Latest Advancements in SSVEPs Classification for Single-Channel, Extended Reality-based Brain-Computer Interfaces

This work details the latest advancements on a single-channel, reactive Brain-Computer Interfaces developed at the Interdepartmental Research Center in Health Management and Innovation in Healthcare (CIRMIS) of the University of Naples Federico II. The proposed instrumentation is based on Extended Reality (XR) and exploits the acquisition and classification of the Steady-State Visually Evoked Potentials (SSVEPs). In particular, an XR headset is employed for generating the flickering stimuli necessary to the SSVEP elicitation. The users brain signals are captured by means of a highly wearable and portable electroencephalografic acquisition unit, which is connected to a portable processing unit in charge of processing in real time the incoming data. In this way, a deeper interaction between users and external devices with respect to traditional architectures is guaranteed. The classification capability of the proposed instrument has been significantly improved over the years. Currently, in fact, a classification accuracy up to 90 % is obtained with at least 2 s of acquisition time

Moisture content measurements through TDR: A metrological assessment for industrial applications

In this paper a metrological assessment on the accuracy provided by a Time Domain Reflectometry (TDR)-based method for the estimation of moisture content of granular materials is proposed. In particular, comparative moisture content measurements are carried out through two different TDR instruments: an inexpensive portable unit and a high-performance unit. The main goals are first to assess a robust procedure for TDR moisture monitoring (in particular for sand-like materials), and second to provide a deep metrological analysis for minimizing and characterizing error contributions. This feature is particularly important when considering the proposed measurement procedures for industrial applications, where both accuracy and low cost must be guaranteed

On the use of dielectric spectroscopy for quality control of vegetable oils

Quality control of vegetable oils is becoming more stringent, and related laws are being enforced especially for avoiding adulteration. As a result, there is a substantial need for methods of analysis that could provide real-time in-situ monitoring, especially for quality control purposes during production process. In this regard, the present paper investigates the possibility of monitoring qualitative characteristics of vegetable oils through microwave dielectric spectroscopy, which is a highly versatile investigative approach. In particular, the Cole & Cole frequency-domain dielectric parameters are known to be strongly related to the compositional characteristics of various substances. This way, starting from traditional Time Domain Reflectometry measurements performed on oils, the corresponding frequency domain information is retrieved. Successively, through a minimization routine, the Cole & Cole parameters of each considered oil are extrapolated. Results show that different dielectric characteristics can be associated with different oils. It is important to point out that the characteristics of the proposed procedure can be automated and, therefore, it may represent a promising solution for practical monitoring applications

An Augmented Reality-Based Solution for Monitoring Patients Vitals in Surgical Procedures

In this work, an augmented reality (AR) system is proposed to monitor in real time the patient's vital parameters during surgical procedures. This system is characterised metrologically in terms of transmission error rates and latency. These specifications are relevant for ensuring real-time response. The proposed system automatically collects data from the equipment in the operating room (OR), and displays them in AR. The system was designed, implemented and validated through experimental tests carried out using a set of Epson Moverio BT-350 AR glasses to monitor the output of a respiratory ventilator and a patient monitor in the OR

ARCHAEOLOGICAL MATERIALS FROM GABII (CENTRAL ITALY): KNOWLEDGE OF OFFERINGS AND RITUALS AT THE INFANT BURIALS THROUGH AN INTEGRATED APPROACH

The ancient Latin city of Gabii is situated 18 km (11.2 miles) to the east of Rome (Central Italy) along the modern Via Prenestina. Gabii was a renowned city in Roman times, particularly during the Republican period and there are various influences in the site that can be identified in Roman culture itself. Gabii is also one of the most significant and important archaeological sites in the territory of the Municipality of Rome and due to its characteristics, it represents today an extraordinary research context. From the excavations carried out in the past it is possible to see how, under the soil, the main structures and buildings of the ancient city are still largely preserved. Among the various testimonies of the past, the tombs, and the micro and macro remains that these contain, represent an opportunity to investigate such practices in the context of Early Iron Age and Orientalizing Latium. In particular, the finds from the Area D baby burials of Gabii enriched the existing dataset so far significantly, allowing us to explore funerary ritual behavior in a more systematic way. This work reports the results of the detailed examination of four tombs (Tombs 30, 50, 51 and 52) of archaeological site. The field strategy for the excavation of the tombs was geared from the start towards both the systematic retrieval of archaeobotanical and zooarchaeological remains and the sampling for organic residue analysis. Aiming for total recovery, the sediments from the tomb fills were sifted in their entirety as their stratigraphic excavation progressed, and samples were taken for flotation. This careful screening allowed for the detection of concentrations of organic material that represent plant and/or animal depositions. The excavation and removal of the grave goods was carried out following strict protocols for residue sampling, minimizing the risk of organic contamination. Samples were analysed by High Temperature Gas Chromatography/Mass Spectrometry (HTGC/MS) and Gas chromatography/Combustion/Isotope ratio mass spectrometry (GC-C-IRMS). For each burial, a subset of vessels including both closed and open shapes was selected, such as cups, open bowl without foot, amphoretta, amphora with dots, Kantharos, plate on a foot, olla, and olpe in bucchero. The results demonstrate the still largely unexploited potential of this sort of integrated studies, encouraging us to expand the application of chemical methods to contexts from other well–controlled excavations

A ML-based Approach to Enhance Metrological Performance of Wearable Brain-Computer Interfaces

In this paper, the adoption of Machine Learning (ML) classifiers is addressed to improve the performance of highly wearable, single-channel instrumentation for Brain-Computer Interfaces (BCIs). The proposed BCI is based on the classification of Steady-State Visually Evoked Potentials (SSVEPs). In this setup, Augmented Reality Smart Glasses are used to generate and display the flickering stimuli for the SSVEP elicitation. An experimental campaign was conducted on 20 adult volunteers. Successively, a Leave-One-Subject-Out Cross Validation was performed to validate the proposed algorithm. The obtained experimental results demonstrate that suitable ML-based processing strategies outperform the state-of-the-art techniques in terms of classification accuracy. Furthermore, it was also shown that the adoption of an inter-subjective model successfully led to a decrease in the 3-σ uncertainty: this can facilitate future developments of ready-to-use systems

Effects of boundary conditions on irreversible dynamics

We present a simple one-dimensional Ising-type spin system on which we define a completely asymmetric Markovian single spin-flip dynamics. We study the system at a very low, yet non-zero, temperature and we show that for empty boundary conditions the Gibbs measure is stationary for such dynamics, while introducing in a single site a $+$ condition the stationary measure changes drastically, with macroscopical effects. We achieve this result defining an absolutely convergent series expansion of the stationary measure around the zero temperature system. Interesting combinatorial identities are involved in the proofs

Feasibility of a wearable reflectometric system for sensing skin hydration

One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are a number of well established systems that offer adequate solutions for real-time, continuous patient monitoring. On the other hand, monitoring skin hydration still remains a challenging task. The continuous monitoring of this physiological parameter is extremely important in several contexts, for example for athletes, sick people, workers in hostile environments or for the elderly. State-of-the-art systems, however, exhibit some limitations, especially related with the possibility of continuous, real-time monitoring. Starting from these considerations, in this work, the feasibility of an innovative time-domain reflectometry (TDR)-based wearable, skin hydration sensing system for real-time, continuous monitoring of skin hydration level was investigated. The applicability of the proposed system was demonstrated, first, through experimental tests on reference substances, then, directly on human skin. The obtained results demonstrate the TDR technique and the proposed system holds unexplored potential for the aforementioned purposes

Positioning by multicell fingerprinting in urban NB-IoT networks

Narrowband Internet of Things (NB-IoT) has quickly become a leading technology in the deployment of IoT systems and services, owing to its appealing features in terms of coverage and energy efficiency, as well as compatibility with existing mobile networks. Increasingly, IoT services and applications require location information to be paired with data collected by devices; NB-IoT still lacks, however, reliable positioning methods. Time-based techniques inherited from long-term evolution (LTE) are not yet widely available in existing networks and are expected to perform poorly on NB-IoT signals due to their narrow bandwidth. This investigation proposes a set of strategies for NB-IoT positioning based on fingerprinting that use coverage and radio information from multiple cells. The proposed strategies were evaluated on two large-scale datasets made available under an open-source license that include experimental data from multiple NB-IoT operators in two large cities: Oslo, Norway, and Rome, Italy. Results showed that the proposed strategies, using a combination of coverage and radio information from multiple cells, outperform current state-of-the-art approaches based on single cell fingerprinting, with a minimum average positioning error of about 20 m when using data for a single operator that was consistent across the two datasets vs. about 70 m for the current state-of-the-art approaches. The combination of data from multiple operators and data smoothing further improved positioning accuracy, leading to a minimum average positioning error below 15 m in both urban environments