ArticleBiomedical optics express2024
Optical fiber sensor for wearable and accurate human respiratory monitoring.
Article in Biomedical optics express, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- POF cardiorespiratory sensor combined with a thermal imaging temperature sensor for multimodal emotion recognition.Biomedical optics express · 2026Article
- Lighting the Path to Precision Healthcare: Advances and Applications of Wearable Photonic Sensors.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Article
- Sensors, technologies, and classification algorithms for monitoring and diagnosis of sleep apnea.Digital healthReview
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate respiratory monitoring is of great significance in assessing and analyzing physical health, and preventing respiratory diseases. The recently emerged wearable respiratory sensors are confronted with the challenges such as complex fabrication processes, limited accuracy, and stringent wearing requirements. An optical fiber sensor for accurate human respiratory monitoring is proposed and experimentally verified. The sensor head is composed of a piece of seven core fiber sandwiched between two single-mode fibers by two fiber bitapers, which is embedded in a textile sheet and freely worn on the upper body. An efficient signal demodulation system is set up to acquire the respiratory signal, while Fourier transform (FFT) and short-time Fourier transform (STFT) methods are used to analyze the measured signal. Six volunteers are invited to perform the respiratory experiment, and the experimental results demonstrate that the sensor can accurately detect and distinguish respiratory signals under different humans, different states (normal, slow, fast), different body parts (abdomen, chest, back), different postures (standing, sitting, lying), and irregular respiration. The Pearson correlation coefficient of the sensor is higher than 0.9, which is consistent with commercial respiratory sensor. Meanwhile, the instability of the sensor is 0.003 Hz for the same volunteer in 6 months. The sensor has the advantages of high sensitivity, good stability and wearing comfort, showing good potential in healthcare applications.
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Registered trials
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