24 documents found, page 1 of 3

Digital Alternative Communication for Individuals with Amyotrophic Lateral Scle...

Amyotrophic Lateral Sclerosis is a disease that compromises the motor system and the functional abilities of the person in an irreversible way, causing the progressive loss of the ability to communicate. Tools based on Augmentative and Alternative Communication are essential for promoting autonomy and improving communication, life quality, and survival. This Systematic Literature Review aimed to provide evidenc...

Hemostasis of the radial artery after coronary angiography

Introduction: Nowadays, a great number of interventional cardiology procedures are made via radial artery, which has increased the variability of hemostasis methods, devices, and protocols. Objective: The focus of this scoping review is to map the literature on hemostasis of the radial artery after coronary angiography. To date, no previous reviews addressing this purpose have been found. Methods: This review f...

Biomedical signals and machine learning in amyotrophic lateral sclerosis: a sys...

Introduction: The use of machine learning (ML) techniques in healthcare encompasses an emerging concept that envisages vast contributions to the tackling of rare diseases. In this scenario, amyotrophic lateral sclerosis (ALS) involves complexities that are yet not demystified. In ALS, the biomedical signals present themselves as potential biomarkers that, when used in tandem with smart algorithms, can be useful...

Automatic Electroencephalogram Artifact Removal Using Deep Convolutional Neural...

Scalp electroencephalogram (EEG) is a non-invasive measure of brain activity. It is widely used in several applications including cognitive tasks, sleep stage detection, and seizure prediction. When recorded over several hours, this signal is usually corrupted by noisy disturbances such as experimental errors, environmental interferences, and physiological artifacts. These may generate confounding factors and, ...

Data Report: "Health care of Persons Deprived of Liberty" Course From Brazil's ...

Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programme...

An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers' cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied ...

Data Report: "Health care of Persons Deprived of Liberty" Course From Brazil's ...

The Brazilian prison system has a history of shortcomings related to lack of investments and infrastructure, leading to severe consequences for the entire prison population, such as problems related to fundamental guarantees of human rights, the lack of health care, and the rise in criminality rates (1-3). With almost the third-largest prison population (4), Brazil accumulates critical issues such as overcrowdi...

Prediction of disease progression and outcomes in multiple sclerosis with machi...

Multiple Sclerosis is a chronic inflammatory disease, affecting the Central Nervous System and leading to irreversible neurological damage, such as long term functional impairment and disability. It has no cure and the symptoms vary widely, depending on the affected regions, amount of damage, and the ability to activate compensatory mechanisms, which constitutes a challenge to evaluate and predict its course. A...

Web-based Platform for Training in Biomedical Signal Processing and Classificat...

Online Experimentation, which comprises remote and virtual experimentation, has played an important role, over the years, in the development of the students learning process. One of its examples is the use of webbased resources to study physiological events in topics of biomedical engineering. This article discusses the use of a virtual experimentation environment as a training tool for studying different metho...

Lessons learned in building a middleware for smart grids

Smart grids play an important role in the modernization and optimization of the existing electrical grid, to accomplish the current European Union Energy and Climate targets. Smart grids require distributed applications to manage the grid more efficiently. The performance of the distributed applications impacts on the communications delay time and on the timely interaction with the devices located in the users’...