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- 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.
- Real-time clinical decision support at the point of carePublication . Pereira, Ana Margarida; Jácome, Cristina; Amaral, Rita; Jacinto, Tiago; Fonseca, João A.This chapter starts by introducing the complex process of shared clinical decision-making, the value of incorporating patient-reported outcome measures into clinical decisions and the increasing usefulness of clinical decision support systems to enhance the quality and safety of healthcare. It then gives examples of three tools for clinical decision support at the point of care, which were designed to support health professionals and patients in the assessment, treatment and long-term management of chronic respiratory diseases.