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Respiration signals are a vital sign of life. Monitoring human breath provides critical information for health assessment, diagnosis, and treatment for respiratory diseases such as asthma, chronic bronchitis, and emphysema. Stretchable and wearable respiration sensors have recently attracted considerable interest toward monitoring physiological signals in the era of real time and portable healthcare systems. This review provides a snapshot on the recent development of stretchable sensors and wearable technologies for respiration monitoring. The article offers the fundamental guideline on the sensing mechanisms and design concepts of stretchable sensors for detecting vital breath signals such as temperature, humidity, airflow, stress and strain. A highlight on the recent progress in the integration of variable sensing components outlines feasible pathways towards multifunctional and multimodal sensor platforms. Structural designs of nanomaterials and platforms for stretchable respiration sensors are reviewed.
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http://dx.doi.org/10.1016/j.bios.2020.112460 | DOI Listing |
Prog Mol Biol Transl Sci
September 2025
Department of Information Sciences and Technology, School of Computing, George Mason University, Fairfax, VA, United States.
Data gathering for diagnostic purposes often relies on psychological instruments and validated tests applied individually through in person interviews. Such an approach is limited since it relies on a subjective perception of the individual as well as their abilities to recall information concerning their behaviors, thoughts, and feelings. Thus, the accuracy of the assessment tends to be unreliable and prone to bias, stigma, as well as subjective interpretations.
View Article and Find Full Text PDFFront Digit Health
August 2025
Architecture Laboratory, Graduate School of Science, Technology and Innovation, Kobe University, Kobe, Japan.
Background: Microwave Doppler sensors, capable of detecting minute physiological movements, enable the measurement of biometric information, such as walking patterns, heart rate, and respiration. Unlike fingerprint and facial recognition systems, they offer authentication without physical contact or privacy concerns. This study focuses on non-contact seismocardiography using microwave Doppler sensors and aims to apply this technology for biometric authentication.
View Article and Find Full Text PDFComput Biol Med
September 2025
Chair of Measurement and Sensor Technology, Chemnitz University of Technology, 09111, Chemnitz, Germany.
With the rise of wearable, affordable solutions using integrated circuits like the AD5933, noise reduction in bioimpedance data has become increasingly important. In this paper, we present an automated method for the realization of a digital filter for noise reduction in bioimpedance data. Unlike traditional methods that require manual tuning, our approach automatically adjusts the filter coefficients based on the characteristics of the incoming bioimpedance data - specifically by minimizing the smoothness difference between consecutive filtered data points.
View Article and Find Full Text PDFJ Biomed Sci
September 2025
Institute of Cellular and System Medicine, National Health Research Institutes, Miaoli, Taiwan.
Aging is the foremost risk factor for metabolic syndrome and atherosclerosis, which is a principal cause of cardiovascular diseases (CVDs). Vascular endothelial cells (ECs), which line the vascular intima, play a central role in maintaining vascular homeostasis. Their dysfunction, marked by impaired barrier function, inflammation, and metabolic dysregulation, constitutes an early and pivotal event in atherogenesis.
View Article and Find Full Text PDFSheng Wu Yi Xue Gong Cheng Xue Za Zhi
August 2025
Department of Research and Development, Hunan Micomme Medical Development Co., Ltd, Changsha 410000, P. R. China.
In order to accurately capture the respiratory muscle movement and extract the synchronization signals corresponding to the breathing phases, a comprehensive signal sensing system for sensing the movement of the respiratory muscle was developed with applying the thin-film varistor FSR402 IMS-C07A in this paper. The system integrated a sensor, a signal processing circuit, and an application program to collect, amplify and denoise electronic signals. Based on the respiratory muscle movement sensor and a STM32F107 development board, an experimental platform was designed to conduct experiments.
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