Heuristics for locating upper extremity joint centres from a reduced set of surface markers

This article presents a set of heuristic algorithms (computational procedur es) for determining upper extremity joint centers from a reduced set of sur face markers (as compared to the conventional scenario of three markers per segment) during three-dimensional (3-D) motions. Two experiments were cond ucted to empirically derive and evaluate the algorithms. The first experime nt characterized the geometric relations between the instantaneous helical axes and corresponding surface markers at the shoulder and elbow. These rel ations, along with anatomic data available in the literature, were employed to derive the geometric heuristics. The heuristics were then enhanced thro ugh a solidification optimization procedure with the objective function of minimizing segment length variability over time. This latter variability wa s also used as the error measure in evaluation of the algorithms. The secon d experiment, incorporating a wide range of upper extremity motions in 3-D, showed the following: (1) the geometric heuristics alone yielded an averag e error of approximately 7.5 mm; (2) with optimization-based enhancement, t he average error was reduced to 3.7 mm; (3) further improvement of the algo rithm performance is achievable by modifying the parameter setting of the o ptimization procedure. While more extensive evaluation is needed before the proposed approach can be generalized, the current work demonstrates the vi ability of heuristic algorithms for estimating upper extremity joint center s based on a reduced set of surface markers and in an efficient manner. (C) 2000 Elsevier Science B.V. All rights reserved.