Paulo de Carvalho

Paulo de Carvalho
University of Coimbra | UC

About

325
Publications
41,892
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2,644
Citations
Citations since 2016
77 Research Items
1419 Citations
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2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250

Publications

Publications (325)
Chapter
The World Health Organization estimated that, in 2019, 1 billion people were aged 60 or older, being predicted to rise to 1.4 and 2.1 billions by 2030 and 2050, respectively. With aging and its related progressive accumulation of cellular and molecular damage, the organism suffers progressive physiological changes that lead to senescence, decline o...
Article
Full-text available
Ultra-short-term HRV features assess minor autonomous nervous system variations such as variations resulting from cognitive stress peaks during demanding tasks. Several studies compare ultra-short-term and short-term HRV measurements to investigate their reliability. However, existing experiments are conducted in low cognitively demanding environme...
Preprint
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Wheezes are adventitious respiratory sounds commonly present in patients with respiratory conditions. The presence of wheezes and their time location are relevant for clinical reasons, such as understanding the degree of bronchial obstruction. Conventional auscultation is usually employed to analyze wheezes, but remote monitoring has become a press...
Preprint
Wheezes are adventitious respiratory sounds commonly present in patients with respiratory conditions. The presence of wheezes and their time location are relevant for clinical reasons, such as understanding the degree of bronchial obstruction. Conventional auscultation is usually employed to analyze wheezes, but remote monitoring has become a press...
Article
Full-text available
Artificial intelligence (AI) has achieved notable performances in many fields and its research impact in healthcare has been unquestionable. Nevertheless, the deployment of such computational models in clinical practice is still limited. Some of the major issues recognized as barriers to a successful real-world machine learning applications include...
Chapter
This chapter addresses the development of innovative algorithms and models, with particular application to risk assessment, stratification, and prognosis in the context of cardiovascular diseases. The main hypothesis is that patients who have experienced similar behaviors (having the same risk factors or same characteristics) will have a similar di...
Chapter
A patient monitoring system provides real-time continuous or intermittent assessment of the patient’s physiological parameters. Monitoring systems for high-acuity settings are established within hospitals. Nowadays, effort in realizing monitoring solutions for use in low-acuity hospital settings and at home as part of personal healthcare (PHC) prod...
Chapter
This chapter gives an overview of medical imaging methods that are used for generation of pulmonary images and it assesses their suitability for implementation into wearable instruments. It focuses on the noninvasive radiation-free method of electrical impedance tomography (EIT) which exhibits a high potential for clinical use in a wearable design....
Chapter
Auscultation of respiratory sounds is a common tool used by physicians to diagnose and monitor respiratory conditions. However, some drawbacks hinder the effectiveness of conventional auscultation. Automated respiratory sound analysis could potentially overcome those limitations. Current methods are much more sophisticated than the techniques used...
Conference Paper
Full-text available
Mechanically ventilated patients typically exhibit abnormal respiratory sounds. Squawks are short inspiratory adventitious sounds that may occur in patients with pneumonia, such as COVID-19 patients. In this work we devised a method for squawk detection in mechanically ventilated patients by developing algorithms for respiratory cycle estimation, s...
Conference Paper
Patients suffering from pulmonary diseases typically exhibit pathological lung ventilation in terms of homogeneity. Electrical Impedance Tomography (EIT) is a non- invasive imaging method that allows to analyze and quantify the distribution of ventilation in the lungs. In this article, we present a new approach to promote the use of EIT data and th...
Conference Paper
One of the key challenges when developing a predictive model is the capability to describe the domain knowledge and the cause-effect relationships in a simple way. Decision rules are a useful and important methodology in this context, justifying their application in several areas, particularly in clinical practice. Several machine-learning classifi...
Preprint
Full-text available
We intend to create a new risk assessment methodology that combines the best characteristics of both risk score and machine learning models. More specifically, we aim to develop a method that, besides having a good performance, offers a personalized model and outcome for each patient, presents high interpretability, and incorporates an estimation o...
Preprint
Full-text available
Patients suffering from pulmonary diseases typically exhibit pathological lung ventilation in terms of homogeneity. Electrical Impedance Tomography (EIT) is a non-invasive imaging method that allows to analyze and quantify the distribution of ventilation in the lungs. In this article, we present a new approach to promote the use of EIT data and the...
Preprint
Full-text available
Mechanically ventilated patients typically exhibit abnormal respiratory sounds. Squawks are short inspiratory adventitious sounds that may occur in patients with pneumonia, such as COVID-19 patients. In this work we devised a method for squawk detection in mechanically ventilated patients by developing algorithms for respiratory cycle estimation, s...
Conference Paper
Full-text available
Patients with respiratory conditions typically exhibit adventitious respiratory sounds, such as wheezes. Wheeze events have variable duration. In this work we studied the influence of event duration on wheeze classification, namely how the creation of the non-wheeze class affected the classifiers' performance. First, we evaluated several classifier...
Article
Introduction The risk prediction of the occurrence of a clinical event is often based on conventional statistical procedures, through the implementation of risk score models. Recently, approaches based on more complex machine learning (ML) methods have been developed. Despite the latter usually have a better performance, they obtain little approval...
Article
Full-text available
Electrocardiogram (ECG) recordings, lasting hours before epileptic seizures, have been studied in the search for evidence of the existence of a preictal interval that follows a normal ECG trace and precedes the seizure’s clinical manifestation. The preictal interval has not yet been clinically parametrized. Furthermore, the duration of this interva...
Chapter
This work deals with similarity measuring and indexing in biosignal time series. In particular, it focuses in an approach proposed by the authors in previous works, which consists in a transformed-based method, performed by means of a set of Haar wavelet basis functions that is reduced to an optimal subset through the Karhunen Loève transform (WKLT...
Chapter
The current health care paradigm clearly identifies prevention as a key element to an efficient disease management. In the context of cardiovascular disease, risk assessment models may be a valuable element in the support to clinical decision, contributing to that preventive care. Moreover, interpretability as well as personalization of risk assess...
Chapter
The possibility of using simple and effective models to estimate the patient’s length of stay in intensive care units is decisive to support the clinical professional decisions. These models can help professionals in the stratification process and, particularly, in the identification of the necessary intervention plan to improve the patient’s healt...
Article
Full-text available
(1) Background: Patients with respiratory conditions typically exhibit adventitious respiratory sounds (ARS), such as wheezes and crackles. ARS events have variable duration. In this work we studied the influence of event duration on automatic ARS classification, namely, how the creation of the Other class (negative class) affected the classifiers’...
Article
Full-text available
Lung sounds acquired by stethoscopes are extensively used in diagnosing and differentiating respiratory diseases. Although an extensive know-how has been built to interpret these sounds and identify diseases associated with certain patterns, its effective use is limited to individual experience of practitioners. This user-dependency manifests itsel...
Chapter
The use of accelerometer (ACC) sensors above the carotid artery provides an interesting approach to pulse detection during Cardiopulmonary Resuscitation (CPR) efforts. In order to study the basic feasibility of these ACC sensors in a resuscitation scenario, a protocol was designed with the aim of simulating characteristics present in a real-life sc...
Conference Paper
Epileptic seizures are by default associated with the occurrence of EEG changes as a consequence of alterations in brain activity seconds to hours before the seizure onset. Additionally, the influence of the autonomic nervous system may also be reflected in the electrocardiogram (ECG) trace. In both biosignals (EEG and ECG), differences have been r...
Conference Paper
Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions.In this paper we introduce a methodology with the goal of fin...
Conference Paper
This paper provides a study using Electroencephalography (EEG) to investigate the brain activity during code comprehension tasks. Three different code complexity levels according to five complexity metrics were considered. The use of EEG for this purpose is relevant, since the existing studies were mostly focused on neuroimaging techniques. Using L...
Article
Full-text available
Imagery of facial expressions in Autism Spectrum Disorder (ASD) is likely impaired but has been very difficult to capture at a neurophysiological level. We developed an approach that allowed to directly link observation of emotional expressions and imagery in ASD, and to derive biomarkers that are able to classify abnormal imagery in ASD. To provid...
Conference Paper
Full-text available
Detection of abnormal cardiac events during clinical examination is a matter of chances, as such events may not happen at that precise moment. We therefore propose the implementation and evaluation of a mobile based system that allows a real-time detection of cardiovascular problems related to heart-rate variability. Our approach is to integrate an...
Conference Paper
In the last decades numerous researches have revealed a strong link between emotions and several physiological responses. However, the automatic recognition of emotions still remains a challenge. In this work we describe a novel approach to estimate valence, arousal and dominance values from various biological parameters (derived from electrodermal...
Conference Paper
Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions. In this paper we introduce a methodology with the goal of fi...
Conference Paper
Full-text available
Stress and emotions can cause several physiological and behavioral changes, some of which may also have a severe impact on the cardiovascular function. For this reason, an accurate assessment of stress level and emotion kind and strength should be considered important to reduce the associated car-diovascular risks. However, the use of biological pa...
Conference Paper
The effectiveness of predictive models in supporting the Clinical Decision is closely related with their clinical interpretability, i.e.the model should provide clear information on how to reach a specific classification/decision. In fact, the development of interpretable and accurate predictive models assumes a key importance as these tools can be...
Conference Paper
P300-based Brain Computer Interfaces (BCI) are one of the most used types of BCIs in the literature that make use of the electroencephalogram (EEG) signal to convey commands to the computer. The efficiency of such systems depends drastically on the ability of correctly identifying the P300 wave in the EEG signal. Due to high inter-subject and inter...
Conference Paper
The development of a reliable and robust algorithm for prediction of syncope events is still a major challenge, especially when it is based on the analysis of the photoplethysmogram (PPG) alone. Several algorithms have been proposed in the literature based on the joint analysis of the electrocardiogram, the blood pressure and also the PPG [1]. Howe...
Conference Paper
The clinical assessment of a specific patient’s condition can be a very difficult process as multiple variables/risk factors may be involved. Thus, clinical guidelines frequently recommend the use of models that were developed with the objective of aiding the clinical decision. However, these models still present some significant flaws that must be...
Article
Full-text available
Analysis and interpretation of heart sounds (HSs) can be seriously hindered by noise contamination when signals are acquired in noncontrolled environments. Signal processing methodologies are then required in order to robustly analyse HSs collected in different recording settings. Some works already address this problem using complex calculus that...
Chapter
Full-text available
The goal of LiNK is to discover and define research tracks in the area of intelligent processing to support cardiovascular disease management in Per-sonalized Healthcare (PHC). The strategy was based on a twofold approach. First, using a status assessment of the current research on PHC and an international research forum. From this roadmap, specifi...
Book
This volume presents the proceedings of the 3rd ICBHI which took place in Thessaloniki on 18-21 November, 2017.The area of biomedical and health informatics is exploding at all scales. The developments in the areas of medical devices, eHealth and personalized health as enabling factors for the evolution of precision medicine are quickly developing...
Article
Cardiovascular diseases are the leading cause of death worldwide. The development of models to support clinical decision is of great importance in the management of these diseases. This work aims to improve the performance exhibited by risk assessment scores that are applied in the clinical practice. This methodology has three main phases: (i) repr...
Conference Paper
Full-text available
We present a new method for the discrimination of explosive cough events, which is based on a combination of spectral content descriptors and pitch-related features. After the removal of near-silent segments, a vector of event boundaries is obtained and a proposed set of 9 features is extracted for each event. Two data sets, recorded using electron...
Conference Paper
The relationship between EEG and fMRI data is poorly covered in the literature. Extensive work has been conducted in resting-state and epileptic activity, highlighting a negative correlation between the alpha power band of the EEG and the BOLD activity in the default-mode-network. The identification of an appropriate task-specific relationship betw...
Conference Paper
Full-text available
The analysis of the respiratory sounds is a valuable diagnostic tool for the detection and the follow-up of respiratory diseases such as Chronic Obstructive Pulmonary Disease (COPD). Adventitious sounds, such as wheezes, stridors, squawks and crackles, refer to additional respiratory sounds superimposed on breath sounds and are highly correlated to...
Conference Paper
Full-text available
The automatic detection of adventitious sounds, such as wheezes and crackles, is a valuable non-invasive tool to detect and follow-up respiratory diseases such as chronic obstructive pulmonary disease. Crackles are short explosive sounds that seem to result from an abrupt opening or closing of the airways. Several methods have been proposed for aut...
Conference Paper
Development of personalized cardiovascular management systems involves automatic identification of the current data as normal or pathological; considering cardiac data as time-series, the illness identification may be performed by seeking similarity between the current patient's time-series data and a reference signal and then proceeding to illness...
Chapter
Full-text available
Blood pressure monitoring is essential in hospital and home monitoring scenarios, with applications requiring on-line beat-to-beat blood pressure estimation, such as tele-monitoring of neurally mediated syncope. This chapter presents a comprehensive review of investigated approaches and reported performance, using different noninvasive correlates o...
Conference Paper
The evaluation of a patient’s condition is a challenging task that physicians have to deal with in their daily clinical practice, as there are some specific conditions where the diagnosis is not straightforward. Therefore, clinical guidelines frequently recommend the use of models that were developed with the objective of aiding the clinical decisi...
Conference Paper
Full-text available
Lung sound signal processing has proven to be a great improvement to the traditional acoustic interpretation of lung sounds. However, that analysis can be seriously hindered by the presence of different types of noise originated in the acquisition environment or caused by physiological processes. Consequently, the diagnostic accuracy of pulmonary d...
Conference Paper
Heart rate variability (HRV) represents one of the most promising markers of the autonomic nervous system (ANS) regulation. However, it requires the acquisition of the ECG signal in order to reliably detect the RR intervals, which is not always easily and comfortably available in personal health applications. Additionally, due to progress in single...
Conference Paper
Full-text available
The global inhomogeneity (GI) index is a electrical impedance tomography (EIT) parameter that quantifies the tidal volume distribution within the lung. In this work the global inhomogeneity index was computed for twenty subjects in order to evaluate his potential use in the detection and follow up of chronic obstructive pulmonary disease (COPD) pat...
Conference Paper
Full-text available