Battle Against Your Fears: Virtual Reality Serious Games and Physiological Analysis for Phobia Treatment.

Advancements in virtual reality (VR) technology have enabled its use to assist in multiple fields. This study introduces a comprehensive framework designed to support exposure therapy through a series of VR serious games and physiological monitoring. It relies on a generic architecture, allowing for the modification of VR stimuli according to different phobias (e.

Extraction of compression indices from maternal-fetal heart rate simultaneous signals.

Intrapartum asphyxia is responsible for approximately 900 000 deaths per year worldwide. These numbers show the urgency of investing in the quality of fetal health care. The heart rate signal is a complex signal and sometimes behaves unpredictably.

Remote Emotion Recognition Using Continuous-Wave Bio-Radar System.

The Bio-Radar is herein presented as a non-contact radar system able to capture vital signs remotely without requiring any physical contact with the subject. In this work, the ability to use the proposed system for emotion recognition is verified by comparing its performance on identifying fear, happiness and a neutral condition, with certified measuring equipment. For this purpose, machine learning algorithms were applied to the respiratory and cardiac signals captured simultaneously by the radar and the referenced contact-based system.

Host Soluble Factors Cause Changes in Antibiotic Susceptibility and Biofilm Formation Ability.

is a major nosocomial pathogen with a remarkable ability to adhere to the surfaces of indwelling medical devices and form biofilms. Unlike other nosocomial pathogens, the interaction of with host factors has not been the focus of substantial research. This study aimed to assess the alterations in the antibiotic susceptibility and biofilm formation ability of in the presence of host serum factors.

Time series big data: a survey on data stream frameworks, analysis and algorithms.

Big data has a substantial role nowadays, and its importance has significantly increased over the last decade. Big data's biggest advantages are providing knowledge, supporting the decision-making process, and improving the use of resources, services, and infrastructures. The potential of big data increases when we apply it in real-time by providing real-time analysis, predictions, and forecasts, among many other applications.

Analysis of Physiological Responses during Pain Induction.

Pain is a complex phenomenon that arises from the interaction of multiple neuroanatomic and neurochemical systems with several cognitive and affective processes. Nowadays, the assessment of pain intensity still relies on the use of self-reports. However, recent research has shown a connection between the perception of pain and exacerbated stress response in the Autonomic Nervous System.

Transcriptome Mining to Identify Molecular Markers for the Diagnosis of Bloodstream Infections.

Bloodstream infections caused by are often misdiagnosed since no diagnostic marker found so far can unequivocally discriminate "true" infection from sample contamination. While attempts have been made to find genomic and/or phenotypic differences between invasive and commensal isolates, possible changes in the transcriptome of these isolates under in vivo-mimicking conditions have not been investigated. Herein, we characterized the transcriptome, by RNA sequencing, of three clinical and three commensal isolates after 2 h of exposure to whole human blood.

Multidimensional assessment of anxiety through the State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA): From dimensionality to response prediction across emotional contexts.

The assessment of mal-adaptive anxiety is crucial, considering the associated personal, economic, and societal burden. The State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA) is a self-report instrument developed to provide multidimensional anxiety assessment in four dimensions: trait-cognitive, trait-somatic, state-cognitive and state-somatic. This research aimed to extend STICSA's psychometric studies through the assessment of its dimensionality, reliability, measurement invariance and nomological validity in the Portuguese population.

On the Impact of the Data Acquisition Protocol on ECG Biometric Identification.

Electrocardiographic (ECG) signals have been used for clinical purposes for a long time. Notwithstanding, they may also be used as the input for a biometric identification system. Several studies, as well as some prototypes, are already based on this principle.

: A Quick Review on Identification, Current Treatments, and Challenges.

is a novel and major fungal pathogen that has triggered several outbreaks in the last decade. The few drugs available to treat fungal diseases, the fact that this yeast has a high rate of multidrug resistance and the occurrence of misleading identifications, and the ability of forming biofilms (naturally more resistant to drugs) has made treatments of infections highly difficult. This review intends to quickly illustrate the main issues in identification, available treatments and the associated mechanisms of resistance, and the novel and alternative treatment and drugs (natural and synthetic) that have been recently reported.

Optimizing a reliable ex vivo human blood model to analyze expression of genes.

Human blood is often used as an ex vivo model to mimic the environment encountered by pathogens inside the host. A significant variety of experimental conditions has been reported. However, optimization strategies are often not described.

Multimodal Emotion Evaluation: A Physiological Model for Cost-Effective Emotion Classification.

Emotional responses are associated with distinct body alterations and are crucial to foster adaptive responses, well-being, and survival. Emotion identification may improve peoples' emotion regulation strategies and interaction with multiple life contexts. Several studies have investigated emotion classification systems, but most of them are based on the analysis of only one, a few, or isolated physiological signals.

The feasibility of an augment reality system to study the psychophysiological correlates of fear-related responses.

Background: Previous studies have successfully used augmented reality (AR) as an aid to exposure-based treatments for anxiety disorders. However, to the best of our knowledge, none of these studies have measured the physiological correlates of the fear response, relying solely on self-reports and behavioral avoidance tests.

Methods: As the physiological defensive reactivity pattern impacts on the treatment effectiveness, we tested the feasibility of an AR system integrated in a mobile and wearable device for assessing the psychophysiological mechanisms (heart rate) involved in fear responses in real-life contexts.

Biometric and Emotion Identification: An ECG Compression Based Method.

We present an innovative and robust solution to both biometric and emotion identification using the electrocardiogram (ECG). The ECG represents the electrical signal that comes from the contraction of the heart muscles, indirectly representing the flow of blood inside the heart, it is known to convey a key that allows biometric identification. Moreover, due to its relationship with the nervous system, it also varies as a function of the emotional state.

Comparative analysis between biofilm formation and gene expression in Staphylococcus epidermidis isolates.

Aim: To understand the relationship between ica, aap and bhp gene expression and the implications in biofilm formation in selected clinical and commensal Staphylococcus epidermidis isolates.

Material & Methods: Isolates were analyzed regarding their biofilm-forming capacity, biochemical matrix composition, biofilm spatial organization and expression of biofilm-related genes.

Results: On polysaccharide intercellular adhesin-dependent biofilms, aap and bhp contributions for the biofilm growth were negligible, despite very high levels of expression.

Rapidly involuting congenital hemangioma.

Rapidly involuting congenital hemangioma is a rare vascular tumor that generally has a good prognosis. The authors describe a case of a newborn girl with a left cervical vascular lesion. Image exams were performed, and the lesion slowly decreased, leaving redundant skin.

A fast-growing cold skin abscess revealing disseminated Mycobacterium intracellulare infection in an HIV-infected patient.

A 66-year-old woman with HIV-1 infection recently commenced on antiretroviral therapy (CD4+ 25 cells/mm was referred to the Dermatology Clinic the following month due to a well-demarcated nodule in the extensor surface of the left arm with evident fluctuation but only slight pain on palpation, with no increase in temperature. Surgical drainage was performed with aspiration of yellowish-green exudate, with no characteristic smell. In culture of cutaneous exudate, Mycobacterium intracellulare was isolated.

Secondary Skin Plasmacytomas.

A 78-year old man was diagnosed in 2006 with IgAκ multiple myeloma (MM) (stage III-A). The patient was referred to our dermatology department in 2012 for evaluation of erythematous skin nodules on the anterior right aspect of the thorax; the skin lesions were noted during hospitalization for multiple bone fractures. He was on fourth-line chemotherapy (with vincristine/adriamycin/dexamethasone) because of constant disease progression.

An automatic classifier of emotions built from entropy of noise.

The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase.

ECG biometric identification: A compression based approach.

Using the electrocardiogram signal (ECG) to identify and/or authenticate persons are problems still lacking satisfactory solutions. Yet, ECG possesses characteristics that are unique or difficult to get from other signals used in biometrics: (1) it requires contact and liveliness for acquisition (2) it changes under stress, rendering it potentially useless if acquired under threatening. Our main objective is to present an innovative and robust solution to the above-mentioned problem.