ABSTRACT
Movement-related potentials (MRP), a component of the electroencephalogram (EEG) generated during voluntary movements, are known to vary during adaptation to changing loads and to different load types. This study attempts to reveal these changes. A novel denoising algorithm based on iterative approximation was applied to the MRPs recorded from four subjects while performing simple movements against changing loads. The results show that when subjects perform a repetitive task under a constant load there appears a significant peak in the activity of several MRP components recorded over the prefrontal cortex during the third and fourth repetition of the task. Furthermore, different types of loads do not affect the shape of the MRP but different force intensities do.
