A5105515708- EEG and Brain-Computer Interfaces
- Heart Rate Variability and Autonomic Control
- Non-Invasive Vital Sign Monitoring
- ECG Monitoring and Analysis
- Geometric and Algebraic Topology
- COVID-19 diagnosis using AI
- COVID-19 and healthcare impacts
- Sleep and related disorders
- Epilepsy research and treatment
- Functional Brain Connectivity Studies
- Advanced Chemical Sensor Technologies
- Radiology practices and education
- COVID-19 Clinical Research Studies
- Thermal and Kinetic Analysis
- Mental Health Research Topics
- Radiomics and Machine Learning in Medical Imaging
- Computational Physics and Python Applications
- Cardiac Fibrosis and Remodeling
- Bee Products Chemical Analysis
- Obstructive Sleep Apnea Research
- Hemodynamic Monitoring and Therapy
- Sensor Technology and Measurement Systems
- Green IT and Sustainability
- Geometry and complex manifolds
- Cardiac Arrest and Resuscitation
University of Verona
2023-2024
Arcispedale Sant'Anna
2019-2024
Istituto Nazionale di Fisica Nucleare, Galileo Galilei Institute for Theoretical Physics
2024
Istituto Nazionale di Fisica Nucleare
2024
University of Ferrara
2020-2023
Massachusetts Institute of Technology
2017
New York University
2017
Consorzio di Bioingegneria e Informatica Medica
2016
Politecnico di Milano
2010-2015
Instituto Politécnico Nacional
2014
New devices are needed for monitoring seizures, especially those associated with sudden unexpected death in epilepsy (SUDEP). They must be unobtrusive and automated, provide false alarm rates (FARs) bearable everyday life. This study quantifies the performance of new multimodal wrist-worn convulsive seizure detectors.Hand-annotated video-electroencephalographic events were collected from 69 patients at six clinical sites. Three different wristbands used to record electrodermal activity (EDA)...
Discrimination of honey based on geographical origin is a common fraudulent practice and one the most investigated topics in authentication. This research aims to discriminate honeys according their by combining elemental fingerprinting with machine-learning techniques. In particular, main objective this study distinguish unifloral multifloral produced neighboring regions, such as Sardinia (Italy) Spain. The compositions 247 were determined using Inductively Coupled Plasma Mass Spectrometry...
We report a probable sudden unexpected death in epilepsy (SUDEP) 20-year-old man wearing smartwatch that recorded wrist motion via 3-axis accelerometer (ACC) and electrodermal activity (EDA). EDA reflects sympathetic without parasympathetic antagonism.1 The (Empatica [Milan, Italy] Embrace, with CE Medical clearance from the European Union for seizure detection) issued an alert, received by caregiver at 8:50 am, indicating convulsive seizure. An adult trained cardiopulmonary resuscitation...
This study presents different methods for automatic sleep classification based on heart rate variability (HRV), respiration and movement signals recorded through bed sensors. Two feature extraction have been implemented: time variant-autoregressive model (TVAM) wavelet discrete transform (WDT); the obtained features are fed into two classifiers: Quadratic (QD) Linear (LD) discriminant staging in REM, nonREM WAKE periods. The performances of all possible combinations extractors classifiers...
We prove that the Bridson-Dison group has quartic Dehn function, thereby providing first precise computation of function a subgroup direct product free groups with super-quadratic function. also coabelian subgroups products $n$ finiteness type $\mathcal{F}_{n-1}$ and corank $r\leq n-2$ have quadratic functions.
In the present paper we propose a methodology for assessment of autonomic nervous system (ANS) in patients affected by bipolar disorder. ANS was explored means heart rate variability (HRV) analysis carried out during night recordings through evaluation many different parameters time and frequency domain, linear non-linear. The recording signals performed wearable sensorized T-shirt. HRV with movement allowed also sleep staging estimation REM percentage over total time. A group 8 normal...
Respiratory diseases such as chronic obstructive pulmonary disease, sleep apnea syndrome, and COVID-19 may cause a decrease in arterial oxygen saturation (SaO2). The continuous monitoring of levels be beneficial for the early detection hypoxemia timely intervention. Wearable non-invasive pulse oximetry devices measuring peripheral (SpO2) have been garnering increasing popularity. However, there is still strong need extended robust clinical validation devices, especially to address topical...
This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from particle detector. The begins with local reconstruction algorithm, employing neural networks on FPGA as its first stage. Subsequent preparation and anomaly detection stages are accelerated using GPGPUs. As practical demonstration detection, we have developed quality monitoring application cosmic muon Its primary objective is detect...
The purpose of the present work is to examine, on a clinically diverse population older adults (N = 46) sleeping at home, performance two actigraphy-based sleep tracking algorithms (i.e., Actigraphy-based Sleep algorithm, ACT-S1 and Sadeh’s algorithm) compared manually scored electroencephalography-based PSG (PSG-EEG). allows for fully automatic identification period time (SPT) within identified period, sleep-wake classification. SPT detected by did not differ statistically from using...
Automatic detection of the sleep macrostructure (Wake, NREM -non Rapid Eye Movement- and REM-Rapid Movement-) based on bed sensor signals is presented. This study assesses feasibility different methodologies to evaluate quality out centers. The compares a) features extracted from time-variant autoregressive modeling (TVAM) Wavelet Decomposition (WD) b) performance K-Nearest Neighbor (KNN) Feed Forward Neural Networks (FFNN) classifiers. In current analysis, 17 full polysomnography recordings...
Lempel-Ziv Complexity (LZC) has been demonstrated to be a powerful complexity measure in several biomedical applications. During sleep, it is still not clear how many samples are required ensure robustness of its estimate when computed on beat-to-beat interval series (RR). The aims this study were: i) evaluation the number necessary different sleep stages for reliable estimation LZC; ii) LZC considering inter-subject variability; and iii) comparison between Sample Entropy (SampEn). Both...
Obesity is associated with cardiovascular mortality. Linear methods, including time domain and frequency analysis, are normally applied on the heart rate variability (HRV) signal to investigate autonomic control, whose imbalance might promote disease in these patients. However, given cardiac activity non-linearities, non-linear methods provide better insight. HRV complexity was hereby analyzed during wakefulness different sleep stages healthy obese subjects. Given short duration of each...
We construct some cusped finite-volume hyperbolic $n$-manifolds $M_n$ that fiber algebraically in all the dimensions $5\leq n \leq 8$. That is, there is a surjective homomorphism $\pi_1(M_n) \to \mathbb Z$ with finitely generated kernel. The kernel also presented $n=7, 8$, and this leads to first examples of $\widetilde M_n$ whose fundamental group but not finite type. These have infinitely many cusps maximal rank hence infinite Betti number $b_{n-1}$. They cover manifold $M_n$. obtain these...
The aim of this study is the evaluation autonomic regulations during depressive stages in bipolar patients order to test new quantitative and objective measures detect such events. A sensorized T-shirt was used record ECG signal body movements night, from which HRV data sleep macrostructure were estimated analyzed. 9 out 20 features extracted resulted be significant (p<;0.05) discriminating among non-depressive states. Such are representation dynamics both linear non-linear domain parameters...
The aim of this work is the creation a completely automatic method for extraction informative parameters from peripheral signals recorded through sensorized T-shirt. acquired data belong to patients affected bipolar disorder, and consist RR series, body movements activity type. extracted features, i.e. linear non-linear HRV in time domain, frequency indicative sleep quality, profile fragmentation, are interest classification clinical mood state. analysis dataset, which be performed online...
The aim of this study was the optimization Time-Variant Autoregressive Models (TVAM) for tracking REM - non transitions during sleep, through analysis spectral indexes extracted from tachograms. A first improvement TVAM achieved by choosing best typology forgetting factor in a tachogram obtained sitting-to-standing test; then, method improving robustness AR recursive identification with respect to outliers selected analyzing an ectopic beat. variable according Fortescue and specific...
Subgroups of direct products finitely many generated free groups form a natural class that plays an important role in geometric group theory. Its members include fundamental examples, such as the Stallings-Bieri groups. This raises problem understanding their invariants. We prove presented subgroups three groups, well finiteness type $\mathcal{F}_{n-1}$ product $n$ have Dehn function bounded above by $N^9$. gives positive answer to question Dison within these subclasses and provides new...