ABSTRACT
The amplitude of an EMG and the temporal pattern can be used when considering if an EMG profile is normal or not. In the method described in this paper a gain factor of the complete EMG profile was determined and then the profile normalised with this gain factor. This normalised individual profile was then compared with a standard profile, predicted on the basis of walking speed. Deviating profiles were identified when they fell outside the upper and lower 95% limits range for the average profiles of 14 leg muscles. The amount of deviation from the normal profile can be quantified with the normalised mean square difference D2. Gain factors varied over a factor of 4 within a group of 10 normal subjects. For a normal population D2 was below 1. Most muscles had consistent profiles but some patterns could be discerned which showed marked variability among muscles and subjects.
Subject(s)
Electromyography , Muscle, Skeletal/physiology , Walking/physiology , Adult , Case-Control Studies , Humans , Linear Models , Lower Extremity/physiology , MaleABSTRACT
Electromyogram (EMG) profiles strongly depend on walking speed and, in pathological gait, patients do not usually walk at normal speeds. EMG data was collected from 14 muscles in two groups of healthy young subjects who walked at five different speeds ranging from 0.75 to 1.75 ms(-1). We found that average EMG profiles varied in a predictable way with speed. The average EMG profile for each muscle at any speed could be estimated in a simple way from two functions, one constant and one proportionally increasing with walking speed. By taking into account the similarity among profiles within functional groups, the number of basic functions could be reduced further. Any average EMG profile among the 14 leg muscles studied at all speeds in the measured range could be predicted from six constant and ten speed-dependent basic patterns. These results can be interpreted in terms of a central pattern generator for human walking.
