Behavioral Change Through Serious Gaming Approaches for Childhood Obesity Interventions.

Childhood obesity is a significant public health issue that can lead to a variety of physical and mental health implications. Serious games offer an innovative approach to address this challenge by reinforcing behaviors through interactive components. In this work, we explore the potential of serious games as a tool for facilitating behavior change in interventions to address childhood obesity.

Training and validating a treatment recommender with partial verification evidence.

Background: Current clinical decision support systems (DSS) are trained and validated on observational data from the clinic in which the DSS is going to be applied. This is problematic for treatments that have already been validated in a randomized clinical trial (RCT), but have not yet been introduced in any clinic. In this work, we report on a method for training and validating the DSS core before introduction to a clinic, using the RCT data themselves.

Permissioned blockchain network for proactive access control to electronic health records.

Background: As digital healthcare services handle increasingly more sensitive health data, robust access control methods are required. Especially in emergency conditions, where the patient's health situation is in peril, different healthcare providers associated with critical cases may need to be granted permission to acquire access to Electronic Health Records (EHRs) of patients. The research objective of this work is to develop a proactive access control method that can grant emergency clinicians access to sensitive health data, guaranteeing the integrity and security of the data, and generating trust without the need for a trusted third party.

Correction: Gligoric et al. IOTA-Based Distributed Ledger in the Mining Industry: Efficiency, Sustainability and Transparency. 2024, , 923.

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IOTA-Based Distributed Ledger in the Mining Industry: Efficiency, Sustainability and Transparency.

The paper presents a traceability framework founded upon a methodological approach specifically designed for the integration of the IOTA-based distributed ledger within the mining industry. This framework constitutes an initial stride towards the certification and labelling of sustainable material production. The efficacy of this methodology is subject to real-world evaluation within the framework of the European Commission funded project DIG_IT.

Small UAS Online Audio DOA Estimation and Real-Time Identification Using Machine Learning.

The wide range of unmanned aerial system (UAS) applications has led to a substantial increase in their numbers, giving rise to a whole new area of systems aiming at detecting and/or mitigating their potentially unauthorized activities. The majority of these proposed solutions for countering the aforementioned actions (C-UAS) include radar/RF/EO/IR/acoustic sensors, usually working in coordination. This work introduces a small UAS (sUAS) acoustic detection system based on an array of microphones, easily deployable and with moderate cost.

Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE.

The rise of modern gene expression profiling techniques, such as RNA-Seq, has generated a wealth of high-quality datasets spanning all fields of current biological research. The large data sets and the continually expanding applications for which they can be mined, such as the investigation of alternative splicing and others, have created novel challenges for data management, exploration, analysis, and visualization. Although a large variety of RNA-Seq data analysis software packages has emerged, both open-source and commercial, most fail to simultaneously address the above challenges, while they lack obvious functionalities, such as estimating RNA abundance over non-annotated genomic regions of interest in real time.

A Platform for Health Record Management of the Conscripts in the Hellenic Navy.

eMass project aims to digitalize the medical examination procedure of recruitment phase of conscripts in the Hellenic Navy. eMass integrates recruits' Electronic Health Record (EHR), while allows a pre-screening test, through portable telemedicine equipment. The data will be exploited to assess the individual's cardiovascular risk through appropriate digital tools and algorithms.

Clinical pharmacogenomics in action: design, assessment and implementation of a novel pharmacogenetic panel supporting drug selection for diseases of the central nervous system (CNS).

Background: Pharmacogenomics describes the link between gene variations (polymorphisms) and drug responses. In view of the implementation of precision medicine in personalized healthcare, pharmacogenetic tests have recently been introduced in the clinical practice. However, the translational aspects of such tests have been limited due to the lack of robust population-based evidence.

Using Big Data to Develop a Clinical Decision Support System for Tinnitus Treatment.

Tinnitus is a common symptom of a phantom sound perception with a considerable socioeconomic impact. Tinnitus pathophysiology is enigmatic and its significant heterogeneity reflects a wide spectrum of clinical manifestations, severity and annoyance among tinnitus sufferers. Although several interventions have been suggested, currently there is no universally accepted treatment.

Reconstruction of cochlea based on micro-CT and histological images of the human inner ear.

The study of the normal function and pathology of the inner ear has unique difficulties as it is inaccessible during life and, so, conventional techniques of pathologic studies such as biopsy and surgical excision are not feasible, without further impairing function. Mathematical modelling is therefore particularly attractive as a tool in researching the cochlea and its pathology. The first step towards efficient mathematical modelling is the reconstruction of an accurate three dimensional (3D) model of the cochlea that will be presented in this paper.

Miniature implantable antennas for biomedical telemetry: from simulation to realization.

We address numerical versus experimental design and testing of miniature implantable antennas for biomedical telemetry in the medical implant communications service band (402-405 MHz). A model of a novel miniature antenna is initially proposed for skin implantation, which includes varying parameters to deal with fabrication-specific details. An iterative design-and-testing methodology is further suggested to determine the parameter values that minimize deviations between numerical and experimental results.

Effect of frequency deviance direction on performance and mismatch negativity.

The mismatch negativity (MMN) component of the auditory event-related potential is associated with automatic perceptual inference concerning changes in auditory stimulation. Recent studies have addressed the question whether performance and MMN is affected by the direction of frequency deviance. In the present study, the frequency MMN and performance is investigated during an auditory identification task.

Mismatch task conditions and error related ERPs.

Background: The N200 component of event related potentials (ERPs) is considered an index of monitoring error related responses. The aim of the present work was to study the effect of mismatch conditions on the subjects' responses in an auditory identification task and their relation to the N200 of stimulus-locked ERPs.

Methods: An auditory identification task required to correctly map a horizontal slider onto an active frequency range by selecting a slider position that matched the stimulus tone in each trial.

Classification of event-related potentials associated with response errors in actors and observers based on autoregressive modeling.

Event-Related Potentials (ERPs) provide non-invasive measurements of the electrical activity on the scalp related to the processing of stimuli and preparation of responses by the brain. In this paper an ERP-signal classification method is proposed for discriminating between ERPs of correct and incorrect responses of actors and of observers seeing an actor making such responses. The classification method targeted signals containing error-related negativity (ERN) and error positivity (Pe) components, which are typically associated with error processing in the human brain.

Nonlinear modeling of the dynamic effects of infused insulin on glucose: comparison of compartmental with Volterra models.

This paper presents the results of a computational study that compares simulated compartmental (differential equation) and Volterra models of the dynamic effects of insulin on blood glucose concentration in humans. In the first approach, we employ the widely accepted "minimal model" and an augmented form of it, which incorporates the effect of insulin secretion by the pancreas, in order to represent the actual closed-loop operating conditions of the system, and in the second modeling approach, we employ the general class of Volterra-type models that are estimated from input-output data. We demonstrate both the equivalence between the two approaches analytically and the feasibility of obtaining accurate Volterra models from insulin-glucose data generated from the compartmental models.

The effect of remifentanil on respiratory variability, evaluated with dynamic modeling.

Opioid drugs disrupt signaling in the brain stem respiratory network affecting respiratory rhythm. We evaluated the influence of a steady-state infusion of a model opioid, remifentanil, on respiratory variability during spontaneous respiration in a group of 11 healthy human volunteers. We used dynamic linear and nonlinear models to examine the effects of remifentanil on both directions of the ventilatory loop, i.

Behavioral and brain pattern differences between acting and observing in an auditory task.

Background: Recent research has shown that errors seem to influence the patterns of brain activity. Additionally current notions support the idea that similar brain mechanisms are activated during acting and observing. The aim of the present study was to examine the patterns of brain activity of actors and observers elicited upon receiving feedback information of the actor's response.

The "Oncosimulator": a multilevel, clinically oriented simulation system of tumor growth and organism response to therapeutic schemes. Towards the clinical evaluation of in silico oncology.

The "Oncosimulator" is at the same time a concept of multilevel integrative cancer and (treatment affected) normal tissue biology, an algorithmic construct and a software tool which aims at supporting the clinician in the process of optimizing cancer treatment on the patient individualized basis. Additionally it is a platform for better understanding and exploring the natural phenomenon of cancer as well as training doctors and interested patients alike. In order to achieve all of these goals it has to undergo a thorough clinical optimization and validation process.

Application of the Kohonen network for automatic point correspondence in retinal images.

In this paper, an algorithm for automatic point correspondence is proposed towards retinal image registration. Given a pair of corresponding retinal images and a set of bifurcations or other salient points in one of the images, the algorithm detects effectively the set of corresponding points in the second image, by exploiting the properties of Kohonen's Self Organizing Maps and embedding them in a stochastic optimization procedure. The proposed algorithm was tested on 20 unimodal retinal pairs and the obtained results show an enhanced performance in terms of accuracy and robustness compared to the existing algorithm, on which it is based.

FDTD study of the focusing properties of a hybrid hyperthermia and radiometry imaging system using a realistic human head model.

Aim of this study is twofold; on one hand, the investigation of the focusing attributes of a microwave radiometry tomography system with the use of a realistic human head model and on the other hand, the system's ability to perform a hyperthermia treatment. The operation principle of the device is based on an ellipsoidal conductive wall cavity, which provides the required beamforming and focusing. The biological tissue under treatment and/or measurement is placed on one of the two focal points whereas on the other one, a radiating or receiving antenna, which measures the black body type radiation emitted from the head's tissue, is placed.

Nonlinear, multiple-input modeling of cerebral hemodynamics during baseline and hypercapnia in young and post-menopausal women.

Normal aging is associated with changes in the cardiovascular system and more specifically in cerebral circulation. Sex-dependent changes in cerebrovascular CO2 reactivity, which may be related to hormonal levels, have been also reported. We therefore examined cerebral hemodynamics, i.

Enhancing the focusing properties of a prototype non-invasive brain hyperthermia system: a simulation study.

Aim of this study is the improvement of the focusing properties of a prototype system for deep brain hyperthermia able to provide also passive measurements of temperature distributions inside the human body and especially the brain. One of the main modules of the system which ensures the necessary beamforming and focusing on the body and brain cortex areas of interest is the symmetrical axis ellipsoidal conductive wall cavity. The proposed system operates in a total non-invasive contactless passive manner and is designed to provide hyperthermia treatment and temperature monitoring.

Thoracic non-rigid registration combining self-organizing maps and radial basis functions.

An automatic three-dimensional non-rigid registration scheme is proposed in this paper and applied to thoracic computed tomography (CT) data of patients with stage III non-small cell lung cancer (NSCLC). According to the registration scheme, initially anatomical set of points such as the vertebral spine, the ribs, and shoulder blades are automatically segmented slice by slice from the two CT scans of the same patient in order to serve as interpolant points. Based on these extracted features, a rigid-body transformation is then applied to provide a pre-registration of the data.