Analysis and recognition of wrist motions by using multidimensional directed information and EMG signal
We propose a recognition system of wrist motions using EMG signals. The objective in this paper is to recognize 7 wrist patterns using EMG signals measured in wrist. Many EMG signal researches have been presented in humanitarian use for handicapped persons. However, almost all the researches were based on measurement from comparatively large muscular region such as arm and shoulder in data measurement location. The EMG signals are measured with 4-channel sensor in wrist and are recorded as 4 channel's time series data. Multi-dimensional directed information (MDI) are applied to the 4 channel's frequency components. The information capacity, which is the amount of information propagation to flow out of a specific signal to other ones, is computed. The information flow is then used as the feature of wrist motions in a preprocessing, followed by a neural network and motion recognition by the EMG signal is carried out. Finally, in order to demonstrate the effectiveness of the proposed method, computer simulations are carried out for the wrist motions recognition.