Spectral Frequency Analysis of Upper-Extremity Motor Imagery and Motor Movement Rhythms for Brain Machine Interface

Abstract

A new and exciting field of study called brain-machine interface (BMI) is expected to aid with many issues, particularly for the disabled and paralyzed persons. A wheelchair or robotic arm can be guided in the appropriate way by detecting the left-hand (LH) and right-hand (RH) motor imagery (MI) and motor movements (MM). Electroencephalogram (EEG) sensors just on scalp can detect overall electrical activity caused by these alterations. The frequency spectrum of the EEG signals is crucial for the BMI implementation; hence the left and right hemispheres of the brain rhythms were used to extract the necessary information. For this study, two channels over sensorimotor areas with seven participants during the performance and/or kinesthetic perception of four actions have been chosen. The activity was shown using both MI and MM while being asked to open and close the left fist and the right fist. Using a Butterworth band pass filter (BBPF), the signals were filtered for the exact range of 8 to 30 HZ. The Fast Fourier Transform (FFT) is then used to investigate the knowledge in the frequency domain. Individuals differed in the MM and MI frequency range. The C3 and C4 electrodes for MM frequency ranges between 8 and 24 Hz are predicted by the algorithm and for the MI frequency ranges, the C3 and C4 electrodes are in the 8–26 Hz range.