V.H.C. Albuquerque

University of Porto | UP · Faculty of Engineering

X-ray images are commonly used in medicine because they are inexpensive and non-invasive, but they often have noise issues caused by equipment or environmental factors. While there are many traditional image processing algorithms for enhancing X-ray images described in literature, there is a lack of machine learning-based methods due to the challen...

Large-scale wireless sensor networks (WSNs) play a critical role in monitoring dangerous scenarios and responding to medical emergencies. However, the inherent instability and error-prone nature of wireless links present significant challenges, necessitating efficient data collection and reliable transmission services. This paper addresses the limi...

Electrocardiogram(ECG) monitoring is a critical and intricate task in cardiac healthcare. While large models supported by the remote cloud servers with abundant computational resources offers a feasible solution for this task, which still face challenges related to processing costs, privacy risks, and response time. Efforts have been made to integr...

In today’s advanced applications, such as memory interfaces, feature-based detection, and sensory games, human-computer interaction (HCI) plays a pivotal role. A medical decision support system (MDSS) emerges from the integration of a data system with resources for medical decision-making. Within MDSS, human-computer interaction and perceptual medi...

In the contemporary digital era, individuals face an overwhelming challenge of searching for personalized content from a seemingly infinite pool of available options such as books, videos, articles, and movies. Simultaneously, digital content providers strive to attract and retain as many users on their platforms as possible for extended periods. T...

The aim of our study is to evaluate the quality of water using machine learning methods. Potability is a subjective word that quantifies water quality. In this research, a variety of metrics were used to measure general potability of the water. The prescribed elements are applied like variable matrix to denote water quality. The article used three...

The type of cancer which is most commonly found throughout the world is skin cancer. Before the cancer gets too serious, a premature detection of skin cancer is crucial for improving the patient’s health and reducing the rate of fatality (Mishra et al. in Rice yield estimation using deep learning [1]). In the research that we have conducted, we pro...

The field of drug discovery has experienced a remarkable transformation with the advent of artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI and ML models are becoming more complex, there is a growing need for transparency and interpretability of the models. Explainable Artificial Intelligence (XAI) is a nove...

Emotion is a complex physiological and psychological activity, accompanied by subjective physiological sensations and objective physiological changes. The body sensation map describes the changes in body sensation associated with emotion in a topographic manner, but it relies on subjective evaluations from participants. Physiological signals are a...

When it comes to vehicle surveillance, the Smart Parking System is considered indispensable, and it is now making its mark in the parking management sector. The errors caused by manual entry of vehicle registration information are absolutely eliminated. The process is made absolutely smooth and safe by the Smart Parking System. This not only stores...

The rapid development of the Internet of Things (IoT) widely supports the smart healthcare system. IoT-based smart health has significant importance for the diagnosis of cardiovascular disease in clinical practice. Combined with advanced artificial intelligence techniques, IoT-based smart health provides valuable and accurate diagnosis information...

The main objective of this study is to propose a cyber-physical system (CPS) based person re-identification framework for smart surveillance. The Internet of Things (IoT) based interconnected vision sensors in smart cities are considered essential elements of a CPS, and contribute significantly to urban security. However, the re-identification of t...

Cardiovascular diseases have emerged as a serious threat to global human health. Cardiac Rehabilitation (CR) is increasingly known as a crucial component in the continuum of care for patients with cardiovascular. Heart Rate Variability Biofeedback (HRVB) facilitates the modulation of the patient's Autonomic Nervous System (ANS) non-invasively by en...

Motion multiple object tracker model is the objective of the object detection and automated monitoring of the scene for suspicious activity incidents on an ongoing basis. An algorithm tracks the motion of an object in order to predict or anticipate where it will be in relation to its trajectory. The identification method of moving objects using dig...

Computer vision technology for detecting objects in a complex environment often includes other key technologies, including pattern recognition, artificial intelligence, and digital image processing. It has been shown that Fast Convolutional Neural Networks (CNNs) with You Only Look Once (YOLO) is optimal for differentiating similar objects, constan...

One of the most widespread illnesses worldwide among women is breast cancer. A quick, proper diagnosis is essential in rehabilitation and recovery. However, because of different difficulties in mammography detection, it is not an easy process. Techniques of applied machine learning can produce early detection tools, significantly improving survival...

Pain assessment is essential for pain diagnosis and treatment. Automating the assessment process from pain behaviors could be an alternative to self-report; however, inter-subject and time-dynamic differences in pain behaviors hinder pain recognition as generic patterns. To address this problem, we proposed a neural network method integrating pain...

The main challenge faced by video-based real-world anomaly detection systems is the accurate learning of unusual events that are irregular, complicated, diverse, and heterogeneous in nature. Several techniques utilizing deep learning have been created to detect anomalies, yet their effectiveness on real-world data is often limited due to the insuff...

An accurate inquiry may aid timely infection diagnosis, patients’ communal security, and community amenities in today’s world, where data is quickly developing in fields such as bioscience and health protection. In the field of medicine, prediction is an important but sometimes overlooked component. In this paper, the authors construct deep learnin...

With the development of brain-computer interfaces (BCI) technologies, EEG-based BCI applications have been deployed for medical purposes. Motor imagery (MI), applied to promote neural rehabilitation for stroke patients, is among the most common BCI paradigms that. The Electroencephalogram (EEG) signals, encompassing an extensive range of channels,...

Even with over 80% of the population being vaccinated against COVID-19, the disease continues to claim victims. Therefore, it is crucial to have a secure Computer-Aided Diagnostic system that can assist in identifying COVID-19 and determining the necessary level of care. This is especially important in the Intensive Care Unit to monitor disease pro...

Retraction: [Gaurav Dhiman, Marcello Carvalho dos Reis, Paulo C. S. Barbosa, Victor Hugo C. de Albuquerque, Sandeep Kautish, Blockchain‐based covert software information transmission for bitcoin, IET Software 2023 (https://doi.org/10.1049/sfw2.12120)]. The above article from IET Software, published online on 8 February 2023 in Wiley Online Library...

Retraction: [Vimal Shanmuganathan, Victor Hugo C. de Albuquerque, Paulo C. S. Barbosa, Marcello Carvalho dos Reis, Gaurav Dhiman, Mohd Asif Shah, Software based sentiment analysis of clinical data for healthcare sector, IET Software 2023 (https://doi.org/10.1049/sfw2.12115)]. The above article from IET Software, published online on 7 February 2023...

Ankle injuries caused by the Anterior Talofibular Ligament (ATFL) are the most common type of injury. Thus, finding new ways to analyze these injuries through novel technologies is critical for assisting medical diagnosis and, as a result, reducing the subjectivity of this process. As a result, the purpose of this study is to compare the ability of...

Forest fires can have severe impacts on both the environment and human communities. They can cause soil erosion, loss of habitat and biodiversity, as well as the release of carbon dioxide and other pollutants into the atmosphere. In addition, they can cause damage to properties, displacement of residents, and put firefighters and other responders a...

Measurement uncertainty is one of the widespread concepts applied in scientific works, particularly to estimate the accuracy of measurement results and to evaluate the conformity of products and processes. In this work, we propose a methodology to analyze the performance of measurement systems existing in the design phases, based on a probabilistic...

The sixth‐generation (6G) networks offer effective results over the earlier generations for satisfying the needs of emergent services as well as applications like multi‐gigabit transmission rate, high reliability, delay, and ubiquitous connections for Internet of Everything (IoE). But due to the shortage of spectrum resource, effectively managing t...

Implementing internet of things technologies in health monitoring systems attracts a lot of attention. Running the model at edge can continuously and in real-time monitor the user’s physiological information, which can be adopted in universal medical care. However, this task is challenging and rarely discussed due to its limited computational capac...

Recently, sixth generation (6G) wireless communication networks are predictable in delivering global coverage, improved efficiency, effective intelligence, privacy, and so on. The advances of artificial intelligence (AI), particularly deep learning (DL) models, can be employed to effectually realize and optimize the 6G network applications. In dail...

In this article, strategies to control knee flexion and hip flexion are presented based on the excitation of the muscles responsible for such movements, in view of the widespread use of functional electrical stimulation (FES) for treatment of neurological diseases, accidents, among others. Currently, the application of the stimulus does not guarant...

This work presents the design of RST controllers for elbow flexion and extension movements through simulation. Mathematical models for the movements were identified and the RST parameters of two controllers were obtained. The operation of the controllers was evaluated operating individually and, later, in parallel. At the end, new studies are propo...

Mobile Ad‐hoc Network (MANET) is an ad hoc Wireless subset with a unique dynamic geometry of the system and movable nodes. The MANETs are auto‐organized networks that permit mobility without infrastructure. Specific protocols for MANET routing are provided with these attributes. The benefits such as infinite stability and the essential organization...

The Internet of Vehicles (IoV) is undoubtedly at the core of the future of intelligent transportation. It will prevail over the road ecosystem, and it will have a huge impact on our lives throughout the provision of seamless connectivity among diverse transportation means. For the network to operate efficiently, the data needs to be quickly spread...

Image-guided intervention is a medical procedure that leverages computerized systems to deliver virtual image overlays to help physicians in visualization and targeting the surgical site in an accurate manner. Computer Aided Diagnosis (CAD) models that use Deep Learning (DL) techniques are useful in achieving accurate skin cancer classification. In...

With the privacy protection increasingly being concerned, Data centralization often heavily causes a big risk of privacy protection, gradually, there is a prevailing trend to enhance the security performance by means of data decentralization, above all, for health care internet of things(IoT) data.Meanwhile, Federated learning has obvious privacy a...

Coronavirus disease (COVID-19) has created an unprecedented devastation and the loss of millions of lives globally. Contagious nature and fatalities invariably pose challenges to physicians and healthcare support systems. Clinical diagnostic evaluation using reverse transcription-polymerase chain reaction and other approaches are currently in use....

Prostheses play an important role in the rehabilitation of people who have suffered some type of amputation. However, due to its high‐cost and high complexity in performing movements of everyday tasks, users of these prostheses may encounter many difficulties. Therefore, this work proposes the development of a future artificial intelligence technol...

This work presents a high-performance approach for 3D lung segmentation tasks in computer tomography images using a new intelligent machine learning algorithm called Floor of Log(FoL). The Support Vector Machine was used to learn the better parameter of the FoL algorithm using the parenchyma and its border as labels. Sensitivity, Matthews Correlati...

Currently, many simulator systems for medical procedures are under development. These systems can provide new solutions for training, planning, and testing medical practices, improve performance, and optimize the time of the exams. Some premises must be followed and applied to the model under development, such as usability, control, graphics realis...

Deep Learning models’ performance strongly correlate with availability of annotated data; however, massive data labelling is laborious, expensive, and error-prone when performed by human experts. Active Learning (AL) effectively handles this challenge by selecting the uncertain samples from unlabeled data collection, but the existing AL approaches...

Anatomical structures manifested in ultrasound (US) images are crucial in efficient disease diagnosis. This modality has been used to analyze different tissue properties, such as blood flow, in-depth tissue motion, and elasticity. Analysis of these US images is posing a critical challenge, as these images are corrupted with noise primarily induced...

Atrial fibrillation (AF) is a serious medical condition of the heart potentially leading to stroke, which can be diagnosed by analyzing electrocardiograms (ECG). Technologies of Artificial Intelligence of Things (AIoT) enable smart abnormality detection by analyzing streaming healthcare data from the sensor end of users. Analyzing streaming data in...

The COVID-19 pandemic continues to wreak havoc on the world’s population’s health and well-being. Successful screening of infected patients is a critical step in the fight against it, with radiology examination using chest radiography being one of the most important screening methods. For the definitive diagnosis of COVID-19 disease, reverse-transc...

In the past decades, fuzzy logic has played an essential role in many research areas. Alongside, graph-based pattern recognition has shown to be of great importance due to its flexibility in partitioning the feature space using the background from graph theory. Some years ago, a new framework for both supervised, semi-supervised, and unsupervised l...

Advancements in smart vehicle design have enabled the creation of Internet of Vehicle (IoV) technologies that can utilize the information provided by various sensors and wireless communication to perform complex functionality. Many of these functionalities rely on high computational power and low latency. Mobile Edge Computing (MEC) technologies ha...

The use of computational techniques in the processing of histopathological images allows the study of the structural organization of tissues and their changes through diseases. This study aims to develop a tool for classifying histopathological images from breast lesions in the benign and malignant classes through magnification scales by an innovat...

Processing signals on edge nodes has become a popular trend, which requires data to be stored in terminals and processed, so it has the advantages of low latency, low power consumption and privacy protection. However, due to the limited resources of embedded devices, few studies have made relevant attempts. Our task was to implement a task for atri...

Processing signals on edge nodes has become a popular trend, which requires data to be stored in terminals and processed, so it has the advantages of low latency, low power consumption and privacy protection. However, due to the limited resources of embedded devices, few studies have made relevant attempts. Our task was to implement a task for atri...

Twitter is currently one of the most popular microblogging platforms allowing people to post short messages, news, thoughts, and so on. The Twitter user community is growing very fast. It has an average of 328 million active accounts today, making it one of the most common media for getting information during any influential or important event. Bec...

Computer vision has always been a hot field of research by contemporary scholars due to its wide range of applications. As an important branch of this field, visual monitoring technology has shown superior vitality in the actual monitoring environment of the Internet of Things (IoT). However, when the monitoring environment is complex, once the tar...

Video summarization (VS) suppresses high-dimensional (HD) video data by only extracting only the important information. However, prior research has not focused on the need for surveillance VS, that is used for many applications to assist video surveillance experts, including video retrieval and data storage. In addition, mainstream techniques commo...

With the continuous advancement of smart devices and their demand for data, the complex computation that was previously exclusive to the cloud server is now moving towards the edge of the network. For numerous reasons (e.g., applications demanding low latencies and data privacy), data-based computation has been brought closer to the originating sou...

The detection of intrusions in IoT networks is essen- tial to maintain the availability and integrity of data transmitted and generated by devices connected to these networks. This is primarily when the data originates from critical activities, such as activities in the military, financial, industrial, and health sectors. Machine learning technique...

Cardiovascular disease has become a significant cause of modern people's health problems. The mobile electrocardiogram can be a non-intrusive and convenient tool to provide an auxiliary diagnosis of cardiovascular diseases for the virtual heath community. In this paper, a new diagnostic framework for mobile electrocardiogram signal is proposed with...

According to the World Health Organization (WHO), about 85 percent of the world’s population suffers from back pain, the main cause being poor posture. Persistent lower back pain is found to be persistent in both the populations. The proposed solution is composed of flexible sensors that capture all the moves made by the spine, being able to identi...

Artificial intelligence (AI) algorithms are experiencing growing research interest due to their ability to improve decision making capabilities for promising applications in different economic sectors. The growing shift toward the Internet of Everything environments brought by devices embedded with sensors that can share information brings immense...