Stand-alone wearable system for ubiquitous real-time monitoring of muscle activation potentials

Wearable technology is attracting most attention in healthcare for the acquisition of physiological signals. We propose a stand-alone wearable surface ElectroMyoGraphy (sEMG) system for monitoring the muscle activity in real time. With respect to other wearable sEMG devices, the proposed system includes circuits for detecting the muscle activation potentials and it embeds the complete real-time data processing, without using any external device. The system is optimized with respect to power consumption, with a measured battery life that allows for monitoring the activity during the day. Thanks to its compactness and energy autonomy, it can be used outdoor and it provides a pathway to valuable diagnostic data sets for patients during their own day-life. Our system has performances that are comparable to state-of-art wired equipment in the detection of muscle contractions with the advantage of being wearable, compact, and ubiquitous

model of reversible breakdown in hfo2 based on fractal patterns

We propose a model of the kinetics of reversible breakdown in metal-insulator-metal structures with afnia based on the growth of fractal patterns of defects when the insulator is subject to an external voltage. The probability that a defect is (or is not) generated and the position where it is generated depend on the electric field distribution. The new defect moves accordingly to fractal rules and attach to another defect in a tree branch. When the two electrodes sandwiching the insulating film are connected a conductive filament is formed and the breakdown takes place. The model is calibrated with experiments inducing metastable soft breakdown events in Pt/HfO2/Pt capacitors

Flip-angle based ratiometric approach for pulsed CEST-MRI pH imaging

Several molecules have been exploited for developing MRI pH sensors based on the chemical exchange saturation transfer (CEST) technique. A ratiometric approach, based on the saturation of two exchanging pools at the same saturation power, or by varying the saturation power levels on the same pool, is usually needed to rule out the concentration term from the pH measurement. However, all these methods have been demonstrated by using a continuous wave saturation scheme that limits its translation to clinical scanners. This study shows a new ratiometric CEST-MRI pH-mapping approach based on a pulsed CEST saturation scheme for a radiographic contrast agent (iodixanol) possessing a single chemical exchange site. This approach is based on the ratio of the CEST contrast effects at two different flip angles combinations (180°/360° and 180°/720°), keeping constant the mean irradiation RF power (Bavg power). The proposed ratiometric approach index is concentration independent and it showed good pH sensitivity and accuracy in the physiological range between 6.0 and 7.4

Fluorescent biosensors based on silicon nanowires

Nanostructures are arising as novel biosensing platforms promising to surpass current performance in terms of sensitivity, selectivity, and affordability of standard approaches. However, for several nanosensors, the material and synthesis used make the industrial transfer of such technologies complex. Silicon nanowires (NWs) are compatible with Si-based flat architecture fabrication and arise as a hopeful solution to couple their interesting physical properties and surface-to-volume ratio to an easy commercial transfer. Among all the transduction methods, fluorescent probes and sensors emerge as some of the most used approaches thanks to their easy data interpretation, measure affordability, and real-time in situ analysis. In fluorescent sensors, Si NWs are employed as substrate and coupled with several fluorophores, NWs can be used as quenchers in stem-loop configuration, and have recently been used for direct fluorescent sensing. In this review, an overview on fluorescent sensors based on Si NWs is presented, analyzing the literature of the field and highlighting the advantages and drawbacks for each strategy

Photonic Torque Microscopy of the Nonconservative Force Field for Optically Trapped Silicon Nanowires

We measure, by photonic torque microscopy, the nonconservative rotational motion arising from the transverse components of the radiation pressure on optically trapped, ultrathin silicon nanowires. Unlike spherical particles, we find that nonconservative effects have a significant influence on the nanowire dynamics in the trap. We show that the extreme shape of the trapped nanowires yields a transverse component of the radiation pressure that results in an orbital rotation of the nanowire about the trap axis. We study the resulting motion as a function of optical power and nanowire length, discussing its size-scaling behavior. These shape-dependent nonconservative effects have implications for optical force calibration and optomechanics with levitated nonspherical particles

A machine learning-based approach to optimize repair and increase yield of embedded flash memories in automotive systems-on-chip

Nowadays, Embedded Flash Memory cores occupy a significant portion of Automotive Systems-on-Chip area, therefore strongly contributing to the final yield of the devices. Redundancy strategies play a key role in this context; in case of memory failures, a set of spare word- and bit-lines are allocated by a replacement algorithm that complements the memory testing procedure. In this work, we show that replacement algorithms, which are heavily constrained in terms of execution time, may be slightly inaccurate and lead to classify a repairable memory core as unrepairable. We denote this situation as Flash memory false fail. The proposed approach aims at identifying false fails by using a Machine Learning approach that exploits a feature extraction strategy based on shape recognition. Experimental results carried out on the manufacturing data show a high capability of predicting false fails

Ultrathin silicon nanowires for optical and electrical nitrogen dioxide detection

The ever-stronger attention paid to enhancing safety in the workplace has led to novel sensor development and improvement. Despite the technological progress, nanostructured sensors are not being commercially transferred due to expensive and non-microelectronic compatible materials and processing approaches. In this paper, the realization of a cost-effective sensor based on ultrathin silicon nanowires (Si NWs) for the detection of nitrogen dioxide (NO2 ) is reported. A modification of the metal-assisted chemical etching method allows light-emitting silicon nanowires to be obtained through a fast, low-cost, and industrially compatible approach. NO2 is a well-known dangerous gas that, even with a small concentration of 3 ppm, represents a serious hazard for human health. We exploit the particular optical and electrical properties of these Si NWs to reveal low NO2 concentrations through their photoluminescence (PL) and resistance variations reaching 2 ppm of NO2 . Indeed, these Si NWs offer a fast response and reversibility with both electrical and optical transductions. Despite the macro contacts affecting the electrical transduction, the sensing performances are of high interest for further developments. These promising performances coupled with the scalable Si NW synthesis could unfold opportunities for smaller sized and better performing sensors reaching the market for environmental monitoring