Publications
Publications by categories in reversed chronological order. generated by jekyll-scholar.
2021
- MDPIe-CoVig: A Novel mHealth System for Remote Monitoring of Symptoms in COVID-19Raposo, Afonso, Marques, Luis, Correia, Rafael, Melo, Francisco, Valente, João, Pereira, Telmo, Rosário, Luis Brás, Froes, Filipe, Sanches, João, and Silva, Hugo Plácido daSensors 2021
In 2019, a new virus, SARS-CoV-2, responsible for the COVID-19 disease, was discovered. Asymptomatic and mildly symptomatic patients were forced to quarantine and closely monitor their symptoms and vital signs, most of the time at home. This paper describes e-CoVig, a novel mHealth application, developed as an alternative to the current monitoring paradigm, where the patients are followed up by direct phone contact. The e-CoVig provides a set of functionalities for remote reporting of symptoms, vital signs, and other clinical information to the health services taking care of these patients. The application is designed to register and transmit the heart rate, blood oxygen saturation (SpO2), body temperature, respiration, and cough. The system features a mobile application, a web/cloud platform, and a low-cost specific device to acquire the temperature and SpO2. The architecture of the system is flexible and can be configured for different operation conditions. Current commercial devices, such as oximeters and thermometers, can also be used and read using the optical character recognition (OCR) functionality of the system. The data acquired at the mobile application are sent automatically to the web/cloud application and made available in real-time to the medical staff, enabling the follow-up of several users simultaneously without the need for time consuming phone call interactions. The system was already tested for its feasibility and a preliminary deployment was performed on a nursing home showing promising results.
@Article{s21103397, author = {Afonso Raposo and Luís Marques and Rafael Correia and Francisco Melo and João Valente and Telmo Pereira and Luis Brás Rosário and Filipe Froes and João Sanches and Hugo Plácido da Silva}, title = {{e-CoVig: A Novel mHealth System for Remote Monitoring of Symptoms in COVID-19}}, journal = {Sensors}, volume = {21}, year = {2021}, number = {10}, article-number = {3397}, url = {https://www.mdpi.com/1424-8220/21/10/3397}, issn = {1424-8220}, abstract = {{In 2019, a new virus, SARS-CoV-2, responsible for the COVID-19 disease, was discovered. Asymptomatic and mildly symptomatic patients were forced to quarantine and closely monitor their symptoms and vital signs, most of the time at home. This paper describes e-CoVig, a novel mHealth application, developed as an alternative to the current monitoring paradigm, where the patients are followed up by direct phone contact. The e-CoVig provides a set of functionalities for remote reporting of symptoms, vital signs, and other clinical information to the health services taking care of these patients. The application is designed to register and transmit the heart rate, blood oxygen saturation (SpO2), body temperature, respiration, and cough. The system features a mobile application, a web/cloud platform, and a low-cost specific device to acquire the temperature and SpO2. The architecture of the system is flexible and can be configured for different operation conditions. Current commercial devices, such as oximeters and thermometers, can also be used and read using the optical character recognition (OCR) functionality of the system. The data acquired at the mobile application are sent automatically to the web/cloud application and made available in real-time to the medical staff, enabling the follow-up of several users simultaneously without the need for time consuming phone call interactions. The system was already tested for its feasibility and a preliminary deployment was performed on a nursing home showing promising results.}}, doi = {10.3390/s21103397} } - EMBCCamera-based Photoplethysmography (cbPPG) using smartphone rear and frontal cameras: an experimental studyRaposo, Afonso, Silva, Hugo Plácido, and Sanches, João2021
Non-expensive methods for measuring heart rate and oxygen saturation are of great importance in the scope of the COVID-19 outbreak to follow up on the symptoms and help to control the disease. Smartphones are widely available and their cameras can be used to acquire relevant physiological data, such as Photoplethysmography (PPG) signals. Covering a light source and the camera sensor with a finger, it is possible to acquire the camera-based photoplethysmography (cbPPG) signal. Two methods were analyzed in this work, namely using the rear smartphone camera and the flash LED, and using the front camera and device display as a light source. The latter presents more advantages overall - in particular, greater control over the emitted light and finger detection - and better results were found when compared to a reference device. Clinical relevance — This technology allows the pervasive monitoring of the PPG signal using a standard smartphone, providing a tool to evaluate the subject’s heart rate and its variability, respiration, blood oxygenation, etc.
@conference{2021_embc_raposo, abbr = {EMBC}, author = {Afonso Raposo and Hugo Plácido da Silva and João Sanches}, title = {Camera-based Photoplethysmography (cbPPG) using smartphone rear and frontal cameras: an experimental study}, booktitle = {43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)}, year = {2021}, month = {11}, organization = {EMBC}, address = {Virtual conference}, pages = {7091-7094}, abstract = {{Non-expensive methods for measuring heart rate and oxygen saturation are of great importance in the scope of the COVID-19 outbreak to follow up on the symptoms and help to control the disease. Smartphones are widely available and their cameras can be used to acquire relevant physiological data, such as Photoplethysmography (PPG) signals. Covering a light source and the camera sensor with a finger, it is possible to acquire the camera-based photoplethysmography (cbPPG) signal. Two methods were analyzed in this work, namely using the rear smartphone camera and the flash LED, and using the front camera and device display as a light source. The latter presents more advantages overall - in particular, greater control over the emitted light and finger detection - and better results were found when compared to a reference device. Clinical relevance — This technology allows the pervasive monitoring of the PPG signal using a standard smartphone, providing a tool to evaluate the subject’s heart rate and its variability, respiration, blood oxygenation, etc.}} } - RECPADLow-Cost Pulse Oximetry and Infra-Red Temperature Device for COVID-19 PatientsRaposo, Afonso, Melo, Francisco, Sanches, João, and Silva, Hugo Plácido2021
With the beginning of the COVID-19 pandemic in early 2020, there was a pressing need for simple yet effective remote monitoring solutions. In this paper, we describe a low-cost device developed for monitoring COVID-19 patients. The device uses an ESP32 module and integrates two distinct off-the-shelf biomedical sensors: a pulse oximeter by MAXIM, and an infra-red (IR) thermometer by MELEXIS. The device communicates with a smartphone via Bluetooth which then sends the acquired data to a cloud-based platform. An initial evaluation was performed at Coimbra’s Polytechnic Institute, and covered reproducibility and agreement with standard clinical devices, revealing a strong correlation for the pulse oximeter and a necessity for further testing the IR thermometer.
@conference{2021_recpad_raposo_ecovig, abbr = {RECPAD}, author = {Afonso Raposo and Francisco Melo and João Sanches and Hugo Plácido da Silva}, title = {Low-Cost Pulse Oximetry and Infra-Red Temperature Device for COVID-19 Patients}, booktitle = {27th Portuguese Conference on Pattern Recognition}, year = {2021}, month = {11}, organization = {RECPAD}, address = {Évora, Portugal}, pages = {81-82}, abstract = {{With the beginning of the COVID-19 pandemic in early 2020, there was a pressing need for simple yet effective remote monitoring solutions. In this paper, we describe a low-cost device developed for monitoring COVID-19 patients. The device uses an ESP32 module and integrates two distinct off-the-shelf biomedical sensors: a pulse oximeter by MAXIM, and an infra-red (IR) thermometer by MELEXIS. The device communicates with a smartphone via Bluetooth which then sends the acquired data to a cloud-based platform. An initial evaluation was performed at Coimbra’s Polytechnic Institute, and covered reproducibility and agreement with standard clinical devices, revealing a strong correlation for the pulse oximeter and a necessity for further testing the IR thermometer.}} } - RECPADUltrasound denoising using the pix2pix GANRaposo, Afonso, Azeitona, António, Afonso, Manya, and Sanches, João2021
The use of ultrasound (US) as an imaging technique is essential for the diagnosis of atherosclerotic cardiovascular disease (ASCVD), which depends on US images of the carotid artery. However, US images are plagued by a specific type of noise called Speckle noise, which lowers image quality dramatically. As an attempt to improve US image quality, the use of a generative adversarial network (GAN) is explored. The GAN chosen for this is the pix2pix model and the dataset used for training is composed of images containing simple geometric shapes of various scales and their equivalent corrupted with Speckle noise following the Log-Compression model. The results of this GAN are displayed and a noticeable improvement can be verified in the image quality.
@conference{2021_recpad_raposo_pix2pix, abbr = {RECPAD}, author = {Afonso Raposo and António Azeitona and Manya Afonso and João Sanches}, title = {Ultrasound denoising using the pix2pix GAN}, booktitle = {27th Portuguese Conference on Pattern Recognition}, year = {2021}, month = {11}, organization = {RECPAD}, address = {Évora, Portugal}, pages = {91-92}, abstract = {{The use of ultrasound (US) as an imaging technique is essential for the diagnosis of atherosclerotic cardiovascular disease (ASCVD), which depends on US images of the carotid artery. However, US images are plagued by a specific type of noise called Speckle noise, which lowers image quality dramatically. As an attempt to improve US image quality, the use of a generative adversarial network (GAN) is explored. The GAN chosen for this is the pix2pix model and the dataset used for training is composed of images containing simple geometric shapes of various scales and their equivalent corrupted with Speckle noise following the Log-Compression model. The results of this GAN are displayed and a noticeable improvement can be verified in the image quality.}} }