TiO₂ nanoparticles coating has been proven to be an extremely performing sensing material for relative humidity (RH) measurements. The chemical activity of TiO₂ toward water vapor adsorption and the very large surface to volume ratio typical of nanostructures are ideal characteristics for the development of RH fast and sensitive sensors. Different sensor technologies can be used in conjunction with this material to realize devices with satisfactory performance. In this paper, the authors aim to describe and discuss the main different possible choices and highlight the advantages and disadvantages, and linking them both to the underlying mechanism of water adsorption on the TiO₂ sensing layer and to the modification of the electrical behavior due to the water adsorption. In particular, the authors start from results obtained by depositing TiO₂ nanoparticles on a novel MEMS microbalance operating at low frequency, which allows to sense only the adsorbed water mass, and they exploit the sensor output to obtain a dynamic model of the water adsorption. They also link these results to those obtained with a Quartz Crystal Microbalance (QCM) functionalized with the same material operating at 10 MHz as a part of an oscillator. Finally, they establish a link with the results obtained by an RH impedance sensor, which exploits the same active material and the same deposition technique. With this sensor technology, the conductive and electrical behavior of the sensing and adsorbed films play a role. The whole work tries to unravel the different phenomena that contribute to the response of RH sensors not only based on TiO₂ nanoparticles but also, more generally, based on nanostructured metal oxide materials.

The paper provides an overview of the measurement issues affecting sensing systems based on QCM, operating in liquid. The paper analyses the effect of the presence of a viscous liquid at the interface with the QCM sensors by analytical models and experimental tests based on impedance measurements in reference conditions. The study takes also into account the parasitic effects due to the measurement setup and provides results, which can be applied to a wide range of scenarios also in the presence of highly viscous media. The paper also presents a model fitting procedure for QCM impedance spectra, which provides accurate estimations of the electromechanical parameters.

This work proposes a model describing the dynamic behavior of sensing films based on functionalized MWCNT networks in terms of conductivity when exposed to time-variable concentrations of NO₂ and operating with variable working temperatures. To test the proposed model, disordered networks of MWCNTs functionalized with COOH and Au nanoparticles were exploited. The model is derived from theoretical descriptions of the electronic transport in the nanotube network, of the NO₂ chemisorption reaction and of the interaction of these two phenomena. The model is numerically implemented and then identified by estimating all the chemical/physical quantities involved and acting as parameters, through a model fitting procedure. Satisfactory results were obtained in the fitting process, and the identified model was used to further the analysis of the MWCNT sensing in dynamical conditions.

Monitoring heart rate (HR) through photoplethysmography (PPG) signals is a challenging task due to the complexities involved, even during routine daily activities. These signals can indeed be heavily contaminated by significant motion artifacts resulting from the subjects’ movements, which can lead to inaccurate heart rate estimations. In this paper, our objective is to present an innovative necklace sensor that employs low-computational-cost algorithms for heart rate estimation in individuals performing non-abrupt movements, specifically drivers. Our solution facilitates the acquisition of signals with limited motion artifacts and provides acceptable heart rate estimations at a low computational cost. More specifically, we propose a wearable sensor necklace for assessing a driver’s well-being by providing information about the driver’s physiological condition and potential stress indicators through HR data. This innovative necklace enables real-time HR monitoring within a sleek and ergonomic design, facilitating seamless and continuous data gathering while driving. Prioritizing user comfort, the necklace’s design ensures ease of wear, allowing for extended use without disrupting driving activities. The collected physiological data can be transmitted wirelessly to a mobile application for instant analysis and visualization. To evaluate the sensor’s performance, two algorithms for estimating the HR from PPG signals are implemented in a microcontroller: a modified version of the mountaineer’s algorithm and a sliding discrete Fourier transform. The goal of these algorithms is to detect meaningful peaks corresponding to each heartbeat by using signal processing techniques to remove noise and motion artifacts. The developed design is validated through experiments conducted in a simulated driving environment in our lab, during which drivers wore the sensor necklace. These experiments demonstrate the reliability of the wearable sensor necklace in capturing dynamic changes in HR levels associated with driving-induced stress. The algorithms integrated into the sensor are optimized for low computational cost and effectively remove motion artifacts that occur when users move their heads.

In this paper, NO₂ sensing by means of single-wall carbon nanotubes (SWCNT) networks, decorated with nanoparticles of TiO₂ and Au, is proposed. In particular, it is shown that the performance of these materials can be enhanced using pulsed temperature mode. This sensing strategy effectiveness is theoretically and experimentally assessed. In this paper, in fact, a dynamic model for conductive gas sensors formed by networks of nanowires, considering the junctions between different wires as the main contribution to sensor conductance, and in the presence of the target gas, is presented and validated. The model accounts for variable temperature and gas concentration and sheds some light on the mechanisms leading to the sensor response improvement related to temperature pulsed working mode. It is also shown how the addition of a different material can be modeled through different surface adsorption kinetics.

In this series of two papers, the humidity sensing of a carbon nanotube’s (CNTs) network-based material is studied through quartz crystal microbalance (QCM) sensors. To this aim, quartzes functionalized with different amounts of sensing material were realized, exposed to different humidity levels, and characterized. In this first paper, the theoretical framework is presented, whereas the second one presents the experimental study. This paper discusses at first the water adsorption and desorption on single-wall carbon nanotube (SWCNT) networks, and subsequently deeply investigates the behavior of QCM-based measurements. Numerical simulations based on the equivalent electrical model of the quartz were used for predicting the vibrational behavior of functionalized QCMs when exposed to different humidity levels, accounting for the effect of the different water adsorption mechanisms: chemisorption, physisorption, and capillary condensation.