This paper puts forward a brain computer interface (BCI) system to realize the hand and wrist control using the ABB Mechanical Arm. This BCI system gathers four kinds of motor imaginary (MI) tasks (hand grasp, hand spread, wrist flexion and wrist extension) electroencephalogram (EEG) signals from 30 electrodes. It utilizes two fifth-order Butterworth Band-Pass Filter (BPF) with different bandwidths and normalization method to achieve the raw MI tasks EEG signals preprocessing. The main challenge of feature extraction is to extract enough representative features from MI tasks to classify them. This proposed BCI system extracts eleven kinds of features in time domain and time-frequency domain and uses mutual information method to reduce the large dimension of the extracted features. In addition, the BCI system applies a single convolutional layer Convolutional neural networks (CNN) with 30 filters to implement the quaternary classification of MI tasks. Compared with early researches, the classification accuracy of this BCI system is increased by about 35%. The actual mechanical arm grasping control experiments verifies that this BCI system has good adaptability.


    Access

    Download


    Export, share and cite



    Title :

    Brain Computer Interface Based on Motor Imagery for Mechanical Arm Grasp Control


    Contributors:
    Shi, Tian-Wei (author) / Chen, Ke-Jin (author) / Ren, Ling (author) / Cui, Wen-Hua (author)

    Publication date :

    2023-07-15


    Remarks:

    Information Technology and Control ; Vol. 52 No. 2 (2023); 358-366 ; 2335-884X ; 1392-124X


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Kinesthetic Motor Imagery Based Brain-Computer Interface for Power Wheelchair Manoeuvring

    T., Jackie / M.P., Paulraj / Adom, A.H. et al. | BASE | 2018

    Free access

    Mobile Robot with Grasp Manipulator: Mechanical Design

    Orozco-Velazquez, R.A. / Silva-Ortigoza, R. / Taud, H. et al. | IEEE | 2014



    Grasp Control: Theory and Practice

    Platt, Robert | NTRS | 2007


    Grasp force control in telemanipulation

    WIKER, STEVEN / DUFFIE, NEIL | AIAA | 1992