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 paper presents a method for JC locations based on the multiple regression algorithms without preliminary assumption on the behavior 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. Mean accuracy errors on the JC locations obtained on dry bones were 5.2±2.5 mm for the humeral head, 2.5±1.1 mm for the humeral trochlea, 2.3±0.9 mm for the humeral capitulum, 8.2±3.9 mm for the scapula glenoid cavity, 7.2±3.2 mm for the scapular aspect of the acromio-clavicular joint, 3.5±1.8 mm for the clavicular aspect of the sternoclavicular joint and 3.2±1.4 mm for the clavicular aspect of the acromio-clavicular joint. In-vitro and in-vivo validation accuracy was 5.3 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 paper.