A novel biochemical sensing approach based on a nanoplasmonic sensor chip, realized on polymers and combined with a specific receptor, has been presented. The plasmonic phenomena are excited and interrogated via two custom experimental configurations, exploiting polymer optical fibers (POFs) and designed holders. Both setups have been used to measure the disposable GNG on a PMMA chip, considering the PMMA chip as a waveguide, in the first configuration, or as a transparent substrate, in the second configuration.

The examined sensor configurations here presented have been realized and experimentally tested. To test the biosensing capabilities of the proposed method, as proof of concept, we have deposited on the sensor a receptor specific for an analyte.

The plasmonic GNG sensor has been fabricated how here schematically reported . The sample consists of a PMMA chip, on which is spun about two hundred nanometers thick positive PMMA e-beam resist layer. The nanograting pattern is obtained by an electron beam lithography (EBL) system. After the development process, a 40 nm thick gold film is deposited through a sputtering machine. The pattern covers an area of 1 mm² at the centre of the PMMA chip. The experimental results have shown a limit of detection four orders of magnitude lower than the one obtained by a biochemical sensor based on a continuous gold film on D-shaped POFs combined with the same receptor.

A novel surface plasmon (SPR) sensor was designed, manufactured, and experimentally tested. A novel approach was followed to fabricate the sensor, which is based on a combination of both inkjet 3D printing process and the use of optical adhesives, which were used as an alternative solution to the use of plastic optical fibers (POFs). The obtained experimental results showed good performances, at least in terms of figure of merit (FOM) for the 3D printed sensor, which were quite similar to those gained SPR-POF configuration. Instead, a pursue to optimize the poor sensitivity of the novel developed sensor was made by mean of a Design of Experiment (DoE) approach: a surfaces lapping procedure was implemented and some geometric parameters were varied. Next, through a cost analysis the possibility of manufacturing the SPR sensor at low cost was proved, thus being economically advantageous towards conventional sensors.

Eventually, a SPR sensor manufactured at low cost (~ 15 €), showing performances similar to POFs, and realized by mean of 3D printing manufacturing free design, was developed. It represents a breakthrough innovation because, being able to be integrated with other devices on the same plastic planar support, it can find application in several fields as all-polymers photonic sensor.

Parkinson disease (PD) is one of the most common neurodegenerative diseases, affecting millions of people worldwide, especially the elderly population, and its main motor symptoms usually are bradykinesia, tremor and rigidity. In the last decade, there have been a lot of studies concerning the research of reliable markers for the early diagnosis of it, since this can lead to a significant improvement in quality of life for the patients.

It has been demonstrated that handwriting impairment can be an important early marker for the detection of this disease.

The aim of this study is to propose a simple and quick way to discriminate PD patients from controls through handwriting tasks using machine learning techniques. We developed a telemonitoring system based on a user-friendly application for digitising tablets that enabled on us to collect real-time information about position, pressure, and inclination of the digital pen during the experiment and, simultaneously, to supply visual feedback on the screen to the subject. The data can be collected remotely, in order to allow the patients to execute tasks in the comfort and safety of their home, reducing the demand on hospital services. Handwriting data from 20 PD patients and 20 control subjects were collected: Information about position, pressure, and inclination of the pen during the tasks have been extracted through a software developed by our team. the participants have been asked to draw an Archimedean spiral and ten concentric circles, and to write the cursive bigram “le”, two Italian sentences and seven lines of free text. In this way, we were able to compute features linked to kinematics, pressure, geometry, and energy of the strokes.

Atrial fibrillation (AF) is one of the most diffused cardiac arrhythmias. Suffering from AF may lead to heart failure and to stroke, so an early detection and a continous monitoring are determining factors in the desease prevention. With the development of telemonitoring systems through wearable devices, the personalized medicine has reached a new level of improvement. An increasing number of telemonitoring systems base their functioning on the recording and the analysis of single-lead ECGs, with the purpose of detecting heart diseases using heart rhythm and rate features.

The purpose of this paper is to present an algorithm for the screening and monitoring of heart disease patients. While most of the wearable systems in this area are limited to the monitoring of ECG, this algorithm uses the combined analysis of different biosignals obtained with a sensorized t-shirt equipped with a single-lead ECG, a pulse-oximeter and a temperature sensor.

Since AF is known to alter heart rhythms’ dynamic and morfological characteristics of ECG signal, a time and frequency domain analysis is performed in order to extract the ECG features. Data collected from wearable devices are often exposed to different kind of artifacts, so morphological characteristic are not preferred because of their lack of robustness in noisy conditions. For this reason frequency and heart rate variability (HRV)-based analisys are used for features extraction. Through this ECG analysis and with the support of the other recorded biosignals, is therefore possibile to exctract features to perform an automatic detection of arrhythmias (specifically AF) and the classification of ECG signals.

Technological innovations in the development of wearable sensors have lead to advancements in smart wearable devices targeted at health monitoring, a research topic of great interest. In fact, telemonitoring systems can help unloading the health care system and minimising the exposure to hospital infection, allowing remote and personalized patient care. In this work we focused on the remote telemonitoring of cardiovascular diseases, in particular atrial fibrillation, because an early diagnosis is important to reduce the risk of stroke. Wearable devices in cardiology are focused on ECG and respiratory parameters, while we tried to provide a wider system, introducing unusual sensors related to cardiac monitoring. We developed a sensorized t-shirt for monitoring vital signs in the home enviroment: it includes a single-lead ECG, a pulse-oximeter and a temperature sensor, all connected to an Arduino board. Data collected are directly sent to the computer with a Bluetooth module, where they can be filtered and visualized thanks to a specific Matlab script, or alternatively they can be visualized Real-Time. Signals are collected with different sampling frequencies, in order to align the system with the literature. We proposed aof 120 seconds at rest where patients wear the sensorized t-shirt and the data elaboration provide information about heart rhythm, average temperature and oxygen saturation. The result is a simple, low-cost and low-power system, an easily applicable solution within everyone’s reach.

High-resolution liquid level sensing is relevant to industry monitoring. Compared to conventional electrical liquid-level sensors, optical-fiber sensors provide key advantages such as immunity to electromagnetic interference, good corrosion resistance, and high sensitivity. In this work, we demonstrate a high-resolution distributed liquid level sensor based on a Cobalt-based, high-attenuation fiber (HAF). Commonly, all-optical liquid sensing makes use of a dual wavelength scheme, where one wavelength is used for heating and the other one for sensing. Here, we propose a simplified approach making use of a single wavelength (1550 nm). A high-spatial resolution (5 mm) Brillouin Optical Frequency-Domain Analysis (BOFDA) sensor is employed to measure the temperature profile along the HAF. The BOFDA method permits to determine the temperature profile along the fiber, using a single laser for the generation of both the pump and probe beams involved in the stimulated Brillouin scattering (SBS) process. The pump beam is composed of a continuous wave (cw) component, superimposed to a small-amplitude modulated component at varying modulation frequencies. In our method, the cw component of the pump has a dual role: on one side, it pre-excites the acoustic wave involved in the SBS phenomenon; on the other side, it heats up the fiber in a manner dependent on the surrounding medium (air, or liquid). Using a HAF fiber with an absorption loss of 40 dB/m, we demonstrate that the proposed sensor determines the liquid level with a spatial resolution in the mm-range, and a sensing range of (at least) 25 cm.

In this article, a novel cost-effective method is proposed to achieve microfeature-sized patterns on Polydimethylsiloxane (PDMS) substrates. PDMS as a biocompatible, flexible, economical, and easy-to-use polymer benefiting the trait of mechanical impedance close to soft tissues, is the best candidate to be used where we need communication between the electrical circuit and soft tissues. This is while PDMS can be matched with tissue’s different shapes and doesn’t cause any trauma. Complex and high-cost manufacturing methods of microfeature-sized patterns on PDMS, such as conventional microfabrication methods will be eliminated by the proposed approach. Our technique takes advantage of not requiring standard photolithography processes, making it simple and cost-effective. This manner can be used for a variety of different purposes, such as microfluidic chip fabrication, biosensing applications, neuroscience research and neural prosthetics such as electrocorticogram (ECoG) and, in general, where microfeature-size patterning on PDMS is required. To prove the method’s functionality, a test sample was fabricated. Firstly, the scaffold was fabricated using a conventional laser engraver and Poly(methylmethacrylate) (PMMA). Then, a mold was made using this scaffold from PDMS. Then S1813 photoresist was applied as an anti-adhesion layer between the PDMS mold and the sample to make the sample peel off easily from the mold surface. The final sample indicated that the pattern’s feature size was around 250 micrometers and that the required patterns were very close to the desired form possible.

In many application fields, chemical and biological sensors require a smart device to monitor them, such as laptops with specific software installed. Numerous biochemical sensors are based on small-size plasmonic platforms with high sensitivity. Thus, a system was accomplished to support the potentialities of a novel tool relative to plasmonic sensors in waveguides that can be applied in several biosensor configurations, where the measurements can be carried out in spectral mode. In particular, the sensors based on a surface plasmon resonance (SPR) phenomenon represent a very sensitive method for detecting specific substances, exploiting several kinds of receptors combined with them. The typical configuration of these sensors is arranged to measure the transmitted light spectrum. First, the light is radiated by a halogen lamp, illuminating the SPR sensor, and then it is collected by a spectrometer connected to a Laptop. The proposed measurement system is managed by software titled “Spectra Analysis by Universal Tool” (SAUT). The developed software tool can configure the instrumentation, the network, the database and the folder to save the experimental results.
Thus, the proposed tool could be used in several application fields requiring a user-friendly interface, e.g., point-of-care applications, environment monitoring, Internet of things (IoT) applications, security, and industrial applications.

Following the outbreak of the SARS-CoV-2 pandemic, the demand for faster diagnostic systems has pushed research activities towards the development of innovative technologies for the detection of the virus through simple, fast and low-cost methods. However, the current diagnostic procedure relies on the molecular technique of Reverse Transcription Polymerase Chain Reaction (RT-PCR), which is expensive and time-consuming.
Aiming at addressing this issue, a plasmonic biochemical sensor for SARS-CoV-2 was realized by combining a plasmonic plastic optical D-shaped fiber sensor with a brand-new kind of synthetic molecularly imprinted polymer (MIP) receptor. The synthetic MIP was properly designed for the molecular recognition of the Subunit 1 of the SARS-CoV-2 Spike protein.
Preliminary experimental results on the developed sensor were performed to test its effectiveness in binding the Subunit 1 of the SARS-CoV-2 Spike protein in different solutions. Afterwards, tests on the SARS-CoV-2 virions were carried on using nasopharyngeal (NP) swabs in UTM (universal transport medium) and physiological solution (0.9% NaCl). The results achieved were compared in the end with those obtained with RT-PCR.
According to these results, the proposed optical biochemical sensor proved to effectively determine SARS-CoV-2 virions in biological samples and with an even higher sensitivity than the RT-PCR one. Furthermore, a reasonably quick response time to the virus (about 10 minutes) was achieved.

The classical production of microfibrillar cellulose involves intensive mechanical processing and discontinuous chemical treatment in solvent-based media in order to introduce additional chemical surface modification. By selecting appropriate conditions of a pulsed plasma reactor, a solvent-free and low-energy input process can be applied with introduction of microcrystalline cellulose (MCC) and maleic anhydride (MA) powders. The plasma processing results in the progressive fibrillation of the cellulose powder into its elementary microfibrillar structure and in-situ modification of the produced fibrils with more hydrophobic groups that provide good stability against re-agglomeration of the fibrils. The selection of MCC/MA ratio at above 200 % allows to separate the single cellulose microfibrils with changeable morphologies depending on the plasma treatment time. Moreover, the density of the hydrophobic surface groups can be changed through selection of different plasma duty cycle times, while the influence of plasma power and pulse frequency is inferior. The variations in treatment time can be followed along the plasma reactor, as the microfibrils gain smaller diameter and become somewhat longer with increasing plasma time. This can be related to the activation of the hierarchical cellulose structure and progressive diffusion of the MA within the cellulose microfibrils causing progressive weakening of the hydroxyl bonding. In parallel, the creation of more reactive species with time allows to create active surface sites that allow for interaction between the different fibrils into more complex morphologies. The in-situ surface modification has been demonstrated by XPS and FTIR analysis, indicating the successful esterification between the MA and hydroxyl groups at the cellulose surface. In particular, the crystallinity of the cellulose has been augmented after plasma modification. Furthermore, the AFM evaluation of the fibrils show surface structures with irregular surface roughness patterns that contribute to better interaction of the microfibrils after incorporation in an eventual polymer matrix. In conclusion, the combination of physical and chemical processing of cellulose microfibrils provide a more sustainable approach for fabrication of advanced nanotechnological materials.