<title>Statistical methods for analysis of coordination of chest wall motion using optical reflectance imaging of multiple markers</title>

Abstract

To analyze coordination of chest wall motion we have used principle component analysis (PCA) and multiple regression analysis (MRA) with respect to spirometry on the displacements of 93 optical reflective markers placed upon the chest wall (CW). Each marker is tracked at 10 Hz with an accuracy of 0.2 mm in each spatial dimension using the ELITE system (IEEE Trans. Biomed. Eng. 11:943-949, 1985). PCA enables the degree of linear coordination between all of the markers to be assessed using the eigenvectors and eigenvalues of the covariance of the matrix of marker displacements in each dimension against time. Thus the number of linear degrees of freedom (DOF) which contribute more than a particular amount to the total variance can be determined and analyzed. MRA with respect to spirometrically measured lung volume changes enables identification of the CW points whose movement correlates best with lung volume. We have used this analysis to compare a quiet breathing sequence with one where tidal volume was increased fourfold involuntarily and show that the number of DOF with eigenvalues accounting for >5% of the covariance increased from 2 to 3. Also the point whose movement correlated best with lung volume changed from halfway down the lower costal margin to a more lateral point at the level of the bottom of the sternum. This quantification of CW coordination may be useful in analysis and staging of many respiratory disorders and is applicable to any nonrigid body motion where points can be tracked.