A cybersecure P300-based brain-to-computer interface against noise-based and fake P300 cyberattacks

In a progressively interconnected world where the internet of things (IoT), ubiquitous computing, and artificial intelligence are leading to groundbreaking technology, cybersecurity remains an underdeveloped aspect. This is particularly alarming for brain-to-computer interfaces (BCIs), where hackers can threaten the user’s physical and psychological safety. In fact, standard algorithms currently employed in BCI systems are inadequate to deal with cyberattacks. In this paper, we propose a solution to improve the cybersecurity of BCI systems. As a case study, we focus on P300-based BCI systems using support vector machine (SVM) algorithms and EEG data. First, we verified that SVM algorithms are incapable of identifying hacking by simulating a set of cyberattacks using fake P300 signals and noise-based attacks. This was achieved by comparing the performance of several models when validated using real and hacked P300 datasets. Then, we implemented our solution to improve the cybersecurity of the system. The proposed solution is based on an EEG channel mixing approach to identify anomalies in the transmission channel due to hacking. Our study demonstrates that the proposed architecture can successfully identify 99.996% of simulated cyberattacks, implementing a dedicated counteraction that preserves most of BCI functions

Multiplexing pH and Temperature in a Molecular Biosensor

Robust and reliable measurements in electrochemical biosensing of molecules are crucial for personalized medicine. Electrochemical sensors based on cytochrome P450 can detect the large majority of drugs commonly used in pharmacological treatments. The same cytochrome can detect different substrates; each of them changes the electrochemical response of the enzyme in a specific manner. Our system exploits the measure of electrical potential to identify the drug type, while current measurements decode the drug concentration. Since potential and current are affected by pH and temperature, and since variations occur in the patient samples, we propose a novel design for multiplexing biosensing with pH and temperature control, which ensures more precise measurements for drugs identification and their quantification

A Novel Multi-Working Electrode Potentiostat for Electrochemical Detection of Metabolites

A novel single-chip and multiplexed read-out circuit for multi-electrode electrochemical sensors, in standard 0.18 μm UMC CMOS technology, is presented. The circuit is a part of a fully-integrated biochip (in design) for the detection of multiple metabolites. The proposed topology is based on the potentiostat approach, and it is devoted to detect currents within the range of 250 pA - 650 nA for an electrode active area of 0.25 mm2. The need of multi-metabolites monitoring asks for a system with multi-working electrodes. In the proposed configuration, switches select one working electrode at each clock phase, while the others are short-circuited to the reference one, in order to nullify the injected current inside the counter. Low noise and low energy topology (50μW at 1.5V of voltage supply) is employed for the control amplifier. The linearity of the proposed read-out circuit allows accuracy better than 0.1%

Apigliano. Un villaggio bizantino e medievale in Terra d’Otranto. I Reperti

Vari articoli che trattano le ricerche sul sito del villaggio medievale abbandonato di Apigliano, Martano (LE

L'area della conceria dell'isolato XII

Analisi stratigrafica di una conceria urbana di II secolo, a Salapia (Cerignola, FG): dalla sua costruzione alle fasi di abbandono e rifunzionalizzazione dell'area, nell'Altomedioevo

Salpi nel contesto del Tavoliere centro-meridionale: l'insediamento altomedievale, la rifondazione della civitas.

Ricostruzione delle fasi insediative altomedievali di una porzione dell'Insula XII della città romana di Salapia, alla luce delle ricerche archeologiche, partendo dal dato materiale di scavo

I reperti archeozoologici dell'Isolato XII

Analisi dei reperti faunistici di età tardoantica e altomedievale dall'isolato XII di Salapia: ricostruzione di allevamento, alimentazione e spazio antropico

Progetto di ricerca archeologica a San Lorenzo "in Carminiano" (Foggia). L'avvio dell'indagine e i primi risultati

*Pasquale Favia:Il sito di S.Lorenzo: i caratteri insediativi(p.533-544);Le indagini non invasive(544-547);Il saggio I(548-550);Conclusioni(554-556

An Embedded Framework for Fully Autonomous Object Manipulation in Robotic-Empowered Assisted Living

Most of the humanoid social robots currently diffused are designed only for verbal and animated interactions with users, and despite being equipped with two upper arms for interactive animation, they lack object manipulation capabilities. In this paper, we propose the MONOCULAR (eMbeddable autONomous ObjeCt manipULAtion Routines) framework, which implements a set of routines to add manipulation functionalities to social robots by exploiting the functional data fusion of two RGB cameras and a 3D depth sensor placed in the head frame. The framework is designed to: (i) localize specific objects to be manipulated via RGB cameras; (ii) define the characteristics of the shelf on which they are placed; and (iii) autonomously adapt approach and manipulation routines to avoid collisions and maximize grabbing accuracy. To localize the item on the shelf, MONOCULAR exploits an embeddable version of the You Only Look Once (YOLO) object detector. The RGB camera outcomes are also used to estimate the height of the shelf using an edge-detecting algorithm. Based on the item’s position and the estimated shelf height, MONOCULAR is designed to select between two possible routines that dynamically optimize the approach and object manipulation parameters according to the real-time analysis of RGB and 3D sensor frames. These two routines are optimized for a central or lateral approach to objects on a shelf. The MONOCULAR procedures are designed to be fully automatic, intrinsically protecting sensitive users’ data and stored home or hospital maps. MONOCULAR was optimized for Pepper by SoftBank Robotics. To characterize the proposed system, a case study in which Pepper is used as a drug delivery operator is proposed. The case study is divided into: (i) pharmaceutical package search; (ii) object approach and manipulation; and (iii) delivery operations. Experimental data showed that object manipulation routines for laterally placed objects achieves a best grabbing success rate of 96%, while the routine for centrally placed objects can reach 97% for a wide range of different shelf heights. Finally, a proof of concept is proposed here to demonstrate the applicability of the MONOCULAR framework in a real-life scenario