## 1 Introduction
However, the in vivo power produced by any single muscle cannot be directly determined. Hence other methods are required. An impediment to the easy assessment of muscle power--and the potential role of individual knee muscles--is that the knee has more muscles crossing that joint than are necessary to perform basic movements. This overabundance of muscles leads to statistical indetermination, where the number of unknown muscle forces is greater than the available solution set of equations [29]. Combining individual muscles into muscle groups simplifies the appraisal, as the number of unknown synergistic power generators is equal to or less than the solution set of equations [30; 31; 32]. Consequently, power calculation approaches are typically based on inverse dynamics techniques. This method solves the actuator-redundancy problem. However, conventional power analysis cannot define the unique power contribution of a single muscle (except in uncommon cases where only a single muscle is responsible for the observed movement). Co-contraction of agonists and antagonists is an additional confound [33; 34; 35]. As a result, there may not be a direct link between a muscle's power output (via inverse dynamics techniques) and that muscle's true role in gait. A single cost function is typically minimized or maximized (e.g., muscle endurance, muscle stress, and metabolic cost) as kinematic data is combined with certain objective function assumptions [34; 35; 36; 37]. However, two aspects related to optimization research remain limitations. First, obtaining a solution can be very time-intensive [29]. A more important issue that cannot be circumvented is that the determination of objective functions remains subjective, as several solution sets may satisfy the stated criteria [28]. Muscle force estimates have been made via an electromyogram-driven model [9; 10; 11; 12; 13; 14; 27; 38; 39; 40; 41]. Determining muscle power follows from force estimates as the power produced by each muscle is the product of its force output and contraction velocity. The EMG-to-force processing method has the advantage of providing a unique solution set [42; 43]. Thus far, only estimations of knee muscle forces have been reported, independent of the method selected (optimization theory and neuromuscular modeling) to examine the role of individual muscles. That is, muscle forces--and not power--have been the emphasis of prior efforts. This work broadens these analyses as the role of muscles can now be assessed based on both muscle force and power production (type of contraction). Muscle force estimates have been made via inference from the joint moments. However, the type of muscle contraction--eccentric, isometric, and concentric--cannot be determined solely from joint moments. The purpose of this study was to determine each knee muscle's contribution to knee joint power and to provide insight into the distinctive role of these muscles during normal, self-selected speed walking. Knee muscle power during level, self-selected speed walking was determined via an EMG-to-force processing (EFP) model and by standard inverse dynamics (kinematics plus kinetics, KIN) during the same gait trial for each study participant.