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Sensors for Breathing Monitoring—2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: 20 April 2026 | Viewed by 351

Special Issue Editors


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Guest Editor
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Interests: bioengineering of the respiratory system; physiological measurements; biomedical instrumentation and sensors and functional lung imaging
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Physiology, Hyogo Medical University, Nishinomiya 663-8501, Japan
Interests: control of breathing; especially; rhythm generation; pattern formation; coordination between swallowing and breathing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We invite you to participate in the Special Issue “Sensors for Breathing Monitoring—2nd Edition”. Breathing monitoring is essential to detecting apnea, hypopnea, and other respiratory abnormalities in clinical settings. Further, respiratory fluctuation presents valuable information that can be used in clinical practice for diagnosis, emotion recognition, and mental conditioning. The recent advancement of sensor technology in combination with machine learning and information theory-based techniques has enabled us to extract hidden information from respiratory fluctuation and translate it into usable forms.

In recent decades, various sensors for breathing monitoring have been developed, which can be classified as 1. airflow-based sensors (e.g., pneumotachograph, thermistor, capnometer, acoustic sensors, etc.); 2. chest wall motion-based sensors (e.g., magnetometer, inductive plethysmography, impedance pneumography, piezoelectric sensors, accelerometer, optical sensors, radio frequency-based methods, etc.); and 3. methods based on respiratory modulation of other physiological signals such as electrocardiograms, arterial pulse wave transit time, photoplethysmograms (PPGs), and imaging PPG.

One of the key issues is establishing an appropriate method for a specific purpose. To accomplish this, we must know the characteristics (accuracy, stability, and restrictions) of these sensors, on the one hand, and the requirements needed to meet the specific purpose, on the other hand.

Contributions to this Special Issue may include, but are not limited to, the following:

  • Novel sensing techniques for breathing monitoring;
  • Practical sensor implementations for diagnosis, emotion recognition, and mental conditioning;
  • New insights into breathing complexity that provide methods to extract useful information. 

Prof. Dr. Andrea Aliverti
Prof. Dr. Yoshitaka Oku
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • breath monitoring
  • apnea detecting
  • wearable sensors
  • gas sensors
  • physiological signals

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Related Special Issue

Published Papers (1 paper)

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Research

15 pages, 46278 KB  
Article
Assessment of KN95 Mask Filtering Degradation and Breathing Detection: A Pilot Study
by Julie Payette, Alexandre Perrotton, Paul Fourmont, Fabrice Vaussenat, Jaime A. Benavides, Luis Felipe Gerlein and Sylvain G. Cloutier
Sensors 2025, 25(24), 7623; https://doi.org/10.3390/s25247623 - 16 Dec 2025
Viewed by 159
Abstract
This study aims to monitor mask performance in operando using all-printed humidity sensor arrays based on BiFeO3/BiOCl heterostructures. Two screen-printed 19-sensor arrays are fixed directly atop the mask, in order to analyze moisture levels in exhaled breath and extract performance indicators. [...] Read more.
This study aims to monitor mask performance in operando using all-printed humidity sensor arrays based on BiFeO3/BiOCl heterostructures. Two screen-printed 19-sensor arrays are fixed directly atop the mask, in order to analyze moisture levels in exhaled breath and extract performance indicators. This approach allows for an examination of the humidity saturation and absorption over time during operation. Accumulation of moisture within the mask can affect its performance, and factors like breath humidity, mask material, and ambient conditions influence this. Results show that the measured data follows an exponential decay, achieving correlation factors of over 0.9 for all tests. We also detect breathing differences through feature extraction, investigating the respiration rates and signal amplitudes for both normal and deep breathing. Furthermore, we animated the airflow in the mask in both 2D and 3D, allowing for the eventual detection of leaks for ill-fitting masks. This study introduces an innovative approach for the assessment of mask fit and longevity, contributing to improving mask efficacy and public health outcomes. Full article
(This article belongs to the Special Issue Sensors for Breathing Monitoring—2nd Edition)
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