Modeling of the pliant surfaces of the thigh and leg during gait

Abstract

Rigid Body Modeling, a 6 degree of freedom (DOF) method, provides state of the art human movement analysis, but with one critical limitation; it assumes segment rigidity. A non-rigid 12 DOF method, Pliant Surface Modeling (PSM) was developed to model the simultaneous pliant characteristics (scaling and shearing) of the human body's soft tissues. For validation, bone pins were surgically inserted into the tibia and femur of three volunteers. Infrared markers (44) were placed upon the thigh, leg and bone pin surfaces. Two synchronized OPTOTRAKI3O2OTM cameras (Northern Digital Inc., Waterloo, ON) were used to record 120 seconds of treadmill gait per subject. In comparison to the "gold standard" bone pin rotational results, PSM located the tibia, femur and tibiofemoral joint with root mean square (RMS) errors of 2.4°, 4.0° and 4.6°, respectively. These performances met or exceeded (P<.0l) the current state of the art for surface data, Rigid Surface Modeling. The thigh's measured surface experienced uniform repeatable changes in scale: 40% mediolateral, 5% anterioposterior, 5% superioinferior, and planar shears of: 25° transverse, 1 5° sagittal, 5°f rontal. With the brief exception of push-off, the lower leg demonstrated much greater rigidity: <5% scaling and <5° shearing. Thus, PSM offers superior "rigid" estimates of knee motion with the ability to quantify "pliant" surface changes.

Human movement analysis using stereophotogrammetry

“…These techniques can also be differentiated by those modeling the external segment surface alone [35,39,[42][43][44] and those addressing also segment relative motion [38,40,[47][48][49][50][51][52][53][54][55]. The former enhances the traditional methods of segment pose optimal estimation [36,56] by explicitly addressing the random and systematic effects of STA and considers absolute and relative motion of the skin markers in a purely geometric view, irrespective of the physiological event generating the STA and irrespective of joint motion and constraints.…”

“…Techniques based on minimization of a general error function, either defined locally to the single body segment [35,36,39,[42][43][44] or globally to the entire lower limb [47][48][49][50][51][52][53][54][55], and on compensation of an assessed measurement of STA [38,40] have been proposed in the literature to optimize bone pose estimation. These techniques can also be differentiated by those modeling the external segment surface alone [35,39,[42][43][44] and those addressing also segment relative motion [38,40,[47][48][49][50][51][52][53][54][55].…”

“…Another study [39] compared traditional rigid body modeling (RBM), which assumes body segment and surface rigidity and 6 DOF, with a novel non-rigid, 12 DOF method, also referred to as pliant surface modeling (PSM). The latter provided for simultaneous quantification of rigid rotations and translations, plus 'pliant' (scales and shears) motion accounting for deformation of the marker cluster associated with skin stretching, muscle activity and inertial phenomena.…”

Soft tissue artifact compensation by linear 3D interpolation and approximation methods

“…Several compensation methods have been proposed . The motion of the skin makers can be minimized by least square methods (Spoor and Veldpaus, 1980;Veldpaus et al, 1988;Soderkvist and Wedin, 1993;Challis, 1995) and can be specifically modeled (Ball and Pierrynowski, 1998;Alexander and Andriacchi, 2001;Cappello et al, 2005;Camomilla et al, 2009;Ryu et al, 2009). STA compensation is analogous to non-rigid body registration (Holden, 2008) and anthropometric scaling (Lewis et al, 1980;Sommer et al, 1982) as they include spatial transformations of a set of 3D points.…”

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

“…Alternatively, the transformation can be approximated by a translation and a general non-singular tensor, which permits homogeneous deformation (including stretching and shearing). This approach was implemented in several studies under the framework of affine mapping (Ball and Pierrynowski, 1998;Dumas and Chèze, 2009;Solav et al, 2014), and will be referred to in this paper as homogeneous deformation least squares (HDLS). RBLS and HDLS generally obtain different results (Dumas and Chèze, 2009;Rubin and Solav, 2016;Solav et al, 2014).…”