Pasquale Arpaia

University of Naples Federico II | UNINA · Department of Electrical Engineering and Information Technology

In this paper, a digital-measurement method for low-invasive clinical diagnosis of metallic prosthesis osseointegration is proposed. Electrical impedance spectroscopy is exploited to characterize the quality of the tissue at the interface between the bone and the prosthesis. The method overcomes current resolution limits of biological electrical-im...

A framework for easily developing software for measurement and test applications under highly and fast-varying requirements is proposed. The framework allows the software quality, in terms of flexibility, usability, and maintainability, to be maximized. Furthermore, the development effort is reduced and finalized, by relieving the test engineer of...

a b s t r a c t A measurement technique based on Electrical Impedance Spectroscopy (EIS) aimed at dis-criminating electrical effects of the electrical treatment from the electrical characteristics of drug delivery in human skin is presented. The technique turns out to be useful as the first and most crucial step in determining the drug delivered in...

A method is proposed to center and align solenoids by means of a vibrating wire. The magnetic axis of a solenoid is defined as the path where the integral over the transversal field components takes its minimum. The wire, fed by an alternating current, oscillates in a plane that is perpendicular to the transversal magnetic field. When the wire posi...

This work addresses the adoption of Machine Learning classifiers and Convolutional Neural Networks to improve the performance of highly wearable, single-channel instrumentation for Brain-Computer Interfaces. The proposed measurement system is based on the classification of Steady- State Visually Evoked Potentials (SSVEPs). In particular, Head-Mount...

This book presents a complete overview of the main EEG-based Brain-Computer Interface (BCI) paradigms and the related practical solutions for their design, prototyping, and testing. Readers will explore active, reactive, and passive BCI paradigms, with an emphasis on the operation for developing solutions, addressing the need for customization. Re...

Three levels of fear of heights were detected in subjects with different severities of acrophobia, based on the electroencephalographic (EEG) and electrocardiographic (ECG) signals. The study aims to demonstrate the feasibility of a data-fusion-based method for real-time assessment of the fear of heights intensity to integrate into adaptive Virtual...

A real-time calibration to enhance the inter-subject reproducibility of insulin bioavailability measurements was proposed and validated on a diabetic patient with more than 49000 impedance values. The measurement method monitors drug absorption through a transducer consisting of a sensitive material (human abdominal tissue) and an impedance spectro...

Background: Executive functions (EFs) are neurocognitive processes planning and regulating daily life actions. Performance of two simultaneous tasks, requiring the same cognitive resources, lead to a cognitive fatigue. Several studies investigated cognitive-motor task and the interference during walking, highlighting an increasing risk of falls esp...

Objective: Recent trends in brain-computer interface (BCI) research concern the passive monitoring of brain activity, which aim to monitor a wide variety of cognitive states. Engagement is such a cognitive state, which is of interest in contexts such as learning, entertainment or rehabilitation. This study proposes a novel approach for real-time es...

Type 1 diabetes mellitus (T1DM) is characterized by insulin deficiency and blood sugar control issues. The state-of-the-art solution is the artificial pancreas (AP), which integrates basal insulin delivery and glucose monitoring. However, APs are unable to manage postprandial glucose response (PGR) due to limited knowledge of its determinants, requ...

A neurofeedback (NF)-supported training is proposed to enable neurosurgeons to learn how to regulate their emotions. Electroencephalographic (EEG) signal and heart rate (HR) of 5 neurosurgeons were acquired in 4 sessions while performing NF-based emotion regulation (ER). Subjects tried to counteract anxious and stressful states through NF, that is...

In particle accelerators devoted to hadron therapy treatments, the magnet design plays an essential role in ensuring the safety of the patients under treatment. An incorrect setting or malfunctioning may cause damage to healthy tissues and cells. Due to their nature, superconducting magnets can undergo a drastic state-change, namely the quench. Whe...

A hybrid method is proposed for removing artifacts from electroencephalographic (EEG) signals. This relies on the integration of artifact subspace reconstruction (ASR) with multivariate empirical mode decomposition. The method can be applied when few EEG sensors are available, a condition in which existing techniques are not effective, and it was t...

A relationship emerged between the progress in performing neurofeedback exercises for emotional regulation and the trend of the \(\mu \)-band power spectral density from the bipolar channel FC4-CP4. The exploratory study involved 3 subjects. As emerged in previous studies on the analysis of the emotional response in the motor cortex, the significan...

A pilot study aimed to assess the usability of an adaptive multisensory virtual reality (VR) system for emotional self-regulation is presented. The neurofeedback relies on electroencephalography (EEG) and is proposed to participants for strengthening the anxiety regulation capacity, by following the task to down-regulate the high-beta band measured...

In the present study, an electrocardiographic (ECG) -based system is proposed for the classification of three levels of fear of heights. A virtual reality (VR) environment was employed for the gradual exposure of the participants to the fear arousing stimuli. The VR scenario consists of a canyon in which a wooden lift brings the subjects to three d...

Brain-Computer Interfaces (BCIs) are an integration of hardware and software communication systems that allow a direct communication path between the human brain and external devices. Among the existing BCI paradigms, Steady-State Visually Evoked Potentials (SSVEPs) have gained momentum in the development of non-invasive BCI applications as they ar...

p>In this study, an EEG-based investigation of different levels of executive function activation (e.g., inhibition and working memory) during walking is performed in order to understand the executive funcions specifically involved during walking. Subjects were asked to perform the cognitive tasks by holding a wireless controller with their right ha...

p>In this study, an EEG-based investigation of different levels of executive function activation (e.g., inhibition and working memory) during walking is performed in order to understand the executive funcions specifically involved during walking. Subjects were asked to perform the cognitive tasks by holding a wireless controller with their right ha...

The present study introduces a brain–computer interface designed and prototyped to be wearable and usable in daily life. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improve the online detection of neurological phenomena....

The potential of motor imagery-based braincomputer interfaces (BCIs) is hindered by long calibration times. Therefore, this study investigates a classification model that minimises BCI calibration time while maximising its accuracy by exploiting transfer learning. To this end, a modified version of the Sinc-EEGNet architecture is proposed. Analyses...

A feasibility study on electroencephalographic monitoring of executive functions during dual (motor and cognitive) task execution is presented. Electroencephalographic (EEG) signals are acquired by means of a wearable device with few channels and dry electrodes. The light weight and wireless device allow for walking in a natural way. The most signi...

The cyber-security of an embedded device is a crucial issue especially in the Internet of Things (IoT) paradigm, since the physical accessibility to the smart transducers eases an attacker to eavesdrop the exchanged messages. In this manuscript, the role of metrology in improving the characterization and security testing of embedded devices is disc...

The present study illustrates a brain-computer interface designed and developed to be wearable, portable, and user-friendly. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improve the detection of neurological phenomena. Twe...

Sustainability has gained significant relevance in every sector. In particular, in information and communication technology (ICT), there is growing attention towards this aspect. Measurement systems are arguably one of the numerous manifestations of ICTs, and they are virtually ubiquitous in the current 4.0 Era. This pervasiveness leads to ponder o...

This folder contains scripts for replicating the analysis of the paper "Visual and haptic feedback in detecting motor imagery within a wearable brain–computer interface".

Type 1 Diabetes (T1D) is an autoimmune disease that affects millions of people worldwide. A critical issue in T1D patients is the managing of Postprandial Glucose Response (PGR), through the dosing of the insulin bolus to inject before meals. The Artificial Pancreas (AP), combining autonomous insulin delivery and blood glucose monitoring, is a prom...

A bioimpedance transducer is proposed for non-invasive monitoring of insulin bioavailability after subcutaneous injection. The insulin bioavailability is assessed indirectly by measuring the local impedance variation due to the drug disappearance from the injection volume. The instrument allows to manage the extreme variability in insulin response...

This work addresses the employment of Machine Learning (ML) and Domain Adaptation (DA) in the framework of Brain-Computer Interfaces (BCIs) based on Steady-State Visually Evoked Potentials (SSVEPs). Currently, all the state-of-the-art classification strategies do not consider the high non-stationarity typical of brain signals. This can lead to poor...

The present work concerns side-channel attacks on cryptographic devices protected with the advanced encryption standard. In this regard, the assessment of guessing entropy and the related uncertainty is proposed for machine learning-based attacks based on power measurements. For the first time, the guessing entropy was assessed on the entire key wh...

In the frame of the Next Generation Europe program, the EU program to boost after-covid recovery, the Italian Minister of University and Research has funded a project called IRIS (Innovative Research Infrastructure for applied Superconductivity). New laboratories will be built or upgraded in six poles: Milan (hub of the infrastructure), Genoa, Fras...

A systematic review on machine-learning strategies for improving generalizability (cross-subjects and cross-sessions) electroencephalography (EEG) based in emotion classification was realized. In this context, the non-stationarity of EEG signals is a critical issue and can lead to the Dataset Shift problem. Several architectures and methods have be...

This paper presents a wearable brain-computer interface relying on neurofeedback in extended reality for the enhancement of motor imagery training. Visual and vibrotactile feedback modalities were evaluated when presented either singularly or simultaneously. Only three acquisition channels and state-of-the-art vibrotactile chest-based feedback were...

Rotating-coil measurement systems are widely used to measure the multipolar fields of particle accelerator magnets. This paper presents a rotating-coil measurement system that aims at providing a complete data set for the characterization of quadrupole magnets with small bore diameters (26 mm). The PCB magnetometer design represents a challenging g...

An electroencephalography-based detection system of emotional states exploiting few dry channels is proposed. The circumplex model of affect was the reference theory adopted and the standardized dataset International Affective Picture System IAPS was exploited for emotion elicitation. A subset of stimuli polarized on both the valence and the arousa...

The sense of body ownership, i.e., the experience of one’s body as one’s own, and the sense of agency, i.e., the feeling of control over bodily actions, are essential for bodily self-consciousness. Research on EEG-based brain-computer interface (BCI) has shown that individuals can retain a sense of agency and ownership even when they control virtua...

A feasibility of Mindfulness-based emotional acceptance in combination with neurofeedback for improving emotion selfregulation is presented. This represents, to our knowledge, an unexplored approach in the emotion regulation literature. The study was performed using a low-cost wearable system designed to perform electroencephalography (EEG) outside...

An innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon’s subjective assessment. As...

A sensory feedback was employed for the present work to remap brain signals into sensory information. In particular, sensorimotor rhythms associated with motor imagery were measured as a mean to interact with an extended reality (XR) environment. The aim for such a neurofeedback was to let the user become aware of his/her ability to imagine a movem...

A pilot study to investigate possible differences between a virtual reality-based neurofeedback and a traditional neurofeedback is presented. Neurofeedback training aimed to strengthen the emotional regulation capacity. The neurofeedback task is to down-regulate negative emotions by decreasing the beta band power measured in the midline areas of th...

A method to detect the presence of infection after Total Joint Arthroplasty is presented. The method is based on Electrical Bioimpedance Spectroscopy and guarantees low latency, non-invasiveness, and cheapness with respect to the state of art. Experimental measurements were carried out on a singular patient who had already undergone bilateral Total...

A systematic review on electroencephalographic (EEG)-based feature extraction strategies to diagnosis and therapy of attention deficit hyperactivity disorder (ADHD) in children is presented. The analysis is realized at an executive function level to improve the research of neurocorrelates of heterogeneous disorders such as ADHD. The Quality Assessm...

This paper proposes a comparison between artifact removal techniques applied to real electroencephalographic data. The aim was to investigate the most suitable technique for artifact removal with a focus on wearability, portability, and low cost of the final system. A particular focus was thus put on the usage of few channels as a key feature to de...

The human sense of smell is important for many vital functions, but with the current state of the art, there is a lack of objective and non-invasive methods for smell disorder diagnostics. In recent years, increasing attention is being paid to olfactory event-related potentials (OERPs) of the brain, as a viable tool for the objective assessment of...

Objective . Processing strategies are analysed with respect to the classification of electroencephalographic signals related to brain-computer interfaces based on motor imagery. A review of literature is carried out to understand the achievements in motor imagery classification, the most promising trends, and the challenges in replicating these res...

An extended-reality (XR) platform for real-time monitoring of patients’ health during surgical procedures is proposed. The proposed system provides real-time access to a comprehensive set of patients’ information, which are made promptly available to the surgical team in the operating room (OR). In particular, the XR platform supports the medical s...

These data concern experiments with steady-state visually evoked potentials. You can find more in the related paper and in the GitHub repository https://github.com/anthonyesp/SSVEPcharacterization.git

A wearable system for the personalized EEG-based detection of engagement in learning 4.0 is proposed. In particular, the effectiveness of the proposed solution is assessed by means of the classification accuracy in predicting engagement. The system can be used to make an automated teaching platform adaptable to the user, by managing eventual drops...

This work addresses an innovative processing strategy to improve the classification of Steady-State Visually Evoked Potentials (SSVEPs). This strategy resorts to the combined use of fast Fourier transform and Canonical Correlation Analysis in time domain, and manages to outperform by over 5% previous results obtained for highly wearable, single-cha...

Objectives Technology is increasingly being used to help practise mindfulness. Immersive virtual reality-enhanced mindfulness may prove especially effective for a wide range of clinical interventions where traditional mindfulness is currently proving valuable. The current paper provides a preliminary survey of research on this topic, aimed at verif...

This zip folder contains measurement results associated with flicering icons on the Epson Moverio BT200. Further details about the experimental setup and the analysis can be found in the linked research paper.

This zip folder contains measurement results associated with flicering icons on the Microsoft Hololens 1. Further details about the experimental setup and the analysis can be found in the linked research paper.

This zip folder contains measurement results associated with flicering icons on the Epson Moverio BT350. Further details about the experimental setup and the analysis can be found in the linked research paper.

This zip folder contains measurement results associated with flicering icons on the Epson Moverio BT200. Further details about the experimental setup and the analysis can be found in the linked research paper.

This zip folder contains measurement results associated with flicering icons on the Microsoft Hololens 1. Further details about the experimental setup and the analysis can be found in the linked research paper.

With this Matlab script, the results obtained in the linked research paper can be replicated. In particular, flickering is visualized in the time and frequency domains The script was implemented in Matlab R2020b, but it can be compatible with previous versions. Don't forget to also download the zip folders containing .mat files for executing the a...

This zip folder contains measurement results associated with flicering icons on the Epson Moverio BT350. Further details about the experimental setup and the analysis can be found in the linked research paper.