characterized by long times in which no energy is available in any form, the battery could completely deplete because of the standby current of the load circuits. For that reason, battery-less applications become more and more relevant. In this paper the available circuit techniques for interfacing vibrational energy harvesters are presented and compared.

Wet gel electrodes are widely used for ECG/EEG monitoring, their low impedance results in high-quality signals. But they have important drawbacks too, such as time-consuming electrode set-up for EEG followed by a painful removal, skin irritation by the gel and signal degradation due to gel drying. Hence various dry electrode types are investigated, such as hard metal electrodes with low impedance but limited patient comfort/safety. We focus on flexible conductive polymer-based electrodes to combine low impedance, user comfort and safety. The composition of the conductive polymers is optimized to improve various properties such as conductivity, which directly affects signal quality and sensitivity to motion artifacts, and mechanical properties of the electrodes, important with respect to patient comfort. Electrode impedance and ECG/EEG signal recordings are evaluated using various polymer compositions and compared to wet gel electrode results. Additive optimization to improve processability of the conductive formulations is performed by dedicated flow studies, and will result in a high electrode fabrication yield. Very promising results are obtained regarding impedance, EEG/ECG signal quality and user comfort.

The filling of microvias with diameters between 30 and 100 µm and aspect ratios up to 2.5 in silicon wafers, was investigated to determine the performance of copper electroplating. An electrolyte with a low leveler concentration was only suitable for filling microvias with aspect ratios below 1. An increase of the leveler concentration enabled the filling of microvias with higher aspect ratios. The fill-up evolution shows a bottom-up plating behavior. Electrochemical measurements show that for conditions prevailing at the bottom of the via, the electrodeposition rate is enhanced while for conditions prevailing at the top, it is inhibited. This difference originates from a concentration gradient of leveler inside the via and different convection conditions inside and outside the via.

A MEMS packaging technique based on porous alumina films is proposed. This method allows for low temperature, wafer level packaging of the devices. We report on initial experiments indicating the feasibility of the technique. Patterned porous alumina films are created by anodizing aluminum films on wafer substrates using shulphuric acid electrolytes. Etching of the barrier layer through the porous membrane by plasma with CF4+O2 gas and evidence of pore opening required for the release of a sacrificial MEMS layer are presented.