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Monitoring the Wall Mechanics During Stent Deployment in a Vessel
Published on: May 8, 2012
Time-of-flight abdominal wall displacement for non-invasive longitudinal monitoring of pulmonary function
1Institute of Metrology and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology, 02-525 Warsaw, Poland.
Abstract:
Objective. Spirometry is the clinical gold standard for pulmonary function testing, but its reliance on mouthpiece-based airflow, trained supervision, and patient effort limits its use for frequent or home-based monitoring. This study investigates a single-point time-of-flight (TOF) sensor to capture abdominal wall displacement as a non-contact surrogate for spirometric indices.Approach. Displacement signals were recorded from 31 adult volunteers during quiet breathing, vital capacity (VC), and forced VC (FVC) manoeuvres, with simultaneous spirometry as reference. A preprocessing framework with filtering, segmentation, and feature extraction was developed, and subject-specific two-point calibration mapped displacement to lung volume. TOF-derived measures were compared to spirometry using agreement analyses, with BA plots used to quantify bias and limits of agreement for key indices.Main results. TOF signals accurately reproduced volume-related parameters: tidal volume, VC, and maximal voluntary ventilation agreed well with spirometry after calibration, with mean differences within clinically acceptable ranges. Estimation of the FEV₁/FVC ratio showed greater variability. After exclusion of one artifactual TOF measurement, BA analysis showed a small positive bias (∼+0.05) with limits of agreement of approximately -0.1 to +0.2. All TOF-derived ratios exceeded the clinical threshold of 0.7, supporting correct classification of normal ventilatory function in this cohort.Significance. These results indicate that although single-point TOF sensing cannot replace spirometry, it offers a non-contact, subject-specific calibration-minimal method for estimating pulmonary function, with promising applications in longitudinal monitoring, telehealth, and early screening.
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