A5021472133- Heart Rate Variability and Autonomic Control
- Non-Invasive Vital Sign Monitoring
- Health Systems, Economic Evaluations, Quality of Life
- Quality and Safety in Healthcare
- ECG Monitoring and Analysis
- Biomedical and Engineering Education
- Artificial Intelligence in Healthcare and Education
- Balance, Gait, and Falls Prevention
- Blood Pressure and Hypertension Studies
- Context-Aware Activity Recognition Systems
- Diabetes Management and Research
- Artificial Intelligence in Healthcare
- IoT and Edge/Fog Computing
- Technology Assessment and Management
- Pharmaceutical Economics and Policy
- Mobile Health and mHealth Applications
- Telemedicine and Telehealth Implementation
- EEG and Brain-Computer Interfaces
- Healthcare Technology and Patient Monitoring
- COVID-19 diagnosis using AI
- Chronic Disease Management Strategies
- COVID-19 epidemiological studies
- Cardiovascular and exercise physiology
- Mental Health Research Topics
- Vaccine Coverage and Hesitancy
University of Warwick
2016-2025
Università Campus Bio-Medico
2022-2025
Intelligent Health (United Kingdom)
2025
Campus Bio Medico University Hospital
2024
Engineering (Italy)
2023-2024
International Diabetes Federation
2024
European Society of Intensive Care Medicine
2024
World Health Organization
2022-2023
University of York
2021
Coventry University
2017
This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes classifier based on nonlinear features HRV for automatic stress detection. 42 students volunteered participate about stress. For each student, two recordings were performed: one during an on-going university examination, assumed as stressor, after holidays. Nonlinear analysis was performed by using Poincaré Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation...
This paper suggests a method to assess the extent which ultra-short Heart Rate Variability (HRV) features (less than 5 min) can be considered as valid surrogates of short HRV (nominally min). Short term analysis has been widely investigated for mental stress assessment, whereas validity remains unclear. Therefore, this study proposes explore excerpts shortened without losing their ability automatically detect stress. ECGs were acquired from 42 healthy subjects during university examination...
Abstract Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight monitoring reduces risk of hypoglycemia, which can result a series complications, especially patients, such as confusion, irritability, seizure even be fatal specific conditions. Hypoglycemia affects electrophysiology heart. However, due to strong inter-subject heterogeneity, previous studies based on cohort failed deploy electrocardiogram (ECG)-based hypoglycemic...
This study aims to develop an automatic classifier for risk assessment in patients suffering from congestive heart failure (CHF). The proposed separates lower higher ones, using standard long-term rate variability (HRV) measures. Patients are labeled as or according the New York Heart Association classification (NYHA). A retrospective analysis on two public Holter databases was performed, analyzing data of 12 mild CHF (NYHA I and II), risk, 32 severe III IV), risk. Only with a fraction total...
There is consensus that Heart Rate Variability associated with the risk of vascular events. However, predictive value for events not completely clear. The aim this study to develop novel models based on data-mining algorithms provide an automatic stratification tool hypertensive patients.A database 139 Holter recordings clinical data patients followed up at least 12 months were collected ad hoc. Subjects who experienced a event (i.e., myocardial infarction, stroke, syncopal event) considered...
Approximate entropy (ApEn) and sample (SampEn) have been previously used to quantify the regularity in centre of pressure (COP) time-series different experimental groups and/or conditions. ApEn SampEn are very sensitive their input parameters: m (subseries length), r (tolerance) N (data length). Yet, effects changing those parameters scarcely investigated analysis COP time-series. This study aimed investigate m, on values time-series, as well ability these measures discriminate between...
Recently, the application of neuroscience methods and findings to study organizational phenomena has gained significant interest converged in emerging field neuroscience. Yet, this body research principally focused on brain, often overlooking fuller analysis activities human nervous system associated available assess them. In article, we aim narrow gap by reviewing heart rate variability (HRV) analysis, which is that set assessing beat-to-beat changes rhythm over time, used draw inference...
Ultra-short heart rate variability (HRV) analysis refers to the study of HRV features in excerpts length <5 min. is widely growing many healthcare applications for monitoring individual's health and well-being status, especially combination with wearable sensors, mobile phones, smart-watches. Long-term (nominally 24 h) short-term 5 min) have been investigated, physiologically justified clear guidelines analysing min or h are available. Conversely, reliability ultra-short remains unclear...
Pneumonia is a leading cause of mortality in limited resource settings (LRS), which are common low- and middle-income countries (LMICs). Accurate referrals can reduce the devastating impact pneumonia, especially LRS. Discriminating pneumonia from other respiratory conditions based only on symptoms major challenge. Machine learning has shown promise overcoming diagnostic difficulties (i.e., low specificity symptoms, lack accessible tests varied clinical presentation). Many scientific papers...
Background and study aims Endoscopic ultrasound-guided through-the-needle biopsy (TTNB) of pancreatic cystic lesions (PCLs) is associated with a non-negligible risk for adverse events (AEs). We aimed to identify the hierarchic interaction among independent predictors TTNB-related AEs generate prognostic model using recursive partitioning analysis (RPA). Patients methods Multicenter retrospective 506 patients PCLs who underwent TTNB. RPA was performed validated by means bootstrap resampling....
The use of AI in healthcare has sparked much debate among philosophers, ethicists, regulators and policymakers who raised concerns about the implications such technologies. presented scoping review captures progression ethical legal proposed frameworks available concerning AI-based medical technologies, capturing key themes across a wide range contexts. dimensions are synthesised order to produce coherent framework for highlighting how transparency, accountability, confidentiality, autonomy,...
Disease Management Programs (DMPs), which use no advanced ICT, are as effective telemedicine but more efficient because less costly.We proposed a platform to enhance effectiveness and efficiency of home monitoring using data mining for early detection any worsening in patient's condition.These could require complex expensive care if not recognized.In this paper, we briefly describe the Remote Health Monitoring (RHM) designed realized, supports Heart Failure (HF) severity assessment offering...
Summary Background: A gap exists between evidence-based medicine and clinical-practice. Every day, healthcare professionals (HCPs) combine empirical evidence subjective experience in order to maximize the effectiveness of interventions. Consequently, it is important understand how HCPs interpret research apply everyday practice. We focused on prevention falls, a common cause injury-related morbidity mortality later life, for which there wide range known risk factors. Objectives: To use...
In this study, we investigated the discrimination power of short-term heart rate variability (HRV) for discriminating normal subjects versus chronic failure (CHF) patients. We analyzed 1914.40 h ECG 83 patients which 54 are and 29 suffering from CHF with New York Heart Association (NYHA) classification I, II, III, extracted by public databases. Following guidelines, performed time frequency analysis in order to measure HRV features. To assess features, designed a classifier based on...
The rigorous elicitation of user needs is a crucial step for both medical device design and purchasing. However, often based on qualitative methods whose findings can be difficult to integrate into decision-making. This paper describes the application AHP elicit new CT scanner use in public hospital. was used hierarchy 12 scanner, grouped 4 homogenous categories, prepare questionnaire investigate relative priorities these. completed by 5 senior clinicians working variety clinical...
Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minutes) HRV not. This study aims to detect mental using linear non-linear features extracted from 3 minutes ECG excerpts recorded 42 university students, during oral examination (stress) at rest after a vacation. were then analyzed according literature validated...
Abstract COVID-19 pandemic is plaguing the world and representing most significant stress test for many national healthcare systems services, since their foundation. The supply-chain disruption unprecedented request intensive care unit (ICU) beds have created in Europe conditions typical of low-resources settings. This generated a remarkable race to find solutions prevention, treatment management this disease which involving large amount people. Every day, new Do-It-Yourself (DIY) regarding...