Sensors for Breathing Monitoring

Dear Colleagues,

We would like to cordially invite you to participate in a Special Issue on “Sensors for Breathing Monitoring”. Breathing monitoring is essential in clinical settings to detect apnea, hypopnea, and other respiratory abnormalities. Further, respiratory fluctuation contains 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 such hidden information from respiratory fluctuation and translate it into usable forms.

Various sensors for breathing monitoring have been developed during recent decades that 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 on other physiological signals such as electrocardiograms, arterial pulse wave transit time, photoplethysmograms (PPG), and imaging PPG.

One of the key issues is to figure out 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 to meet the purpose on the other hand.

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

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

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

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