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Publicações

Publicações por Joana Isabel Paiva

2016

Changes in ST, QT and RR ECG intervals during acute stress in firefighters: A pilot study

Autores
Paiva, JS; Rodrigues, S; Cunha, JPS;

Publicação
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Abstract
Firefighting is a stressful occupation. The monitoring of psychophysiological measures in those professionals can be a way to prevent and early detect cardiac diseases and other stress-related problems. The current study aimed to assess morphological changes in the ECG signal induced by acute stress. A laboratory protocol was conducted among 6 firefighters, including a laboratory stress-inducer task - the Trier Social Stress Task (TSST) - and a 2-choice reaction time task (CRTT) that was performed before (CRTT1) and after (CRTT2) the stress condition. ECG signals were continuously acquired using the VitalJacket®, a wearable t-shirt that acts as a medical certified ECG monitor. Results showed that ECG morphological features such as QT and ST intervals are able to differentiate stressful from non stressful events in first responders. Group mean Visual Analogue Scale (VAS) for stress assessment significantly increased after the stress task (TSST), relatively to the end of CRTT2 (after TSST: 4.67±1.63; after CRTT2: 3.17±0.75), a change that was accompanied by a significant increase in group mean QT and ST segments corrected for heart rate during TSST. These encouraging results will be followed by larger studies in order to explore those measures and its physiological impact under realistic environments in a higher scalability. © 2016 IEEE.

2017

Beat-ID: Towards a computationally low-cost single heartbeat biometric identity check system based on electrocardiogram wave morphology

Autores
Paiva, JS; Dias, D; Cunha, JPS;

Publicação
PLOS ONE

Abstract
In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710 +/- 1.900% and 3.440 +/- 1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of concept implementation is presented as an annex to this paper.

2017

Computational modeling of red blood cells trapping using Optical Fiber Tweezers

Autores
Paiva, JS; Ribeiro, RSR; Jorge, PAS; Rosa, CC; Cunha, JPS;

Publicação
ENBENG 2017 - 5th Portuguese Meeting on Bioengineering, Proceedings

Abstract
Optical Tweezers (OT) are able to trap/manipulate dielectric particles with few microns in a contactless manner due to forces exerted on them by a strongly focused optical beam. OT are being applied in Biology/Medicine, especially Optical Fiber Tweezers (OFT), for being simpler and more flexible than the conventional setups. Despite of the trapping phenomena of symmetrical particles by OFTs being already modeled, effects regarding complex bodies remain poorly understood. Here we provide a 2D characterization of the trapping forces exerted by a laser OFT on a geometric form of a Red Blood Cell (RBC), occupying different positions in a grid, using the method proposed by Barnett&Loudon. Comparisons were made between the forces exerted on a RBC having the mean normal size; a RBC with 80% of the normal size and an 1.5µm circular particle, due to the size and shape variability of biological-derived structures. The influence of RBCs inclination angles regarding its major axis on trapping performance was also evaluated for angles of p/4 and p/2. Simulation results showed that trapping phenomena are possible for all the conditions evaluated, as well as calculated trapping forces range was according with the literature (pN). We observed that, despite of modeled particles having the same optical characteristics, features such as particle geometry, size, position and inclination degree influence trapping. Trapping forces magnitude was higher for RBC relatively to the circular symmetrical particle; for large RBCs than RBCs with smaller dimensions; and for inclined RBCs than erythrocytes horizontally aligned. Those results reinforce the importance of modeling optical experiments to determine relevant parameters which affect trapping performance. © 2017 IEEE.

2017

2D computational modeling of optical trapping effects on malaria-infected red blood cells

Autores
Paiva, JS; Ribeiro, RSR; Jorge, PAS; Rosa, CC; Guerreiro, A; Cunha, JPS;

Publicação
Optics InfoBase Conference Papers

Abstract
A computational method for optical fiber trapping of healthy and Malariainfected blood cells characterization is proposed. A trapping force relation with the infection stage was found, which could trigger the development of a diagnostic sensor. © OSA 2017.

2016

Effects of perceived stress and fatigue in Firefighters cognitive performance: a pilot study

Autores
Rodrigues, S; Paiva, J; Pimentel, G; Silva Cunha, JPS;

Publicação
SHO2016: INTERNATIONAL SYMPOSIUM ON OCCUPATIONAL SAFETY AND HYGIENE

Abstract
Firefighting is a hazardous occupation. Firefighters are commonly subjected to high levels of stress and fatigue that could interfere with their ability to take decisions under pressure. Based on this assumption, a laboratory protocol was conducted among 10 Portuguese firefighters in order to address their stress and mental fatigue levels and its impact on cognitive performance. A 2-Choice Reaction Time Task was used to measure cognitive performance (before and after a stress condition) and a psychosocial stress paradigm was used to assess stress. Visual Analogue Scales were also used to measure perceived stress and mental fatigue. Results suggested that firefighters felt more fatigued at the end of the protocol, however their performance only decreased in the first reaction time task. Furthermore, findings suggested that stress improved firefighters reaction times, however when stress levels increased, performance decreased. This suggests the need to better understand firefighters optimal stress levels and fatigue, in order to promote their health and work safety, by improving their performance under demanding situations.

2018

Optical Fiber Tips for Biological Applications: from Light Confinement, Biosensing to Bioparticles Manipulation

Autores
Paiva, JS; Jorge, PAS; Rosa, CC; Cunha, JPS;

Publicação
Biochimica et Biophysica Acta (BBA) - General Subjects

Abstract

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