Search Results (14)

Cardiovascular diseases remain one of the leading causes of mortality worldwide, highlighting the importance of effective monitoring and early diagnosis. While electrocardiography (ECG) is the standard technique for evaluating the heart’s electrical activity and detecting rhythm and conduction abnormalities, it alone is insufficient for identifying certain conditions, such as valvular disorders. Phonocardiography (PCG) allows the recording and analysis of heart sounds and improves the diagnostic accuracy when combined with ECG. In this study, ECG and PCG signals were simultaneously acquired from a resting adult subject using a compact system comprising an analog front-end (model AD8232, manufactured by Analog Devices, Wilmington, MA, USA) for ECG acquisition and a digital stethoscope built around a condenser electret microphone (model HM-9250, manufactured by HMYL, Anqing, China). Both the ECG electrodes and the microphone were positioned on the chest to ensure the spatial alignment of the signals. An adaptive segmentation algorithm was developed to segment PCG and ECG signals based on their morphological and temporal features. This algorithm identifies the onset and peaks of S1 and S2 heart sounds in the PCG and the Q, R, and S waves in the ECG, enabling the extraction of the systolic time intervals such as EMAT, PEP, LVET, and LVST parameters proven useful in the diagnosis and monitoring of cardiovascular diseases. Based on the segmented signals, the measured averages (EMAT = 74.35 ms, PEP = 89.00 ms, LVET = 244.39 ms, LVST = 258.60 ms) were consistent with the reference standards, demonstrating the reliability of the developed method. The proposed algorithm was validated on synchronized ECG and PCG signals from multiple subjects in an open-source dataset (BSSLAB Localized ECG Data). The systolic intervals extracted using the proposed method closely matched the literature values, confirming the robustness across different recording conditions; in detail, the mean Q–S1 interval was 40.45 ms (≈45 ms reference value, mean difference: −4.85 ms, LoA: −3.42 ms and −6.09 ms) and the R–S1 interval was 14.09 ms (≈15 ms reference value, mean difference: −1.2 ms, LoA: −0.55 ms and −1.85 ms). In conclusion, the results demonstrate the potential of the joint ECG and PCG analysis to improve the long-term monitoring of cardiovascular diseases. Full article

Semiconductor detectors for high-energy sensing ($X/\gamma$-rays) play a critical role in fields such as astronomy, particle physics, spectroscopy, medical imaging, and homeland security. The increasing need for precise detector characterization highlights the importance of developing advanced digital twins, which help optimize the design and performance of imaging systems. Current simulation frameworks primarily focus on modeling electron–hole pair dynamics within the semiconductor bulk after the photon absorption, leading to the current signals at the nearby electrodes. However, most simulations neglect charge diffusion and Coulomb repulsion, which spatially expand the charge cloud during propagation due to the high complexity they add to the physical models. Although these effects are relatively weak, their inclusion is essential for achieving a high-fidelity replication of real detector behavior. There are some existing methods that successfully incorporate these two phenomena with minimal computational cost, including those developed by Gatti in 1987 and by Benoit and Hamel in 2009. The present work evaluates these two approaches and proposes a novel Monte Carlo technique that offers higher accuracy in exchange for increased computational time. Our new method enables more realistic performance predictions while remaining within practical computational limits. Full article

The complexity of information processing in the brain requires the development of technologies that can provide spatial and temporal resolution by means of dense electrode arrays paired with high-channel-count signal acquisition electronics. In this work, we present an ultra-low noise modular 512-channel neural recording circuit that is scalable to up to 4096 simultaneously recording channels. The neural readout application-specific integrated circuit (ASIC) uses a dense 8.2 mm × 6.8 mm 2D layout to enable high-channel count, creating an ultra-light 350 mg flexible module. The module can be deployed on headstages for small animals like rodents and songbirds, and it can be integrated with a variety of electrode arrays. The chip was fabricated in a TSMC 0.18 µm 1.8 V CMOS technology and dissipates a total of 125 mW. Each DC-coupled channel features a gain and bandwidth programmable analog front-end along with 14 b analog-to-digital conversion at speeds up to 30 kS/s. Additionally, each front-end includes programmable electrode plating and electrode impedance measurement capability. We present both standalone and in vivo measurements results, demonstrating the readout of spikes and field potentials that are modulated by a sensory input. Full article

The objective of this systematic review centers on cognitive assessment based on electroencephalography (EEG) analysis in Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) environments, projected on Head Mounted Displays (HMD), in healthy individuals. A range of electronic databases were searched (Scopus, ScienceDirect, IEEE Explore and PubMed), using PRISMA research method and 82 experimental studies were included in the final report. Specific aspects of cognitive function were evaluated, including cognitive load, immersion, spatial awareness, interaction with the digital environment and attention. These were analyzed based on various aspects of the analysis, including the number of participants, stimuli, frequency bands range, data preprocessing and data analysis. Based on the analysis conducted, significant findings have emerged both in terms of the experimental structure related to cognitive neuroscience and the key parameters considered in the research. Also, numerous significant avenues and domains requiring more extensive exploration have been identified within neuroscience and cognition research in digital environments. These encompass factors such as the experimental setup, including issues like narrow participant populations and the feasibility of using EEG equipment with a limited number of sensors to overcome the challenges posed by the time-consuming placement of a multi-electrode EEG cap. There is a clear need for more in-depth exploration in signal analysis, especially concerning the α, β, and γ sub-bands and their role in providing more precise insights for evaluating cognitive states. Finally, further research into augmented and mixed reality environments will enable the extraction of more accurate conclusions regarding their utility in cognitive neuroscience. Full article

In recent years, limited works on EOG (electrooculography)-based biometric authentication systems have been carried out with eye movements or eye blinking activities in the current literature. EOGs have permanent and unique traits that can separate one individual from another. In this work, we have investigated FSST (Fourier Synchrosqueezing Transform)-ICA (Independent Component Analysis)-EMD (Empirical Mode Decomposition) robust framework-based EOG-biometric authentication (one-versus-others verification) performances using ensembled RNN (Recurrent Neural Network) deep models voluntary eye blinkings movements. FSST is implemented to provide accurate and dense temporal-spatial properties of EOGs on the state-of-the-art time-frequency matrix. ICA is a powerful statistical tool to decompose multiple recording electrodes. Finally, EMD is deployed to isolate EOG signals from the EEGs collected from the scalp. As our best knowledge, this is the first research attempt to explore the success of the FSST-ICA-EMD framework on EOG-biometric authentication generated via voluntary eye blinking activities in the limited EOG-related biometric literature. According to the promising results, improved and high recognition accuracies (ACC/Accuracy: ≥99.99% and AUC/Area under the Curve: 0.99) have been achieved in addition to the high TAR (true acceptance rate) scores (≥98%) and low FAR (false acceptance rate) scores (≤3.33%) in seven individuals. On the other hand, authentication and monitoring for online users/students are becoming essential and important tasks due to the increase of the digital world (e-learning, e-banking, or e-government systems) and the COVID-19 pandemic. Especially in order to ensure reliable access, a highly scalable and affordable approach for authenticating the examinee without cheating or monitoring high-data-size video streaming is required in e-learning platforms and online education strategies. Hence, this work may present an approach that offers a sustainable, continuous, and reliable EOG-biometric authentication of digital applications, including e-learning platforms for users/students. Full article

The fabrication of thin-film electrodes, which contain metal nanoparticles and nanostructures for applications in electrochemical sensing as well as energy conversion and storage, is often based on multi-step procedures that include two main passages: (i) the synthesis and purification of nanomaterials and (ii) the fabrication of thin films by coating electrode supports with these nanomaterials. The patterning and miniaturization of thin film electrodes generally require masks or advanced patterning instrumentation. In recent years, various approaches have been presented to integrate the spatially resolved deposition of metal precursor solutions and the rapid conversion of the precursors into metal nanoparticles. To achieve the latter, high intensity light irradiation has, in particular, become suitable as it enables the photochemical, photocatalytical, and photothermal conversion of the precursors during or slightly after the precursor deposition. The conversion of the metal precursors directly on the target substrates can make the use of capping and stabilizing agents obsolete. This review focuses on hybrid platforms that comprise digital metal precursor ink printing and high intensity light irradiation for inducing metal precursor conversions into patterned metal and alloy nanoparticles. The combination of the two methods has recently been named Print-Light-Synthesis by a group of collaborators and is characterized by its sustainability in terms of low material consumption, low material waste, and reduced synthesis steps. It provides high control of precursor loading and light irradiation, both affecting and improving the fabrication of thin film electrodes. Full article

The microstructures of porous electrodes in lithium-ion cells strongly affect their electrochemical performance. Experimental tomography techniques to investigate the microstructure during electrode development is costly and time consuming. To address this issue, a numerical method is presented to create a digital morphology to realize a realistic microstructure. In this study, the spherical harmonics in a straightforward mathematical approach are proposed to develop the virtual 3D morphology of the electrode’s heterogeneous structure. The introduced method offers a numerically light procedure which enables effective iterative virtual testing and optimization. The generated morphology model is parameterized to reproduce a NMC cathode microstructure observed in the literature. The electrode model allows evaluation of the spatially resolved geometric, transport and electric potential characteristics of the microstructure. The computed characteristics are employed to improve the parametrization of the continuum model as the most widely used physics-based model. For this purpose, the electrochemical impedance spectra of a lithium foil/separator/NMC half-cell is virtually modeled by heterogeneous and continuum approaches. Then, the modified continuum model is compared to the heterogeneous model as a benchmark, in terms of the kinetics and transport characteristics underlying the electrochemical impedance spectra. The modified continuum model shows an improved response in both frequency and time domains. Full article

Electrical capacitance tomography (ECT) is a technique of imaging the distribution of permittivity inside an object under test. Capacitance is measured between the electrodes surrounding the object, and the image is reconstructed from these data by solving the inverse problem. Although both sinusoidal excitation and pulse excitation are used in the sensing circuit, only the AC method is used to measure both components of complex capacitance. In this article, a novel method of complex capacitance measurement using pulse excitation is proposed for ECT. The real and imaginary components are calculated from digital samples of the integrator response. A pulse shape in the front-end circuit was analyzed using the Laplace transform. The numerical simulations of the electric field inside the imaging volume as well as simulations of a pulse excitation in the front-end circuit were performed. The calculation of real and imaginary components using digital samples of the output signal was verified. The permittivity and conductivity images reconstructed for the test object were presented. The method enables imaging of permittivity and conductivity spatial distributions using capacitively coupled electrodes and may be an alternative measurement method for ECT as well as for electrical impedance tomography. Full article

Food heating assisted by radio frequencies has been industrially applied to post-harvest treatment of grains, legumes and various kind of nuts, to tempering and thawing of meat and fish products and to post-baking of biscuits. The design of food processes based on the application of radiofrequencies was often based on rules of thumb, so much so that their intensification could lead significant improvements. One of the subjects under consideration is the shape of the food items that may influence their heating assisted by radiofrequency. In this work, a joint experimental and numerical study on the effects of the spatial configuration of a food sample (chicken meat shaped as a parallelepiped) on the heating pattern in a custom RF oven (40.68 MHz, 50 Ohm, 10 cm electrodes gap, 300 W) is presented. Minced chicken breast samples were shaped as cubes (4 × 4 × 4 cm³) to be organized in different loads and spatial configurations (horizontal or vertical arrays of 2 to 16 cubes). The samples were heated at two radiofrequency operative power levels (225 W and 300 W). Heating rate, temperature uniformity and heating efficiency were determined during each run. A digital twin of the experimental system and process was developed by building and numerically solving a 3D transient mathematical model, taking into account electromagnetic field distribution in air and samples and heat transfer in the food samples. Once validated, the digital tool was used to analyze the heating behavior of the samples, focusing on the most efficient configurations. Both experiments and simulations showed that, given a fixed gap between the electrodes (10 cm), the vertically oriented samples exhibited a larger heating efficiency with respect to the horizontally oriented ones, pointing out that the gap between the top electrode and the samples plays a major role in the heating efficiency. The efficiency was larger (double or even more; >40% vs. 10–15%) in thicker samples (built with two layers of cubes), closer to the top electrode, independently from nominal power. Nevertheless, temperature uniformity in vertical configurations was poorer (6–7 °C) than in horizontal ones (3 °C). Full article

Implantable neuromodulation devices typically have metal in contact with soft, ion-conducting nerves. These neural interfaces excite neurons using short-duration electrical pulses. While this approach has been extremely successful for multiple clinical applications, it is limited in delivering long-duration pulses or direct current (DC), even for acute term studies. When the charge injection capacity of electrodes is exceeded, irreversible electrochemical processes occur, and toxic byproducts are discharged directly onto the nerve, causing biological damage. Hydrogel coatings on electrodes improve the overall charge injection limit and provide a mechanically pliable interface. To further extend this idea, we developed a silicone-based nerve cuff lead with a hydrogel microfluidic conduit. It serves as a thin, soft and flexible interconnection and provides a greater spatial separation between metal electrodes and the target nerve. In an in vivo rat model, we used this cuff to stimulate and record from sciatic nerves, with performance comparable to that of metal electrodes. Further, we delivered DC through the lead in an acute manner to induce nerve block that is reversible. In contrast to most metallic cuff electrodes, which need microfabrication equipment, we built this cuff using a consumer-grade digital cutter and a simplified molding process. Overall, the device will be beneficial to neuromodulation researchers as a general-purpose nerve cuff electrode for peripheral neuromodulation experiments. Full article

This paper explores the effectiveness of the white, red, green, and blue light emitted diodes (LEDs) light sources to detect the third layer of the electrode pixel and the fourth layer of the via-hole passivation on thin-film transistors. The time-delay-integration charge-coupled device and a reflective spectrometer were implemented in this experiment. The optical conditions are the same, as each light source and the digital image’s binary method also recognize the sharpness and contrast in the task. Consequently, the white and the blue LED light sources can be candidates for the light source for the optical inspection, especially for monochromic blue LED’s outperformance among the light sources. The blue LED demonstrates the high spatial resolution and short wavelength’s greater energy to trigger the photosensor. Additionally, the metal material has shown a tremendous responsibility in the photosensor with 150 Dn/nj/cm² over the sensibility. The mercury ¹⁹⁸Hg-pencil discharge lamp emits the stable spectral wavelength to significantly calibrate the spectrometer’s measurement. Full article

Organic light-emitting field-effect transistors (LEFETs) provide the possibility of simplifying the display pixilation design as they integrate the drive-transistor and the light emission in a single architecture. However, in p-type LEFETs, simultaneously achieving higher external quantum efficiency (EQE) at higher brightness, larger and stable emission area, and high switching speed are the limiting factors for to realise their applications. Herein, we present a p-type polymer heterostructure-based LEFET architecture with electron and hole injection interlayers to improve the charge injection into the light-emitting layer, which leads to better recombination. This device structure provides access to hole mobility of ~2.1 cm² V⁻¹ s⁻¹ and EQE of 1.6% at a luminance of 2600 cd m⁻². Most importantly, we observed a large area emission under the entire drain electrode, which was spatially stable (emission area is not dependent on the gate voltage and current density). These results show an important advancement in polymer-based LEFET technology toward realizing new digital display applications. Full article

In this article, we report on a highly sensitive tactile shear sensor that was able to detect minute levels of shear and surface slip. The sensor consists of a suspended elastomer diaphragm with a top ridge structure, a graphene layer underneath, and a bottom substrate with multiple spatially digitized contact electrodes. When shear is applied to the top ridge structure, it creates torque and deflects the elastomer downwards. Then, the graphene electrode makes contact with the bottom spatially digitized electrodes completing a circuit producing output currents depending on the number of electrodes making contact. The tactile shear sensor was able to detect shear forces as small as 6 μN, detect shear direction, and also distinguish surface friction and roughness differences of shearing objects. We also succeeded in detecting the contact slip motion of a single thread demonstrating possible applications in future robotic fingers and remote surgical tools. Full article

In this article, we report on a novel diaphragm-type tactile pressure sensor that produces stepwise output currents depending on varying low contact pressures. When contact pressures are applied to the stepped output tactile sensor (SOTS), the sensor’s suspended diaphragm makes contact with the substrate, which completes a circuit by connecting resistive current paths. Then the contact area, and therefore the number of current paths, would determine the stepped output current produced. This mechanism allows SOTS to have high signal-to-noise ratio (>20 dB) in the 3–500 Hz frequency range at contact pressures below 15 kPa. Moreover, since the sensor’s operation does not depend on a material’s pressure-dependent electrical properties, the SOTS is able to demonstrate high reproducibility and reliability. By forming a 4 × 4 array of SOTS with a surface bump structure, we demonstrated shear sensing as well as surface (1 × 1 cm²) pressure mapping capabilities. Full article