Validation of a new method for bone motion measurement by soft-tissue artifact compensation through spatial interpolation

Localizing a bone hidden behind soft tissue is crucial in biomechanics. A typical approach consists in placing markers on the skin, measuring their position/orientation, and from these measurements, estimating the position and orientation of the bone hidden behind the skin while compensating of soft tissue deformations. In this paper, we present a new method to address this problem. It requires to initially record scattered spacial transformations between the rigid body and the markers. Then, a natural neighbors interpolation algorithm, modified to apply to homogeneous transformations, is proposed. The presented method is validated on a robot manipulator on which soft tissue is placed.

[1]  Anthony G Schache,et al.  Non-invasive assessment of soft-tissue artifact and its effect on knee joint kinematics during functional activity. , 2010, Journal of biomechanics.

[2]  A. Householder,et al.  Discussion of a set of points in terms of their mutual distances , 1938 .

[3]  François Lavaste,et al.  On the estimation of knee joint kinematics , 1999 .

[4]  Sylvain Brochard,et al.  Double calibration: an accurate, reliable and easy-to-use method for 3D scapular motion analysis. , 2011, Journal of biomechanics.

[6]  A Roby-Brami,et al.  3-D scapular kinematics during arm elevation: effect of motion velocity. , 2006, Clinical biomechanics.

[7]  A R Karduna,et al.  Dynamic measurements of three-dimensional scapular kinematics: a validation study. , 2001, Journal of biomechanical engineering.

[8]  B. Fregly,et al.  A solidification procedure to facilitate kinematic analyses based on video system data. , 1995, Journal of biomechanics.

[9]  R. Sibson,et al.  A brief description of natural neighbor interpolation , 1981 .

[10]  T. Mcadams Three-Dimensional Scapulothoracic Motion During Active and Passive Arm Elevation , 2006 .

[11]  Alberto Leardini,et al.  Soft tissue artifact compensation in knee kinematics by double anatomical landmark calibration: performance of a novel method during selected motor tasks , 2005, IEEE Transactions on Biomedical Engineering.

[12]  Michael Patrick Johnson,et al.  Exploiting quaternions to support expressive interactive character motion , 2003 .

[13]  G R Johnson,et al.  The measurement of three dimensional scapulohumeral kinematics--a study of reliability. , 1999, Clinical biomechanics.

[14]  Sylvain Brochard,et al.  In vivo estimation of the glenohumeral joint centre by functional methods: accuracy and repeatability assessment. , 2010, Journal of biomechanics.

[15]  Y. Oshman,et al.  Averaging Quaternions , 2007 .

[16]  Gerald E. Farin,et al.  Natural neighbor extrapolation using ghost points , 2009, Comput. Aided Des..

[17]  Yi Li,et al.  A novel dataglove calibration method , 2010, 2010 5th International Conference on Computer Science & Education.

[18]  Alain Fournier,et al.  Reconstructing 2D images with natural neighbour interpolation , 2001, The Visual Computer.

[19]  G. Seber Multivariate observations / G.A.F. Seber , 1983 .

[20]  Anthony M J Bull,et al.  Skin-fixed scapula trackers: a comparison of two dynamic methods across a range of calibration positions. , 2011, Journal of biomechanics.

[21]  A Leardini,et al.  Position and orientation in space of bones during movement: anatomical frame definition and determination. , 1995, Clinical biomechanics.

[22]  Jonathan P. Braman,et al.  Motion of the shoulder complex during multiplanar humeral elevation. , 2009, The Journal of bone and joint surgery. American volume.

[23]  F Charleux,et al.  Quantification of the 3D relative movement of external marker sets vs. bones based on magnetic resonance imaging. , 2006, Clinical biomechanics.

[24]  Andrew R Karduna,et al.  Three-dimensional scapulothoracic motion during active and passive arm elevation. , 2005, Clinical biomechanics.

[25]  B. Bru,et al.  A new method for determining the location of the instantaneous axis of rotation during human movements , 2009 .