Improving EMG based muscle force estimation using principal component analysis on a high-density EMG array - Staudenmann, D.; Kingma, I.; Daffertshofer, A.; Stegeman, D. F.; van Dieën, J. H. (ISB Congress, 2005)
The aim of this experimental study is to analyze whether PCA techniques (Principle component analysis) can improve force estimation from EMG collected with a high-density array. Conclusion: High-density EMG is a powerful tool for the prediction of force output of a muscle but its value depends strongly on the EMG signal procedures. PCA can be used as an alternative to spatial filtering with different electrode configurations (3-5). Apparently, any order of spatially filtering electrodes (3-5) suffers from a biased choice of the configuration direction relative to the direction of the underlying muscle fibers. PCA appears to be a valuable tool, extracting the physiologically relevant information independent from the muscle structure and thereby improving the quality of muscle force estimation.