TY - JOUR
T1 - Recent developments in wearable breath sensors for healthcare monitoring
AU - Kim, Dohyung
AU - Lee, Jinwoo
AU - Park, Moo Kyun
AU - Ko, Seung Hwan
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - Within the breath lie numerous health indicators, encompassing respiratory patterns and biomarkers extending beyond respiratory conditions to cardiovascular health. Recently, the emergence of the SARS-CoV-2 pandemic has not only underscored the necessity of on-the-spot breath analysis but has also normalized the use of masks in everyday life. Simultaneously, the rapid evolution of wearable technology has given rise to innovative healthcare monitoring tools, with a specific emphasis on wearable breath sensors. This review explores current research trends in utilizing wearable breathing sensors to detect diverse respiratory biomarkers and monitor respiratory parameters, including airflow, temperature, and humidity. Additionally, it explores diverse applications, ranging from recognizing breathing patterns to swiftly detecting diseases. Integrating the Internet of Things and machine learning technologies into these applications highlights their potential to offer a personalized, accurate, and efficient healthcare solution.
AB - Within the breath lie numerous health indicators, encompassing respiratory patterns and biomarkers extending beyond respiratory conditions to cardiovascular health. Recently, the emergence of the SARS-CoV-2 pandemic has not only underscored the necessity of on-the-spot breath analysis but has also normalized the use of masks in everyday life. Simultaneously, the rapid evolution of wearable technology has given rise to innovative healthcare monitoring tools, with a specific emphasis on wearable breath sensors. This review explores current research trends in utilizing wearable breathing sensors to detect diverse respiratory biomarkers and monitor respiratory parameters, including airflow, temperature, and humidity. Additionally, it explores diverse applications, ranging from recognizing breathing patterns to swiftly detecting diseases. Integrating the Internet of Things and machine learning technologies into these applications highlights their potential to offer a personalized, accurate, and efficient healthcare solution.
UR - http://www.scopus.com/inward/record.url?scp=85188247887&partnerID=8YFLogxK
U2 - 10.1038/s43246-024-00480-w
DO - 10.1038/s43246-024-00480-w
M3 - Review article
AN - SCOPUS:85188247887
SN - 2662-4443
VL - 5
JO - Communications Materials
JF - Communications Materials
IS - 1
M1 - 41
ER -