Название: Wearable Sensing and Intelligent Data Analysis for Respiratory Management
Автор: Rui Pedro Paiva, Paulo de Carvalho
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 357
Язык: английский
Формат: pdf (true)
Размер: 21.0 MB

Wearable Sensing and Intelligent Data Analysis for Respiratory Management highlights the use of wearable sensing and intelligent data analysis algorithms for respiratory function management, offering several potential and substantial clinical benefits. The book allows for the early detection of respiratory exacerbations in patients with chronic respiratory diseases, allowing earlier and, therefore, more effective treatment. As such, the problem of continuous, non-invasive, remote and real-time monitoring of such patients needs increasing attention from the scientific community as these systems have the potential for substantial clinical benefits, promoting P4 medicine (personalized, participative, predictive and preventive). Wearable and portable systems with sensing technology and automated analysis of respiratory sounds and pulmonary images are some of the problems that are the subject of current research efforts, hence this book is an ideal resource on the topics discussed.

The book, organized into 4 parts and 11 chapters, starts with an introductory overview of the process of respiration, its physiology, pathologies, and treatment, followed by the current needs and gaps of respiratory management in daily life. The second part addresses the aspects involved on wearable sensing, namely portable and noninvasive sensor technologies for mobile and wearable applications, and textiles and smart materials. Part III covers the data analysis and management pipeline, from data acquisition, transmission, storage, and representation, to feature engineering and Machine Learning for respiratory sound and image analysis. Finally, Part IV addresses the current key challenges of respiratory management systems, namely the edge-cloud continuum in wearable sensing, strategies for long-term patient adherence, decision support systems, and integrated care in respiratory management.




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