@ARTICLE{7763855, 
author={V. Soleimani and M. Mirmehdi and D. Damen and J. Dodd and S. Hannuna and C. Sharp and M. Camplani and J. Viner}, 
journal={IEEE Transactions on Biomedical Engineering}, 
title={Remote, Depth-Based Lung Function Assessment}, 
year={2017}, 
volume={64}, 
number={8}, 
pages={1943-1958}, 
keywords={biomedical optical imaging;calibration;data analysis;feature extraction;lung;medical signal processing;pneumodynamics;signal reconstruction;FVC;SVC;automatic extraction;calibration;chest surface motion;chest volume variation;clinical PFT measures;depth sensor;depth-based approach;flow-time data sequence;forced vital capacity;intrasubject measures;intratest measures;main effort sections;point cloud generation;prevalent spirometry tests;pulmonary function testing;remote depth-based lung function assessment;remote noninvasive approach;respiratory outpatient service;scene depth values;slow vital capacity;subject chest;subject torso motion;three-dimensional model;tidal volume;traditional cumbersome methods;volume-time data analysis;volume-time data sequence;Biomedical measurement;Cameras;Correlation;Electrical resistance measurement;Lungs;Static VAr compensators;Volume measurement;Kinect noise analysis;chest surface reconstruction;chest volume estimation;forced vital capacity (FVC);pulmonary function testing (PFT);slow vital capacity (SVC);spirometry},
doi={10.1109/TBME.2016.2618918}, 
ISSN={0018-9294}, 
month={Aug},}