ArticleFrontiers in physiology2020
Development and Clinical Application of a Novel Non-contact Early Airflow Limitation Screening System Using an Infrared Time-of-Flight Depth Image Sensor.
Article in Frontiers in physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Implementation of Thermal Camera for Non-Contact Physiological Measurement: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Estimation of Respiratory Volumes During Tidal Breathing Using Two Depth Cameras.Sensors (Basel, Switzerland) · 2026Article
- Thoracic Motion Analysis Using a TrueDepth Camera in Patients with Relapsing Polychondritis: A Pilot Study.Healthcare (Basel, Switzerland) · 2025Article
- Beyond the Spirometry: New Diagnostic Modalities in Chronic Obstructive Pulmonary Disease.Tuberculosis and respiratory diseases · 2025Article
- Depth-Based Measurement of Respiratory Volumes: A Review.Sensors (Basel, Switzerland) · 2022Review
- Development of a Novel Vital-Signs-Based Infection Screening Composite-Type Camera With Truncus Motion Removal Algorithm to Detect COVID-19 Within 10 Seconds and Its Clinical Validation.Frontiers in physiology · 2022Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obstructive pulmonary diseases, such as diffuse panbronchiolitis (DPB), asthma, chronic obstructive pulmonary disease (COPD), and asthma COPD overlap syndrome (ACOS) trigger a severe reaction at some situations. Detecting early airflow limitation caused by diseases above is critical to stop the progression. Thus, there is a need for tools to enable self-screening of early airflow limitation at home. Here, we developed a novel non-contact early airflow limitation screening system (EAFL-SS) that does not require calibration to the individual by a spirometer. The system is based on an infrared time-of-flight (ToF) depth image sensor, which is integrated into several smartphones for photography focusing or augmented reality. The EAFL-SS comprised an 850 nm infrared ToF depth image sensor (224 × 171 pixels) and custom-built data processing algorithms to visualize anterior-thorax three-dimensional motions in real-time. Multiple linear regression analysis was used to determine the amount of air compulsorily exhaled after maximal inspiration (referred to as the forced vital capacity, FVC
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