Study on Discrimination of Finger Motions based on EMG signals

In recent years, biological signals have attracted attention as tools for human interfaces. Researches on biological signals have been actively conducted. In this paper, we propose a method which distinguishes ten motions, such as “One” “Two” “Three” “Four” “Five” “Six” “Seven” “Eight” “Nine” and “Ten” by measured the electromyogram of the wrist. We measure data by installing 8 dry type sensors on the right wrist. We carry out frequency analysis using FFT and try to take 3 kinds of methods to remove noise. Finally, we use Support Vector Machine (SVM) for identification and classification. We conducted experiments with four subjects. In the experimental result, the accuracy of finger motions recognition was 65%. In the future, we will also add more methods to remove noise, and try to find other methods to improve the accuracy in the research.