Lidia Dobrescu

Analog layouts often use matched devices to reduce sensitivity to process gradients. However, the resulting interconnect can introduce parasitic coupling. We compare four DRC-clean, LVS-equivalent layouts of the same hysteresis comparator, implemented in a 130 nm bulk CMOS process with 5 V, thick-oxide devices. The schematic, bias, load, and R+C+CC extraction flow are held fixed, while placement and routing vary together. At 5.0 V and 25 °C, the strictly common-centroid layout has a simulated 315.758 mV high-state output ripple despite nearly balanced input capacitances. Among the protected layouts, C3 yields the narrowest finite-slew switching window, whereas C4 reduces nominal ripple to 0.275 mV. In 200 mismatch samples at the nominal 5.0 V supply, C3 and C4 have similar threshold dispersion, while C4 retains lower output ripple. The observations support evaluating placement and routing together with device matching. The preferred layout depends on the chosen performance metric.

This paper presents a compact output-stage current-limiting architecture intended for reliable overcurrent protection in CMOS analog and mixed-signal circuits. In modern integrated systems, the output stages of blocks such as operational amplifiers, drivers, buffers, and reference circuits may be exposed to overload conditions, low-impedance loads, or short circuits that can lead to excessive power dissipation and device degradation. The proposed architecture employs scaled replicas of the output transistors together with local negative feedback to sense the delivered load current and independently limit both sinking and sourcing currents. The circuit is demonstrated by integration into a two-stage folded-cascode operational amplifier with a class-AB output stage and evaluated through circuit-level simulations in 130 nm CMOS technology. The results confirm a well-defined current limit across the supply and temperature corners that are relevant to high-reliability applications, spanning 2 V and 5 V supplies and a temperature range from −55 °C to 175 °C. The proposed current-limiting scheme constrains both pull-down and pull-up currents to approximately 9–12 mA across the investigated operating domain. Monte Carlo analysis further shows bounded dispersion and symmetric single-mode distributions, indicating predictable operation under device mismatch. These results demonstrate that the proposed architecture provides a compact and scalable solution for deterministic current limiting in reliability-critical CMOS systems.

Conventional operational amplifier designs often experience parameter performance issues during the transition between complementary input differential stages, which restricts the full rail-to-rail common mode voltage swing. This paper presents an innovative charge pump architecture featuring a feedback supply selector that optimizes the transition performance. The proposed approach employs a switched-capacitor technique to boost the supply voltage by 1.5 V relative to the input voltage, thereby enabling the use of a single pMOS differential input stage. The novel supply selector dynamically chooses the maximum available voltage between the external supply and the boosted output, ensuring efficient transistor switching and improved biasing. Schematic-level and post-layout simulations in a 250 nm CMOS process validate the design under varied load currents, supply voltages, temperatures, and process corners. Results show a significant reduction in output voltage ripple, with a maximum value of 48 mV achieved post-layout, and enhanced overall efficiency, even under higher load currents. This architecture provides a robust and scalable solution for advanced operational amplifiers, particularly in fields where high performance and stability are critical.

Analysis of unintended compromising emissions from Video Display Units (VDUs) is an important topic in research communities. This paper examines the feasibility of recovering the information displayed on the monitor from reconstructed video frames. The study holds particular significance for our understanding of security vulnerabilities associated with the electromagnetic radiation of digital displays. Considering the amount of noise that reconstructed TEMPEST video frames have, the work in this paper focuses on two different approaches to de-noising images for efficient optical character recognition. First, an Adaptive Wiener Filter (AWF) with adaptive window size implemented in the spatial domain was tested, and then a Convolutional Neural Network (CNN) with an encoder–decoder structure that follows both classical auto-encoder model architecture and U-Net architecture (auto-encoder with skip connections). These two techniques resulted in an improvement of more than two times on the Structural Similarity Index Metric (SSIM) for AWF and up to four times for the SSIM for the Deep Learning (DL) approach. In addition, to validate the results, the possibility of text recovery from processed noisy frames was studied using a state-of-the-art Tesseract Optical Character Recognition (OCR) engine. The present work aims to bring to attention the security importance of this topic and the non-negligible character of VDU information leakages.

The information technology and communication (IT&C) market consists of computing and telecommunication technology systems, which also include a variety of audio devices. Preserving the confidentiality of transmitted information through these devices stands as a critical concern across various domains and businesses. Notably, spurious electromagnetic emanations emitted by audio devices can be captured and processed, potentially leading to eavesdropping incidents. The evaluation of electronic devices for potential security vulnerabilities often involves employing Transient Electromagnetic Pulse Emanation Standard (TEMPEST) technology. This paper introduces a novel approach to TEMPEST testing specifically tailored for audio devices. The outcomes of the proposed approach offer valuable insights into TEMPEST equipment testing, aiming to mitigate the potential risks posed by threats exploitable by eavesdroppers in everyday scenarios. The present work delves into the examination of two ubiquitous global electronic devices: a notebook and a pair of in-ear headphones. The symmetrical framework of this study arises from the intrinsic similarity that, despite belonging to distinct categories, both devices possess the capability to emit electromagnetic emissions that contain compromised audio signals. This assertion is substantiated by the measurement results presented herein. The proposed methodology involves the analysis of the audio amplitude modulation (AM) demodulated signal in the frequency domain. This innovative approach not only mitigates operator fatigue but also significantly reduces the testing time required for these devices and instrument running hours and leads to the development of new applications.

The origin of the photoplethysmography (PPG) signal is a debatable topic, despite plausible models being addressed. One concern revolves around the correlation between the mechanical waveform’s pulsatile nature and the associated biomechanism. The interface between these domains requires a clear mathematical or physical model that can explain physiological behavior. Describing the correct origin of the recorded optical waveform not only benefits the development of the next generation of biosensors but also defines novel health markers. In this study, the assumption of a pulsatile nature is based on the mechanism of blood microcirculation. At this level, two interconnected phenomena occur: variation in blood flow velocity through the capillary network and red blood cell (RBC) shape deformation. The latter effect was qualitatively investigated in synthetic capillaries to assess the experimental data needed for PPG model development. Erythrocytes passed through 10 µm and 6 µm microchannel widths with imposed velocities between 50 µm/s and 2000 µm/s, according to real scenarios. As a result, the length and area deformation of RBCs followed a logarithmic law function of the achieved traveling speeds. Applying radiometric expertise on top, mechanical-optical insights are obtained regarding PPG’s pulsatile nature. The mathematical equations derived from experimental data correlate microcirculation physiologic with waveform behavior at a high confidence level. The transfer function between the biomechanics and the optical signal is primarily influenced by the vasomotor state, capillary network orientation, concentration, and deformation performance of erythrocytes.

The demand for CMOS precision operational amplifiers for critical applications has continuously increased over time due to higher accuracy and sensitivity requirements. Trimming or chopper architectures are advanced solutions that reduce the offset voltage and improve the circuit’s parameters, but the complexity and the increased chip die size are serious downsides. An efficient solution is a source degeneration configuration to control the transistor’s current-mirror transconductance, which impacts the offset voltage, with cost savings and a die area reduction also obtained. This paper focuses on designing and implementing such an approach in a two-stage folded-cascode operational amplifier. State-of-the-art thin-film resistors that use silicon–chromium as the metallic alloy were implemented to reduce mismatch variations between these passive components. Distinct methods that control the offset voltage parameter are also discussed and established. A comparison between the offset voltage standard deviation obtained using different types of resistors and that achieved with the innovative high-precision resistors was also carried out. The source degeneration’s impact on the common-mode rejection ratio, power supply rejection ratio, bandwidth and phase margin was also analyzed, and a comparison between the proposed design and the classical one was performed. The process variation’s influence on the circuit functionality was studied. A pre-layout ±1.273 mV maximum offset voltage at T = 27 °C was achieved using vector/array notations for the amplifier with the best overall performance. Post-layout simulations that included parasitic effects were performed, with a ±1.254 mV maximum offset voltage reached at room temperature.

Left ventricular ejection time (LVET) is an important parameter for assessing cardiovascular disorders. In a medical office, it is typically measured using the Tissue Doppler Imaging technique, but new wearable devices have led to a growing interest in integrating this parameter into them, increasing accessibility to personalized healthcare for users and patients. In the cardiovascular domain, photoplethysmography (PPG) is a promising technology that shares two distinctive features with invasive arterial blood pressure (ABP) tracing: the tidal wave (TDW) and the dicrotic wave (DCW). In the early years of cardiovascular research, the duration of the dicrotic point was initially linked to the ending phase of left ventricular ejection. Subsequent studies reported deviations from the initial association, suggesting that the ejection period is related to the tidal wave feature. In this current study, we measured left ventricular ejection time in both ABP and PPG waveforms, considering recent research results. A total of 27,000 cardiac cycles were analyzed for both afore-mentioned signals. The reference value for ejection time was computed based on the T-wave segment duration from the electrocardiogram waveform. In lower blood pressure, which is associated with decreased heart contractility, the results indicated an underestimation of −29 ± 19 ms in ABP and an overestimation of 18 ± 31 ms in PPG. On the other side of the spectrum, during increased contractility, the minimum errors were −3 ± 18 ms and 4 ± 33 ms, respectively. Since the tidal wave feature is strongly affected by arterial tree compliance, the population evaluation results indicate a Pearson’s correlation factor of 0.58 in the ABP case, and 0.53 in PPG. These findings highlight the need for advanced compensation techniques, in particular for PPG assessment, to achieve clinical-grade accuracy.

Improved performance operational amplifier demand has continuously increased. IC designers use the charge pump technique as an advanced solution to implement the amplifier’s rail−to−rail input stage, but the need for a large load capacitor is a serious downside. To reduce this passive component value, high−frequency clock circuits with a 50% duty cycle should be implemented. This paper focuses on designing such a circuit that is further compensated with temperature and power supply, maintaining these performances even when process variations occur, starting from a ring oscillator as the architecture core. A pre−layout 50 MHz center frequency at 25 °C with a 1.6 temperature percentage error was achieved. Post−layout simulations to account for parasitic effects were also performed, with a 48.9 MHz center frequency reached. Distinct methods that control the frequency variation were discussed and established. Performance comparison of the designed PLL with previously reported clock circuits in the CMOS process was concluded, with superior results such as power consumption, die area, and temperature range accomplished.

In our modern digitalized world, hypertension detection represents a key feature that enables self-monitoring of cardiovascular parameters, using a wide range of smart devices. Heart rate and blood oxygen saturation rate are some of the most important ones, easily computed by wearable products that are provided by the photoplethysmography (PPG) technique. Therefore, this low-cost technology has opened a new horizon for health monitoring in the last decade. Another important parameter is blood pressure, a major predictor for cardiovascular characterization and health related events. Analyzing only PPG signal morphology and combining the medical observation with machine learning (ML) techniques, this paper develops a hypertension diagnosis tool, named the ANC Test™. During the development process, distinguishable characteristics have been observed among certain waveforms and certain types of patients that leads to an increased confidence level of the algorithm. The test was enchanted by machine learning models to improve blood pressure class detection between systolic normotensive and hypertensive patients. A total of 359 individual recordings were manually selected to build reference signals using open-source available databases. During the development and testing phases, different ML models accuracy of detecting systolic hypertension scored in many cases around 70% with a maximum value of 72.9%. This was resulted from original waveform classification into four main classes with an easy-to-understand nomenclature. An important limitation during the recording processing phase was given by a different PPG acquisition standard among the consulted free available databases.