Human gait is characterized by smooth, regular and repeating movements
but the control system is complex: there are many more actuators (i.e
. muscles) than degrees of freedom in the system. Statistical pattern-
recognition techniques have been applied to examine muscle activity si
gnals, but these have all concentrated exclusively on unilateral gait.
We report here the application of factor analysis to the electromyogr
aphic patterns of 16 muscles (eight bilateral pairs) in ten normal sub
jects. Consistent with our prior work, we have established two factors
, named loading response and propulsion, which correspond with importa
nt phases in the gait cycle. In addition, we have also discovered a th
ird factor, which we have named the coordinating factor, that maintain
s the phase shift between the left and right sides. These findings sug
gest that the central nervous system solves the problem of high dimens
ionality by generating a few fundamental signals which control the maj
or muscle groups in both legs.