ESS - CAR - Comunicações em eventos científicos
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Browsing ESS - CAR - Comunicações em eventos científicos by Author "Almeida, Rute"
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- AIRDOC: Smart mobile application for individualized support and monitoring of respiratory function and sounds of patients with chronic osbtructive diseasePublication . Almeida, Rute; Amaral, Rita; Jácome, Cristina; Martinho, Diogo; Vieira-Marques, Pedro; Jacinto, Tiago; Ferreira, Ana; Almeida, Ana; Martins, Constantino; Pereira, Mariana; Pereira, Ana; Valente, José; Almeida, Rafael; Vieira, Ana; Amaral, Rita; Sá-Sousa, Ana; Gonçalves, Ivânia; Rodrigues, Pedro; Alves-Correia, Magna; Freitas, Alberto; Marreiros, GoretiCurrent tools for self-management of chronic obstructive respiratory diseases (CORD) are difficult to use, not individualized and requiring laborious analysis by health professionals, discouraging their use in healthcare. There is an opportunity for cost-effective and easy-to-disseminate advanced technological solutions directed to patients and attractive to different stakeholders. The strategy of AIRDOC is to develop and integrate self-monitoring and self-managing tools, making use of the smartphone's presence in everyday life. AIRDOC intends to innovate on: i) technologies for remote monitoring of respiratory function and computerized lung auscultation; ii) coaching solutions, integrating psychoeducation, gamification and disease management support systems; and iii) management of personal health data, focusing on security, privacy and interoperability. It is expected that AIRDOC results will contribute for the innovation in CORD healthcare, with increased patient involvement and empowerment while providing quality prospective information for better clinical decisions, allowing more efficient and sustainable healthcare delivery.
- Automatic quality assessment of a forced expiratory manoeuvre acquired with the tablet microphonePublication . Almeida, Rute; Bernardo, Pinho; Jácome, Cristina; Teixeira, João Fonseca; Amaral, Rita; Gonçalves, Ivânia; Lopes, Filipa; Pinheiro, Ana Catarina; Jacinto, Tiago; Paixão, Cátia; Pereira, Mariana; Marques, Alda; Fonseca, João AlmeidaEvaluation of lung function is central to the management of chronic obstructive respiratory diseases. It is typically evaluated with a spirometer by a specialized health professional, who ensures the correct execution of a forced expiratory manoeuvre (FEM). Audio recording of a FEM using a smart device embedded microphone can be used to self-monitor lung function between clinical visits. The challenge of microphone spirometry is to ensure the validity and reliability of the FEM, in the absence of a health professional. In particular, the absence of a mouthpiece may allow excessive mouth closure, leading to an incorrect manoeuvre. In this work, a strategy to automatically assess the correct execution of the FEM is proposed and validated. Using 498 FEM recordings, both specificity and sensitivity attained were above 90%. This method provides immediate feedback to the user, by grading the manoeuvre in a visual scale, promoting the repetition of the FEM when needed.
- Combined image-based approach for monitoring the adherence to inhaled medicationsPublication . Vieira-Marques, Pedro; Teixeira, João Fonseca; Valente, José; Pinho, Bernardo; Guedes, Rui; Almeida, Rute; Jácome, Cristina; Pereira, Ana; Jacinto, Tiago; Amaral, Rita; Gonçalves, Ivânia; Sousa, Ana Sá; Couto, Mariana; Magalhães, Manuel; Bordalo, Diana; Silva, Luís Nogueira; Fonseca, J. AlmeidaThe adherence to inhaled controller medications is of critical importance to achieve good clinical results in patients with chronic respiratory diseases. To objectively verify the adherence, a detection tool was previously developed and integrated in the mobile application InspirerMundi, based on image processing methods. In this work, a new approach for enhanced adherence verification was developed. In a first phase template matching is employed to confirm the inhaler positioning and to locate the dose counter. In a second phase Google ML Kit framework is used for the detection of each numerical dose in the dose counter. The proposed approach was validated through a new detection tool pilot implementation, using a set of images collected by patients using the application in their daily life. Performance of each of the two phases was evaluated for a set of commonly used inhaler devices. Promising results were achieved showing the potential of mobile embedded sensors without the need for external devices.
- A comparison of unsupervised methods based on dichotomous data to identify clusters of airways symptoms: latent class analysis and partitioning around medoids methodsPublication . Amaral, Rita; Jacinto, Tiago; Pereira, Ana; Almeida, Rute; Fonseca, JoãoLatent class analysis (LCA) and partitioning around medoids (PAM) are popular data-driven methods for partitioning objects based on dichotomous data, remaining not clear which is better for large epidemiological datasets. Hence, we compared these methods in the identification of clusters of subjects with airways symptoms, using a large population-based data from the U.S. National Health and Nutrition Examination Surveys (NHANES).
- Data-driven prescription patterns in patients under maintenance treatment for respiratory diseases from the Portuguese prescription databasePublication . Sá-Sousa, Ana; Amaral, Rita; Almeida, Rute; Freitas, Alberto; Fonseca, João AWe aimed to identify prescription patterns in respiratory patients using an unsupervised (data-driven) method, in a random sample of patients aged >14 years (n=8799), retrieved from the Portuguese Electronic Medical Prescription database. Respiratory patients were defined if >2 packs of maintenance treatment for respiratory diseases were prescribed in 2016. We analysed all the prescriptions (n=39810) for respiratory diseases and exacerbations by medication type. Two-step clustering was based on the presence of ICS, LABA, LTRA, LAMA, LABA, SABA, SAMA and on the speciality of prescriber.
- Engagement and usage patterns of a mobile application to monitor disease and treatment adherence in patients with asthmaPublication . Almeida, Rute; Jácome, Cristina; Vieira-Marques, Pedro; Pereira, Ana; Sá-Sousa, Ana; Amaral, Rita; Valente, José; Fonseca, João Almeida; Amaral, RitaInhaled therapies are the cornerstone of effective asthma treatment and adequate inhaled medication adherence (IMA) is critical. mHealth technologies have shown to be promise for asthma self-management, including IMA improvement. InspirerMundi is a mobile application designed to support self-management of patients with asthma. It aims to transform the adherence to treatment into a positive experience through gamification and social interaction while allowing for ubiquitous verified IMA monitoring. The app includes an image-based inhaler usage detection tool, tools for reporting symptoms and burden of the asthma (disease monitoring) and Game & Peer support features. Still, the effectiveness of these tools depends on a regular app use and a real-life assessment of patient engagement and pattern of use is needed. This work evaluates the patient engagement, usage, and acceptance of InspirerMundi app during a real-world multicentre feasibility study. The app use was recommended for a 4-months period to 77 participants with persistent asthma. From those, 72 installed the app, with 67% of them beginning to use both the inhaler usage detection tool and the disease monitoring components within the first week. Over 95% used it more than once, with the period of usage (from first use to last registered monitoring in 2018) being over 30 days for almost 70% of the users, and over 90 days for around 35%. Nevertheless, the usage rate (ratio of the number of days with app usage and the period of use) had a median value of 0.6 and was above 75% for only 35% of the users, revealing room for improvement. In general, the users started to use the app features right after installation and the usage patterns and retention rates indicate that InspirerMundi is well accepted among patients with asthma.
- Quality assessment and feedback of Smart Device Microphone Spirometry executed by childrenPublication . Almeida, Rute; Pinho, Bernardo; Jácome, Cristina; Teixeira, Joao Fonseca; Amaral, Rita; Lopes, Filipa; Jacinto, Tiago; Guedes, Rui; Pereira, Mariana; Goncalves, Ivania; Fonseca, Joao AlmeidaSmart device microphone spirometry, based on the audio recording of forced expiratory maneuver (FEM), can be a simple, ubiquitous and easy tool for patients to self-monitor their asthma. Automatic validity assessment is crucial to guarantee that the global effort of the FEM fulfil the admissible minimum or if the maneuver needs to be repeated. In this work an automatic method to classify the sounds from FEM with respect to global effort was developed and evaluated using data from 54 children (5-10 years). The method proposed was able to correctly classify the microphone spirometry with respect to admissible minimum of effort with an accuracy of 86% (specificity 87% and sensitivity 86%). This method can be used to provide immediate feedback of the correct execution of the maneuver, improving the clinical value and utility of this self-monitoring tool.
- Reproducibility of the Vivatmopro measurements for exhaled nitric oxide valuesPublication . Amaral, Rita; Jácome, Cristina; Almeida, Rute; Sá-Sousa, Ana; Pinho, Bernardo; Guedes, Rui; Jacinto, Tiago; Fonseca, JoãoPortable monitoring devices allow fraction exhaled nitric oxide (FeNO) measurements outside clinical settings. However, the reproducibility of the new portable device Vivatmo pro is not yet fully established. In this study, we aimed to assess the reproducibility of this device for FeNO measurements.