The mechanical effects of a muscle are related in part to the size of the muscle and to its location relative to the joint it crosses. For more than a century, researchers have expressed muscle size by its ‘physiological cross-sectional area’ (PCSA). Researchers mathematically calculating muscle and joint forces typically use some expression of a muscle's PCSA to constrain the solution to one which is reasonable (i.e. a solution in which small muscles may not have large forces, and large muscles have large forces when expected or when there is significant electromyographic activity). It is obvious that muscle mass (and therefore any expression of PCSA) varies significantly from person to person, even in individuals of similar weight and height. Since it is not practical to predict the PCSA of each muscle in a living subject's limb or trunk, it is important to generally understand the sensitivity of muscle force solutions to possible variations in PCSA.

We used nonlinear optimization techniques to predict 47 muscle forces and hip contact forces in a living subject. The PCSA (volume/muscle fiber length) of each of 47 lower limb muscle elements from two cadaver specimens and the 47 PCSA's reported by Pierrynowski were input into an optimization algorithm to create three solution sets. The three solutions were qualitatively similar but at times a predicted muscle force could vary as much as two to eight times. In contrast, the joint force solutions were within 11% of each other and, therefore, much less variable.

When using optimization techniques to predict muscle forces, it must be recognized that the solution is sensitive to many assumptions and variables such as PCSA. The muscle force solutions are therefore best used to determine relative values (i.e. trends) in parametric studies. On the other hand, the joint force solutions are less sensitive to such variations, and the absolute values are more reliable.