Time-frequency analysis of the surface EMG during maximum height jumps under altered-G conditions

Surface electromyographic (SEMG) signals are often used to study motor control during human movement. Typically, the SEMG signal is used to determine when the muscle was on or off during the movement. However, determining the time-based frequency content of the SEMG signal in conjunction with the time-history of the movement may provide us with more insight into how the motion is organized. We collected SEMG from 4 muscles, (soleus, vasti, gluteus maximus, hamstrings) while subjects performed jumping and sit-to-stand tasks under altered g-environments. The experiment was performed on the Dynamic Environmental Simulator at Wright Patterson AFB, OH. The subjects performed the tasks at 1.0, 1.2, 1.4, 1.6, and 1.8 g. The SEMG signals were then analyzed using a continuous discrete wavelet transform based on a 4-coefficient Daubechie wavelet. Our initial results show that although the time-history of muscle activation patterns during movements do not always vary significantly at different g levels, the frequency content does change, with more high frequency activation at low g levels, and more low frequency activation at higher g levels. One possible explanation for the difference in frequency activation is fatigue of fast twitch fibers during the experiment. These differences were not apparent from the time-history activation patterns, and are difficult to interpret from standard FFT manipulations.