Prediction of joint center location by customizable multiple regressions: application to clavicle, scapula and humerus

Accurate spatial location of joint center (JC) is a key issue in motion analysis since JC locations are used to define standardized anatomical frames, in which results are represented. Accurate and reproducible JC location is important for data comparison and data exchange. This research developed a method for JC locations based on multiple regression algorithms without preliminary assumption on the behaviour of the joint-of-interest. Regression equations were obtained from manually palpable ALs on each bone-of-interest. Results are presented for all joint surfaces found on the clavicle, scapula and humeral bone. In-vitro and in-vivo validation accuracy was 5.3 mm and 8.5 mm, respectively, for the humeral head center location. Regression coefficients for joint radius dimension and joint surface orientation were also processed and reported in this research.

Extension of this method to the lower limb, spine and skull is also running.

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