Research Topic

ICT for Respiratory Function Assessment

About this Research Topic

Respiratory diseases, such as chronic obstructive pulmonary disease (COPD), lower respiratory tract infections or asthma, have a significant impact on both patient's health-related quality of life, healthcare systems and society in general. Recent studies estimate that, worldwide, around 339 million people suffer from asthma and that, by 2030, COPD will become the third leading cause of death. This poses severe burdens to healthcare systems in terms of outpatient and inpatient care, as well as pharmaceutical costs, which are highly correlated with the severity of exacerbation episodes.

In this scenario, the use of ICT for respiratory function assessment assumes particular relevance, offering several potential and substantial clinical benefits. Namely, it allows for the early detection of respiratory exacerbations in patients with chronic respiratory diseases, allowing earlier and, therefore, more effective treatment. Early intervention in exacerbations of these conditions has been shown to decrease hospitalization rates and improve long-term outcomes, including survival.
As such, presently, the problem of continuous, non-invasive, remote and real-time monitoring of such patients is deserving of increasing attention from the scientific community. 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. Such systems have the potential for substantial clinical benefits, promoting the so-called P4 medicine (personalized, participative, predictive and preventive).

This Research Topic of Frontiers in Computer Science aims to select high-quality original research focused on the use of ICT methodologies and systems for respiratory function assessment. Topics of interest include, but are not limited to:
- Wearable, portable, non-invasive and p-health systems, biomedical sensor technology and textiles
- Data management: acquisition, transmission, storage, representation, visualization, security, privacy, etc.
- Data science and big data
- Automated respiratory sound analysis: cough, crackles, wheezes and all sort of clinically-relevant respiratory sounds
- Pulmonary image reconstruction and analysis: electrical impedance tomography, computed tomography, magnetic resonance imaging, etc.
- Information fusion approaches: multi-channel and multi-sensor approaches towards respiratory function assessment
- Human-Computer Interaction and usability studies
- Risk management and decision-support systems
- ICT-based clinical studies tackling respiratory diseases and co-morbidities
- Applications of ICT in respiratory healthcare


Note: The final list of participation Journals will be shortly available on the website


Keywords: wearable sensors, portable sensors, textiles sensors, data management, ICT-based clinical studies, respiratory signal analysis


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Respiratory diseases, such as chronic obstructive pulmonary disease (COPD), lower respiratory tract infections or asthma, have a significant impact on both patient's health-related quality of life, healthcare systems and society in general. Recent studies estimate that, worldwide, around 339 million people suffer from asthma and that, by 2030, COPD will become the third leading cause of death. This poses severe burdens to healthcare systems in terms of outpatient and inpatient care, as well as pharmaceutical costs, which are highly correlated with the severity of exacerbation episodes.

In this scenario, the use of ICT for respiratory function assessment assumes particular relevance, offering several potential and substantial clinical benefits. Namely, it allows for the early detection of respiratory exacerbations in patients with chronic respiratory diseases, allowing earlier and, therefore, more effective treatment. Early intervention in exacerbations of these conditions has been shown to decrease hospitalization rates and improve long-term outcomes, including survival.
As such, presently, the problem of continuous, non-invasive, remote and real-time monitoring of such patients is deserving of increasing attention from the scientific community. 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. Such systems have the potential for substantial clinical benefits, promoting the so-called P4 medicine (personalized, participative, predictive and preventive).

This Research Topic of Frontiers in Computer Science aims to select high-quality original research focused on the use of ICT methodologies and systems for respiratory function assessment. Topics of interest include, but are not limited to:
- Wearable, portable, non-invasive and p-health systems, biomedical sensor technology and textiles
- Data management: acquisition, transmission, storage, representation, visualization, security, privacy, etc.
- Data science and big data
- Automated respiratory sound analysis: cough, crackles, wheezes and all sort of clinically-relevant respiratory sounds
- Pulmonary image reconstruction and analysis: electrical impedance tomography, computed tomography, magnetic resonance imaging, etc.
- Information fusion approaches: multi-channel and multi-sensor approaches towards respiratory function assessment
- Human-Computer Interaction and usability studies
- Risk management and decision-support systems
- ICT-based clinical studies tackling respiratory diseases and co-morbidities
- Applications of ICT in respiratory healthcare


Note: The final list of participation Journals will be shortly available on the website


Keywords: wearable sensors, portable sensors, textiles sensors, data management, ICT-based clinical studies, respiratory signal analysis


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 May 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 May 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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